Q2 2024 Ginkgo Bioworks Holdings Inc Earnings Call - Q&A

August 8, 2024

Important to updating you on our progress as a reminder, during the presentation today, we will be making forward looking statements, which involve risks and uncertainties. Please refer to our filings with the SEC to learn more about these risks and uncertainties.

Today. In addition to updating you on the quarter, we're going to provide updates on our path towards adjusted EBITDA breakeven, including a deeper dive on how we're executing against our cost reduction targets as well as what we're doing to drive revenue.

Jason: As usual, we'll end with a Q&A session and I'll take questions from analysts investors in the public you can submit those questions to us in advance via acts at hashtag ginkgo results or email investors I can go by <unk> Dot com alright over to you Jason Thanks, Meghan and thanks, everyone for joining us we always start with our mission of making biology easier to engineer and in order to do so, particularly.

Jason: In this quarter and the quarters to come we are focused on three objectives first reaching adjusted EBITDA breakeven, while maintaining a cash margin of safety. We ended this quarter with $730 million in cash and no bank debt. We also made aggressive moves in head count reduction and other reductions that will be reflected in reducing our cash opex spending in the coming quarters.

Jason: Second while we're cutting these costs, we need to keep serving our current customers well are unhappy with our revenue number this quarter, which are indicative of continuing to serve our current customers. This was a big lift for the team alongside our risks and a change in how we are organized but it is early indications are that these changes were effective in improving the efficacy of <unk>.

Jason: Delivery.

Jason: Finally, we want to grow our revenue in solutions and expand into selling tools. So I'm going to cover this more in the strategic session, but we're excited to open our platform directly to our customers' scientists previously it's been something we've just had available to ourselves here. If you can go and were getting that out there and the more democratized way our technology assets in <unk>.

Oh engineering, our world, leading so I'm excited to find more ways to sell them and drive growth.

Speaker Change: As a reminder, in our Q1 call. We noted our annualized opex of about $500 million was simply too high relative to near term revenues to address this we announced the plan to cut those back by $200 million on an annualized basis by mid 'twenty, five including consolidating of our footprint and reduction of our labor expenses across both G&A.

Jason: <unk> and R&D.

Jason: And I think again with our strong cash position, we are well positioned to continue executing on these restructuring efforts.

Speaker Change: I will be providing a detailed update on the cost reduction plan later in this presentation, but for now I'd like to give you a summary of the actions we took in the second quarter relating to head count reduction at present, we have notified approximately 450 employees or roughly 35% of the business that they will be impacted by a reduction in force approximately 300 positions were.

Speaker Change: Impacted as of the end of Q2 and an additional 100 positions are anticipated to be impacted by the end of this year and the remaining 50 by mid 'twenty five these cuts although difficult to make our estimated to save ginkgo over $85 million in annualized cost savings once they're fully implemented and because of these reductions were very much.

Speaker Change: On track to hit our goal of reducing our annualized costs by $100 million by the end of year.

Speaker Change: I know, it's not much consolation, but I do want to take a minute and again. Thank our employees who were let go as part of this reduction enforce they contributed enormously to building ginkgo and we're deeply grateful for it much of what we're doing now I can go with these changes is to establish a firm base for the company that will allow us to then grow and meet the mission that they all are.

Bill: US Bill.

Bill: Now I'm going to get into cost cutting details in the strategic section, but before I do let me hand, it over to Mark to go over the financials. Thank.

Operator: Thanks, as always, for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we will be making forward-looking statements, which involve risks and uncertainties. Please refer to our filings with the SEC to learn more about these risks and uncertainties.

Operator: Thanks as always for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we will be making forward-looking statements which involve risks and uncertainties.

Megan LeDuc: Thanks as always for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we will be making forward-looking statements, which involve risks and uncertainties. Please refer to our filings with the SEC to learn more about these risks and uncertainties. Today, in addition to updating you on the quarter, we are going to provide updates on our path towards Adjusted EBITDA breakeven, including a deeper dive on how we're executing against our cost reduction targets, as well as what we're doing to drive revenue. As usual, we'll end with a Q&A session, and I'll take questions from analysts, investors, and the public. You can submit those questions to us in advance via X at hashtag Ginkgo Results or email investors@ginkgobioworks.com. All right, over to you, Jason.

Mark: Thanks, Jason I'll start with the cell engineering business sell engineering revenue was $36 million in the quarter down 20% compared to the second quarter of 2023 similar to Q1 of this year. This decline was driven primarily by a decrease in revenue from early stage customers, partially offset by growth in revenue from larger customers. We continue.

Operator: Please refer to our filings with the SEC to learn more about these risks and uncertainties. Today, in addition to updating you on the quarter, we are going to provide updates on our paths towards adjusted evaluative break even, including a deeper dive on how we're executing against our cost reduction targets, as well as what we're doing to drive revenue. As usual, we'll end with a Q&A session and I'll take questions from analysts investors in the public. You can submit those questions to us in advance via X at hashtag ginkgo results, or email investors at ginkgobioworks.com.

Our technology assets in bioengineering are world-leading, so I'm excited to find more ways to sell them and drive growth.

Unknown Executive: So I'm excited to find more ways to sell them and drive growth. As a reminder, in our Q1 call, we noted our annualized off X of about $500 million, simply too high relative to near-term revenues.

Operator: Today, in addition to updating you on the quarter, we are going to provide updates on our paths towards adjusted evaluative break even, including a deeper dive on how we're executing against our cost reduction targets, as well as what we're doing to drive revenue. As usual, we'll end with a Q&A session, and I'll take questions from analysts, investors, in the public. You can submit those questions to us in advance via X at hashtag Ginkgo results, or email investors at ginkgobioworks.com.

Speaker Change: All right.

Speaker Change: As a reminder, in our Q1 call we noted our annualized off-ex of about $500,000 was simply too high relative to near-term revenues. To address this, we announced a plan to cut this back by $200,000 on an annualized basis by mid-25, including consolidating of our footprint and reduction of our labor expenses across both G&A and R&D.

Unknown Executive: To address this, we announced a plan to cut this back by $200 million on an annualized basis by mid-2017, including consolidation of our footprint and reduction of our labor expenses across both G&A and R&D. And I think again, with our strong cash position, we're well positioned to continue executing on these restructuring efforts. I will be providing a detailed update on the cost reduction plan later in this presentation, but for now, I'd like to give you a summary of the actions we took in the second quarter relating to headcount reduction.

Mark: To believe the shift to larger cash based customers to be an overall positive shifts.

Mark: In the quarter, we supported a total of 140 active programs across 82 customers on cell engineering platform.

Mark: This represents a 33% increase in active programs year over year with solid growth across most verticals as we discussed on our prior earnings call. We anticipate the nature of programs that we take on with our customers to evolve in the future. Following our recent adjustments to commercial terms and offering.

Jason Kelly: All right, over to you, Jason. Thanks, Megan, and thanks everyone for joining us. We always start with our mission of making biology easier to engineer, and in order to do so, particularly in this quarter and the quarters to come. We're focused on three objectives. First, reaching adjusted evaluative break even while maintaining a cash margin of safety. We ended this quarter with $730 million in cash and no bank debt. We also made aggressive moves in headcount reduction and other reductions that will be reflected in reducing our cash off extending in the coming quarters. Second, while we're cutting these costs, we need to keep serving our current customers as well.

Jason Kelly: All right, over to you, Jason. Thanks, Megan, and thanks everyone for joining us. We always start with our mission of making biology easier to engineer and in order to do so, particularly in this quarter and the quarters to come.

Jason Kelly: Thanks, Megan, and thanks everyone for joining us. We always start with our mission of making biology easier to engineer. In order to do so, particularly in this quarter and the quarters to come, we're focused on three objectives. First, reaching a adjusted EBITDA breakeven while maintaining a cash margin of safety. We ended this quarter with $730 million in cash and no bank debt. We also made aggressive moves in headcount reduction, and other reductions that will be reflected in reducing our cash OpEx spending in the coming quarters. Second, while we're cutting these costs, we need to keep serving our current customers well. I'm happy with our revenue number this quarter, which are indicative of continuing to serve our current customers.

Speaker Change: And I think, again, with our strong cash position, we're well positioned to continue executing on these restructuring efforts.

Speaker Change: I will be providing a detailed update on the cost reduction plan later in this presentation. But for now, I'd like to give you a summary of the actions we took in the second quarter relating to headcount reduction.

Jason Kelly: We're focused on three objectives. First, reaching adjusted evaluative break even while maintaining a cash margin of safety. We ended this quarter with $730 million in cash and no bank debt. We also made aggressive moves in headcount reduction and other reductions that will be reflected in reducing our cash off extending in the coming quarters. Second, while we're cutting these costs, we need to keep serving our current customer as well. I'm happy with our revenue number this quarter, which are indicative of continuing to serve our current customers. This is a big lift for the team alongside a riff and a change in how we are organized, but it's an early indication that these changes were effective in improving the efficacy of our delivery.

Unknown Executive: At present, we have notified approximately 450 employees, or roughly 35% of the business, that they will be impacted by our reduction in force. Approximately 300 positions were impacted as of the end of Q2, and an additional 100 positions are anticipated to be impacted by the end of this year, and the remaining 50 by mid-25. These cuts, although difficult to make, are estimated to save Ginkgo over $85 million in annualized cost savings once they're fully implemented.

Mark: While still very early days the slide gives you some detail on how the nature of programs is changing.

At present, we have notified approximately 450 employees, or roughly 35% of the business, that they will be impacted by our reduction in force.

Mark: We added a total of 18, new programs and contracts in Q2, 2024 of which 10 were generally comparable in size and scope to historically reported new programs.

Speaker Change: Approximately three and a positions were impacted as of the end of Q2 and an additional 100 positions are anticipated to be impacted by the end of this year and the remaining 50 by mid-25.

Mark: Importantly, you'll note that of those 10 deals five include a downstream value share potential.

Jason Kelly: I'm happy with our revenue number this quarter, which are indicative of continuing to serve our current customers. This is a big lift for the team alongside a riff and a change in how we are organized, but it's an early indication that these changes were effective in improving the efficacy of our delivery. Finally, we want to grow our revenue in solutions and expand into selling tools. So I'm going to cover this more in the strategic session, but we're excited to open our platform directly to our customer scientists. Previously, it's been something we've just had available to ourselves here at Ginkgo, and we're getting that out there in a more democratized way.

Jason Kelly: This is a big lift for the team alongside a RIF and a change in how we are organized, but it's an early indication that these changes were effective in improving the efficacy of our delivery. Finally, we want to grow our revenue in solutions and expand into selling tools. So I'm going to cover this more in the strategic session, but we're excited to open our platform directly to our customer scientists. Previously, it's been something we've just had available to ourselves here at Ginkgo, and we're getting that out there in a more democratized way. Our technology assets in bioengineering are world-leading, so I'm excited to find more ways to sell them and drive growth.

Speaker Change: These cuts, although difficult to make, are estimated to save Ginkgo over $80.5 million in annualized cost savings once they're fully implemented. And because of these reductions, we're very much on track to hit our goal of reducing our annualized cost by $100 million by the end of year.

Mark: In addition, we commenced eight other customer contracts in the quarter that represent a variety of small deal archetypes. These are generally much smaller in scope and shorter in duration and includes two lab data as a service deals and the protein characterization space that we signed with a large cap Tech company, which itself is an entirely new customer segments.

Unknown Executive: And because of these reductions, we're very much on track to hit our goal of reducing our annualized cost by $100 million by the end of the year. I know it's not much consolation, but I do want to take a minute and, again, thank our employees who were let go as part of this reduction in force. They contributed enormously to building Ginkgo, and we're deeply grateful for it.

Jason Kelly: Finally, we want to grow our revenue in solutions and expand into selling tools. So I'm going to cover this more in the strategic session, but we're excited to open our platform directly to our customer scientists. Previously, it's been something we've just had available to ourselves here at ginkgo, and we're getting that out there in a more democratized way. Our technology assets in bioengineering are world leading. So I'm excited to find more ways to sell them and drive growth.

Speaker Change: I know it's not much consolation, but I do want to take a minute and again thank our employees who were let go as part of this reduction in force. They contributed enormously to building Gingko and we're deeply grateful for it. Much of what we're doing now at Gingko with these changes is to establish a firm base base.

Mark: The current sales pipeline for both categories of deals are solid and while it's still in its early days. We are encouraged that during the course of a major restructuring we have been able to execute on existing customer programs, while converting new opportunities Jason.

Unknown Executive: Much of what we're doing now at Ginkgo with these changes is to establish a firm base for the company that will allow us to then grow and meet the mission that they all helped us build. Now I'm going to get into cost-cutting details in the strategic section, but before I do, let me hand it over to Mark to go over the financials. Thanks, Jason.

Jason Kelly: Our technology assets in bioengineering are world leading. So I'm excited to find more ways to sell them and drive growth. As a reminder, in our Q1 call, we noted our annualized off-ex of about $500 million was simply too high relative to near-term revenues. To address this, we announced a plan to cut this back by $200 million on an annualized basis by mid-25, including consolidation of our footprint and reduction of our labor expenses across both GNA and R&D. And I think again, with our strong cash position, we're well positioned to continue executing on these restructuring efforts.

Speaker Change: for the company that will allow us to then grow and meet the mission that they all helped us build.

Mark: Jason will speak further about our approach to driving revenue later in the presentation.

Jason Kelly: As a reminder, in our Q1 call, we noted our annualized OpEx of about $500 million was simply too high relative to near-term revenues. To address this, we announced a plan to cut this back by $200 million, on an annualized basis by mid-2025, including consolidating of our footprint and reduction of our labor expenses across both G&A and R&D. And I think, again, with our strong cash position, we're well positioned to continue executing on these restructuring efforts. I will be providing a detailed update on the cost reduction plan later in this presentation, but for now, I'd like to give you a summary of the actions we took in Q2 relating to headcount reduction.

Jason Kelly: As a reminder, in our Q1 call, we noted our annualized off-ex of about $500 million was simply too high relative to near-term revenues. To address this, we announced a plan to cut this back by $200 million on an annualized basis by mid-25, including consolidating of our footprint and reduction of our labor expenses across both GNA and R&D. And I think again, with our strong cash position, we're well positioned to continue executing on these restructuring efforts.

Speaker Change: Now I'm going to get into cost-cutting details in the strategic section, but before I do, let me hand it over to Mark to go over the financials.

Mark: I'll start with the cell engineering business. Cell engineering revenue was $36 million in the quarter, down 20% compared to the second quarter of 2023. Similar to Q1 of this year, this decline was driven primarily by a decrease in revenue from early stage customers, partially offset by growth in revenue from larger customers. We continue to believe the shift to larger cash-based customers to be an overall positive shift. In the quarter, we supported a total of 140 active programs across 82 customers on the cell engineering platform.

Jason: Now turning to bio security, our bio security business generated $20 million of revenue in the second quarter of 2024 at a gross margin of 41%.

Mark: Thanks, Jason. I'll start with the cell engineering business. Cell engineering revenue was $36 million in the quarter, down 20% compared to the second quarter of 2023. Similar to Q1 of this year, this decline was driven primarily by a decrease in revenue from early-stage customers,

Speaker Change: Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract.

Mark: Partly I'll set by growth and revenue from larger customers. We continue to believe the shift to larger cash-based customers to be an overall positive shift.

Speaker Change: And now I will provide more commentary on the rest of the P&L where noted these figures exclude stock based compensation expense, which is shown separately and we're also breaking out in M&A and restructuring related expenses to provide you with additional comparability.

Jason Kelly: I will be providing a detailed update on the cost reductions plan later in this presentation, but for now, I'd like to give you a summary of the actions we took in the second quarter relating to headcount reduction. At present, we have notified approximately 450 employees, a roughly 35% of the business that they will be impacted by our reduction in force. Approximately 300 positions were impacted as of the end of Q2, and an additional 100 positions are anticipated to be impacted by the end of this year, and the remaining 50 by mid-25. These cuts, although difficult to make, are estimated to save GINCO over 80 at $5 million in annualized cost savings once typically implemented.

Speaker Change: In the quarter, we supported a total of 140 active programs across 82 customers on the Cell Engineering Platform.

Mark: This represents a 33% increase in active programs year over year with solid growth across most verticals. As we discussed in our prior earnings call, we anticipate the nature of programs that we take on with our customers to evolve in the future following our recent adjustments to commercial terms and offerings. While still very early days, this slide gives you some detail on how the nature of programs is changing. We added a total of 18 new programs and contracts in Q2 2024, of which 10 were generally comparable in size and scope to historically reported new programs.

Jason Kelly: At present, we have notified approximately 450 employees, or roughly 35% of the business, that they will be impacted by our reduction in force. Approximately 300 positions were impacted as of the end of Q2, and an additional 100 positions are anticipated to be impacted by the end of this year, and the remaining 50 by mid-2025. These cuts, although difficult to make, are estimated to save Ginkgo over $85 million in annualized cost savings once they're fully implemented. And because of these reductions, we're very much on track to hit our goal of reducing our annualized cost by $100 million by the end of the year.

Jason Kelly: These cuts, although difficult to make, are estimated to save GINCO over 80 at $5 million in annualized cost savings once typically implemented. And because of these reductions, we're very much on track to hit our goal of reducing our annualized cost by $100 million by the end of year. I know it's not much consolation, but I do want to take a minute. And again, thank our employees who were let go as part of this reduction in force.

Speaker Change: Starting with Opex R&D expense, excluding stock based comp and M&A and restructuring costs increased from $99 million in the second quarter of 2000 $23 million to $110 million in the second quarter of 2020 for this.

Speaker Change: This represents a 33% increase in active programs year over year with solid growth across most verticals. As we discussed on our prior earnings call, we anticipate the nature of programs that we take on with our customers to evolve in the future, following our recent adjustments to commercial terms and offering.

Speaker Change: This increase was mainly driven by an increase in rent expense and AI related spend.

Speaker Change: While still very early days, this slide gives you some detail on how the nature of programs is changing.

G&A expense, excluding stock based comp and M&A and restructuring costs decreased from $59 million in the second quarter of 2000 $23 million to $45 million in the second quarter of 'twenty 'twenty, four which reflects cost reductions we completed in 2023 importantly, Q2 does not.

Speaker Change: We added a total of 18 new programs and contracts in Q2 2024, of which 10 were generally comparable in size and scope to historically reported new programs.

Jason Kelly: And because of these reductions, we're very much on track to hit our goal of reducing our annualized cost by $100 million by the end of the year. I know it's not much consolation, but I do want to take a minute. And again, thank our employees who were let go as part of this reduction in force. They contributed enormously to building GINCO, and we're deeply grateful for it. Much of what we're doing now at GINCO with these changes is to establish a firm base for the company that will allow us to then grow and meet the mission that they all help us build.

Mark: Importantly, you'll note that of those 10 deals, five included downstream value share potential. In addition, we've commenced other customer contracts in the quarter that represent a variety of small deal architectures. These are generally much smaller in scope and shorter in duration and include two lab data as a service deals in the protein characterization space that we signed with a large cap tech company, which itself is an entirely new customer segment.

Jason Kelly: I know it's not much consolation, but I do want to take a minute, and again, thank our employees who were let go as part of this reduction in force. They contributed enormously to building Ginkgo, and we're deeply grateful for it. Much of what we're doing now at Ginkgo with these changes is to establish a firm base for the company that will allow us to then grow and meet the mission that they all helped us build. Now, I'm going to get into cost-cutting details in the strategic section, but before I do, let me hand it over to Mark to go over the financials.

Speaker Change: Importantly, you'll know that of those 10 deals, 5 include a downstream value share of potential.

Jason Kelly: They contributed enormously to building GINCO, and we're deeply grateful for it. Much of what we're doing now at GINCO with these changes is to establish a firm base for the company that will allow us to then grow and meet the mission that they all help us build.

Speaker Change: In addition, we commenced eight other customer contracts in the quarter that represent a variety of small deal archetypes.

Speaker Change: Like the benefits of our head count reduction since those only commenced at the end of June and so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year, the M&A and restructuring related costs. This quarter includes a goodwill impairment charge of $48 million other.

Speaker Change: These are generally much smaller in scope and shorter in duration and include two lab data as a service deals in the protein characterization space that we signed with a large cap tech company which itself is an entirely new customer segment.

Mark Massaro: Now, I'm going to get into cost-cutting details in the strategic section, but before I do, let me hand it over to Mark to go over the financials.

Mark Massaro: Now, I'm going to get into cost-cutting details in the strategic section, but before I do, let me hand it over to Mark to go over the financials. Thanks, Jason.

Mark: The current sales pipeline for both categories of deals is solid, and while it's still in its early days, we are encouraged that, during the course of a major restructuring, we have been able to execute on existing customer programs while converting new opportunities. Jason will speak further about our approach to driving revenue later in the presentation. Now turning to biosecurity, our biosecurity business generated $20 million of revenue in the second quarter of 2024 at a gross margin of 41%. Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract.

Speaker Change: Other costs relating to restructuring such as severance.

Mark Dmytruk: Thanks, Jason. I'll start with the cell engineering business. Cell engineering revenue was $36 million in the quarter, down 20% compared to the second quarter of 2023. Similar to Q1 of this year, this decline was driven primarily by a decrease in revenue from early-stage customers, partially offset by growth in revenue from larger customers. We continue to believe the shift to larger cash-based customers to be an overall positive shift. In the quarter, we supported a total of 140 active programs across 82 customers on the cell engineering platform. This represents a 33% increase in active programs year-over-year, with solid growth across most verticals. As we discussed on our prior earnings call, we anticipate the nature of programs that we take on with our customers to evolve in the future following our recent adjustments to commercial terms and offering.

Mark Massaro: Thanks, Jason.

Mark Massaro: I'll start with the Cell Engineering Business. Cell engineering revenue was $36 million in the quarter, down 20% compared to the second quarter of 2023. Similar to Q1 of this year, this decline was driven primarily by a decrease in revenue from early stage customers, partially offset by growth in revenue from larger customers. We continue to believe the shift to larger cash-based customers to be an overall positive shift. In the quarter, we supported a total of 140 active programs across 82 customers on the Cell Engineering platform. This represents a 33% increase in active programs year over year, with solid growth across most verticals.

Mark Massaro: I'll start with the Cell Engineering Business. Cell Engineering revenue was $36 million in the quarter, down 20% compared to the second quarter of 2023. Similar to Q1 of this year, this decline was driven primarily by a decrease in revenue from early stage customers, partially offset by growth in revenue from larger customers. We continue to believe the shift to larger cash-based customers to be an overall positive shift. In the quarter, we supported a total of 140 active programs across 82 customers on the Cell Engineering platform.

Speaker Change: The current sales pipeline for both categories of deals is solid, and while it's

Speaker Change: And costs relating to smaller M&A transactions that we closed early in the quarter a full reconciliation of this line item can be found in the appendix to this presentation.

Speaker Change: Still in its early days, we are encouraged that during the course of a major restructuring, we have been able to execute on existing customer programs while converting new opportunities. Jason will speak further about our approach to driving revenue later in the presentation.

Speaker Change: Stock based comp you will again notice a significant drop in stock based comp this quarter similar to what we have seen over the past year as we complete the roll off of the original catch up accounting adjustment related to the modification of restricted stock units. When we went public additional details are provided in the appendix.

Jason: Now, turning to biosecurity. Our biosecurity business generated $20 million of revenue in the second quarter of 2024 at a gross margin of 41%. Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract.

Mark Massaro: This represents a 33% increase in active programs year over year with solid growth across most verticals. As we discussed on our prior earnings call, we anticipate the nature of programs that we take on with our customers to evolve in the future following our recent adjustments to commercial terms and offering. While still very early days, this slide gives you some detail on how the nature of programs is changing. We added a total of 18 new programs in contracts in Q2 2024, of which 10 were generally comparable in size and scope to historically reported new programs.

Speaker Change: Net loss it is important to note that our net loss includes a number of noncash income <unk> expenses as detailed more fully in our financial statements.

Mark: And now I'll provide more commentary on the rest of the P&L. Where noted, these figures exclude stock-based compensation expense, which is shown separately. And we are also breaking out M&A and restructuring-related expenses to provide you with additional comparability. Starting with OPEX, R&D expense excluding stock-based comp and M&A and restructuring costs increased from $99 million in the second quarter of 2023 to $110 million in the second quarter of 2024. This increase was mainly driven by an increase in rent expense and AI-related spend.

Mark Massaro: As we discussed on our prior earnings call, we anticipate the nature of programs that we take on with our customers to evolve in the future following our recent adjustments to commercial terms and offering. While still very early days, this slide gives you some detail on how the nature of programs is changing. We added a total of 18 new programs in contracts in Q2 2024, of which 10 were generally comparable in size and scope to historically reported new programs. Importantly, you'll know that of those 10 deals, five included downstream value share potential. In addition, we've commenced eight other customer contracts in the quarter that represent a variety of small-deal archetypes.

Speaker Change: And now I'll provide more commentary on the rest of the P&L. Where noted, these figures exclude stock-based compensation expense, which is shown separately. And we are also breaking out M&A and restructuring-related expenses to provide you with additional comparability.

Speaker Change: Because of these noncash and other nonrecurring items, we believe adjusted EBITDA is a more indicative measure of our profitability. We've also included a reconciliation of adjusted EBITDA to net loss in the appendix.

Mark Dmytruk: While still very early days, this slide gives you some detail on how the nature of programs is changing. We added a total of 18 new programs and contracts in Q2 2024, of which 10 were generally comparable in size and scope to historically reported new programs. Importantly, you'll note that of those 10 deals, five included downstream value share potential. In addition, we commenced eight other customer contracts in the quarter that represent a variety of small deal archetypes. These are generally much smaller in scope and shorter in duration and include two Lab Data as a Service deals in the protein characterization space that we signed with a large cap tech company, which itself is an entirely new customer segment.

Mark Massaro: Importantly, you'll know that of those 10 deals, five included downstream value share potential. In addition, we've commenced eight other customer contracts in the quarter that represent a variety of small-deal archetypes. These are generally much smaller in scope and shorter in duration and included two lab data as a service deals in the protein characterization space that we signed with a large cap tech company, which itself is an entirely new customer segment. The current sales pipeline for both categories of deals of solid, and while it's still in this early days, we encourage that during the course of a major restructuring, we have been able to execute on existing customer programs while converting new opportunities.

Speaker Change: Starting with OptX, R&D expense excluding stock-based comp and M&A's restructuring costs.

Speaker Change: Adjusted EBITDA in the quarter was negative $99 million, which was down from negative $80 million in Q2 2023.

Speaker Change: Increase from $99 million in the second quarter of 2023 to $110 million in the second quarter of 2024. This increase was mainly driven by an increase in rent expense and AI related spend.

Speaker Change: This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses in.

Mark: GNA expense, excluding stock-based comp and M&A and restructuring costs, decreased from $59 million in the second quarter of 2023 to $45 million in the second quarter of 2024, which reflects cost reductions we completed in 2023. Importantly, Q2 does not reflect the benefits of our headcount reduction.

Speaker Change: In addition, I would like to note that we are now reporting adjusted EBITDA inclusive of noncash in process R&D charges relating to acquisitions and so we have separately itemized that amount for you here.

Speaker Change: G&A expense, excluding stock-based comp and M&A and restructuring costs.

Mark Massaro: These are generally much smaller in scope and shorter in duration and included two lab data as a service deals in the protein characterization space that we signed with a large cap tech company, which itself is an entirely new customer segment. The current sales pipeline for both categories of deals is solid, and while it's still in these early days, we encourage that during the course of a major restructuring, we have been able to execute on existing customer programs while converting new opportunities.

Speaker Change: decreased from $59 million in the second quarter of 2023 to $45 million in the second quarter of 2024, which reflects cost reductions we completed in 2023. Importantly, Q2 does not reflect the benefits of our headcount reduction.

Speaker Change: And finally, the Capex in the second quarter of 2024 was $13 million net of tenant improvement allowance as we continue to build out the bio fab one facility.

Mark Dmytruk: The current sales pipeline for both categories of deals is solid, and while it's still in its early days, we are encouraged that during the course of a major restructuring, we have been able to execute on existing customer programs while converting new opportunities. Jason will speak further about our approach to driving revenue later in the presentation. Now, turning to Biosecurity. Our Biosecurity business generated $20 million of revenue in the second quarter of 2024, at a gross margin of 41%. Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract. Now I'll provide more commentary on the rest of the P&L. Where noted, these figures exclude stock-based compensation expense, which is shown separately, and we are also breaking out M&A and restructuring-related expenses to provide you with additional comparability.

Mark: Since those only commence at the end of June, and so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year. The M&A and restructuring-related costs this quarter include a goodwill impairment charge of $48 million. Other costs relating to restructuring, such as severance, and costs relating to smaller M&A transactions that we closed early in the quarter. A full reconciliation of this line item can be found in the appendix to this presentation.

Speaker Change: Yeah.

Speaker Change: Since those only commence at the end of June , and so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year. The M&A and restructuring related costs this quarter includes a goodwill impairment charge of $48 million.

Speaker Change: In terms of outlook for the full year, we are reaffirming our guidance for 'twenty to 'twenty four with cell engineering revenue expected to be $120 million to $140 million and bio security revenue expected to be at least $50 million totaling $170 million to $190 million.

Jason Kelly: Jason will speak further about our approach to driving revenue later in the presentation.

Mark Massaro: Now, turning to biosecurity, our biosecurity business generated $20 million of revenue in the second quarter of 2024 at a gross margin of 41%. Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract. And now, we'll provide more commentary on the rest of the PNL. We're noted these figures exclude stock-based compensation expense, which is shown separately. And we are also breaking out M&A and restructuring-related expenses to provide you with additional comparability. Starting with OPEX, R&D expense excluding stock-based comp and M&A and restructuring costs increase from $99 million in the second quarter of 2023 to $110 million in the second quarter of 2024.

Mark Massaro: Now, turning to biosecurity, our biosecurity business generated $20 million of revenue in the second quarter of 2024 at a gross margin of 41%. Revenue and gross margin were up significantly in Q2 due to the timing of a customer contract. And now, we'll provide more commentary on the rest of the PNL. We're noted these figures exclude stock-based compensation expense, which is shown separately. And we are also breaking out M&A and restructuring related expenses to provide you with additional comparability.

Speaker Change: Other costs relating to restructuring, such as severance, and costs relating to smaller M&A transactions that we closed early in the quarter. A full reconciliation of this line item can be found in the appendix to this presentation.

Speaker Change: In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes, which we see is foundational to our path to adjusted EBITDA breakeven.

Mark: Stock-based comp. You'll again notice a significant drop in stock-based comp this quarter, similar to what we have seen over the past year, as we complete the roll-off of the original catch-up accounting adjustment related to the modification of restricted stock units when we went public. Additional details are provided in the appendix.

Speaker Change: Stock-based comp. You'll again notice a significant drop in stock-based comp this quarter, similar to what we have seen over the past year, as we complete the roll-off of the original catch-up accounting adjustment related to the modification of restricted stock units when we went public.

Jason: Back over to you, Jason Thanks, Mark I'm going to use the first strategic section to focus on getting those efforts to reduce costs as that is currently my primary focus.

Speaker Change: Again because of unique player in the life science tools industry, where more than 100 active cell engineering programs running on our platform across Biopharma industrial and agricultural biotechnology, and we have a unique scale and breadth in both automation and software and cell engineering.

Mark: Net loss. It is important to note that our net loss includes a number of non-cash income and or expenses as detailed more fully in our financial statement. Because of these non-cash and other non-recurring items, we believe adjusted EVA debt is a more indicative measure of our profitability. We've also included a reconciliation of adjusted EVA debt to net loss in the appendix. Adjusted even down, the corridor was negative $99 million, which was down from negative $80 million in Q2 2023. This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses.

Speaker Change: Additional details are provided in the appendix.

Mark Massaro: Starting with OPEX, R&D expense excluding stock-based comp and M&A and restructuring costs increase from $99 million in the second quarter of 2023 to $110 million in the second quarter of 2024. This increase was mainly driven by an increase in rent expense and AI-related spend. G&A expense excluding stock-based comp and M&A and restructuring costs decreased from $59 million in the second quarter of 2023 to $45 million in the second quarter of 2024, which reflects cost reductions we completed in 2023.

Mark Dmytruk: Starting with OpEx, R&D expense, excluding stock-based comp, M&A, and restructuring costs, increased from $99 million in Q2 2023 to $110 million in Q2 2024. This increase was mainly driven by an increase in rent expense and AI-related spend. G&A expense, excluding stock-based comp, M&A, and restructuring costs, decreased from $59 million in Q2 2023 to $45 million in Q2 2024, which reflects cost reductions we completed in 2023. Importantly, Q2 does not reflect the benefits of our headcount reduction, since those only commenced at the end of June, and so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year.

Speaker Change: Net loss. It is important to note that our net loss includes a number of non-cash income and or expenses as detailed more fully in our financial statements.

We can deliver on that services business profitably and we're focused on demonstrating that as quickly as we can I'll cover how we're taking out costs, while maintaining delivery for our customers. Our second I want to talk about how we see the opportunity for growth I cant go by opening our platform up directly to our customers' scientists while.

Speaker Change: Because of these non-cash and other non-recurring items, we believe a judge that even does a more indicative measure of our profitability. We've also included a reconciliation of a judge that even denets a net loss in the appendix.

Mark Massaro: This increase was mainly driven by an increase in rent expense and AI-related spend. G&A expense excluding stock-based comp and M&A and restructuring costs decreased from $59 million in the second quarter of 2023 to $45 million in the second quarter of 2024, which reflects cost reductions we completed in 2023. Importantly, Q2 does not reflect the benefits of our headcount reduction since those only commence at the end of June. And so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year. The M&A and restructuring related costs this quarter includes a goodwill impairment charge of $48 million.

Speaker Change: The just that even down in the court, it was negative $99 million, which was down from negative $80 million in Q2 2023.

Speaker Change: <unk>, our existing service offerings around our areas of strength.

And then finally I'd like to spend some time, highlighting a growth opportunity within bio security as it tackles emerging threats and modalities, specifically H five N one or bird flu, okay, let's get started.

Speaker Change: This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses.

Mark: In addition, I would like to note that we are now reporting adjusted EBITDA inclusive of non-cash in-process R&D charges relating to acquisitions. And so, we have separately itemized that amount for you here. And finally, CapEx in the second quarter of 2024 was $13 million net of tenant improvement allowance as we continue to build out the BioFab 1 facility. In terms of outlook for the full year, we are reaffirming our guidance for 2024, with cell engineering revenue expected to be $120 to $140 million and biosecurity revenue expected to be at least $50 million, totaling $170 to $190 million.

Mark Massaro: Importantly, Q2 does not reflect the benefits of our headcount reduction since those only commence at the end of June. And so we would expect both R&D and G&A expenses to decrease meaningfully by Q4 of this year. The M&A and restructuring related costs this quarter includes a goodwill impairment charge of $48 million. Other costs relating to restructuring such as submarines and costs relating to smaller M&A transactions that we close early in the quarter.

Speaker Change: In addition, I would like to note that we are now reporting adjusts that he was an inclusive of non-cash in process R&D charges relating to acquisitions. And so we have separately itemized that amount for you here.

Speaker Change: During our Q1 call, we announced our plans to cut spending backed by a run rate of $100 million by Q4 2024 with an additional 100 million expected to come out by mid 'twenty five.

Mark Dmytruk: The M&A and restructuring-related costs this quarter includes a goodwill impairment charge of $48 million, other costs relating to restructuring, such as severance, and costs relating to smaller M&A transactions that we closed early in the quarter. A full reconciliation of this line item can be found in the appendix to this presentation. Stock-based comp. You'll again notice a significant drop in stock-based comp this quarter, similar to what we have seen over the past year, as we complete the roll-off of the original catch-up accounting adjustment related to the modification of restricted stock units when we went public. Additional details are provided in the appendix. Net loss. It is important to note that our net loss includes a number of non-cash income and/or expenses, as detailed more fully in our financial statements.

Speaker Change: Earlier on this call I mentioned that we expect to see over $85 million in annualized cost savings from a reduction in force as you can see from this chart of the approximate $85 million, we expect to say by mid 25 $75 million of that is expected to be achieved on an annualized run rate basis and 24 based on actions we've already taken.

Speaker Change: and finally a cat accident, the second quarter of 2024, was $13 million net of tenant improvement allowance as we continue to build out the biofound one facility.

Mark Massaro: Other costs relating to restructuring, such as submarines and costs relating to smaller M&A transactions that we close early in the quarter. A full reconciliation of this line item can be found in the appendix to this presentation. Stock-based comp. You'll again notice a significant drop in stock-based comp for this quarter, similar to what we have seen over the past year, as we complete the roll-off of the original catch-up accounting adjustment related to the modification of restricted stock units when we went public. Additional details are provided in the appendix. Net loss; it is important to note that our net loss includes a number of non-cash income and/or expenses, as detailed more fully in our financial statements.

Mark Massaro: A full reconciliation of this line item can be found in the appendix to this presentation. Stock-based comp. You'll again notice a significant drop in Stock-based comp for this quarter, similar to what we have seen over the past year, as we complete the roll-off of the original catch-up accounting adjustment related to the modification of restricted stock units when we went public. Additional details are provided in the appendix. Net loss, it is important to note that our net loss includes a number of non-cash income and or expenses as detailed more fully in our financial statements.

Speaker Change: In terms of outlook for the full year, we are reaffirming our guidance for 2024, with cell engineering revenue expected to be $120 to $140 million, and biosecurity revenue expected to be at least $50 million, totaling $170 to $190 million.

Speaker Change: In addition to the people cost savings we've taken actions expected to result in an additional $25 million in annualized cost savings by the end of year.

Speaker Change: Putting us on track to hit our goal of reducing costs by 100 million by end of 24 on a run rate basis.

Mark: In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes which we see as foundational to our path to adjusted EBITDA breakeven. Back over to you, Jason. Thanks, Mark.

Speaker Change: Because we are still in progress with the majority of the non people costs cutting initiatives I'd like to take a minute and dive deeper into what we're planning to reduce costs there.

Speaker Change: In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes which we see as foundational to our path to adjusted EBITDA breakeven.

So we've established a number of internal work streams, I think 19 or something so.

Jason: Thanks, Mark. I'm gonna use the first strategic section to focus on Ginkgo's efforts to reduce costs, as that's currently my primary focus. Ginkgo's a unique player in the life science tools industry. We have more than 100 active cell engineering programs running on our platform across biopharma, industrial, and agricultural biotechnology, and we have a unique scale and breadth in both automation and software in cell engineering.

Speaker Change: Focusing on major spending areas a few examples.

Speaker Change: Back over to you, Jason.

Jason: Thanks, Mark. I'm going to use the first strategic section to focus on Ginkgo's efforts to reduce costs, as that's currently my primary focus.

Mark Massaro: Because of these non-cash and other non-recurring items, we believe that even does a more indicative measure of our profitability. We've also included a reconciliation of adjusted EVA-Data to net loss in the appendix. Adjusted EVA-deta in the court was negative $99 million, which was down from negative $80 million in Q2 2023. This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses. In addition, I would like to note that we are now reporting adjusted EVA-deta, inclusive of non-cash in-process R&D charges relating to acquisitions. And so we have separately itemized that amount for you here.

Mark Dmytruk: Because of these non-cash and other non-recurring items, we believe Adjusted EBITDA is a more indicative measure of our profitability. We've also included a reconciliation of Adjusted EBITDA to net loss in the appendix. Adjusted EBITDA in the quarter was negative $99 million, which was down from negative $80 million in Q2 2023. This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses. In addition, I would like to note that we are now reporting Adjusted EBITDA inclusive of non-cash in-process R&D charges relating to acquisitions, and so we have separately itemized that amount for you here. And finally, CapEx in the second quarter of 2024 was $13 million net of tenant improvement allowance, as we continue to build out the BioFab1 facility.

Mark Massaro: Because of these non-cash and other non-recurring items, we believe that even does a more indicative measure of our profitability. We've also included a reconciliation of adjusted eva-deta to net loss in the appendix. Adjusted eva-deta in the court was negative $99 million, which was down from negative $80 million in Q2 2023. This decline was driven by a decrease in total revenue, partially offset by a decrease in certain operating expenses. In addition, I would like to note that we are now reporting adjusted eva-deta, inclusive of non-cash in process R&D charges relating to acquisitions.

Speaker Change: Mining third party costs, we're focusing on realizing efficiency with our vendors not for strategic sourcing and renegotiations. Additionally, we're reducing our dependence on third party technical work and consulting as well as external legal services.

Jason: Ginkgo is a unique player in the life science tools industry. We have more than 100 active cell engineering programs running on our platform, across biopharma, industrial, and agricultural biotechnology, and we have a unique scale and breadth in both automation and software in cell engineering.

Speaker Change: We're reducing as I mentioned previously our real estate footprints actively.

Jason: We can deliver on that services business profitably, and we're focused on demonstrating that as quickly as we can. I'll describe how we're taking out costs while maintaining delivery for our customers. Second, I want to talk about how we see the opportunity for growth at Ginkgo by opening our platform up directly to our customers' scientists, while focusing our existing service offerings around our areas of strength. And then, finally, I'd like to spend some time highlighting a growth opportunity within biosecurity as it tackles emerging threats and modalities, specifically H5N1 or BIRDS. Okay, let's get started.

Speaker Change: And looking for sublease opportunities there as well.

Jason: We can deliver on that service as business profitably and we're focused on demonstrating that as quickly as we can. I'll cover how we're taking out costs while maintaining delivery for our customers.

Speaker Change: Equipment cost alignment, we're adjusting our equipment expenses and related service contracts to match. The current utilization and then we will scale into demand as it comes in.

We're undertaking a significant effort to rationalize our software portfolio a lot of enterprise software by reducing licenses and consolidating applications overall on the on the technical side, both in the lab and with software we have a lot of historical data now on what infrastructure really pays off across these hundreds of programs. We've done I think go.

Jason: Second, I want to talk about how we see the opportunity for growth at Ginkgo by opening our platform up directly to our customer scientists while focusing our existing service offerings around our areas of strength.

Mark Massaro: And so we have separately itemized that amount for you here. And finally, a cap-axe in the second quarter of 2024 was $13 million net of tenant improvement allows as we continue to build out the BioFab1 facility.

Mark Massaro: And finally, a cap-axe in the second quarter of 2024 was $13 million net of tenant improvement allows as we continue to build out the BioFab1 facility.

Jason: And then finally, I'd like to spend some time highlighting a growth opportunity within biosecurity as it tackles emerging threats and modalities, specifically H5N1 or bird flu.

Jason: During our Q1 call, we announced our plans to cut spending back by a run rate of $100 million by Q4 2024, with an additional $100 million expected to come out by mid-25. Earlier in this call, I mentioned that we expect to see over $85 million in annualized cost savings from our reduction in force. As you can see from this chart, of the approximate $85 million, we expect to save by mid-25, $75 million of that is expected to be achieved on an annualized run rate basis in 2024, based on actions we've already taken. In addition to the people cost savings, we've taken actions expected to result in an additional $25 million in annualized cost savings by the end of the year.

Speaker Change: So we've been able to make good decisions decisive decisions quickly in this area and so I'm excited to see that play out and save us save us money okay.

Jason: Okay, let's get started.

Jason: During our Q1 call, we announced our plans to cut spending back by a run rate of $100 million by Q4 2024, with an additional $100 million expected to come out by mid-25.

Mark Massaro: In terms of outlook for the full year, we are reaffirming our guidance for 2024, with sell engineering revenue expected to be $120 to $140 million and BioSecurity revenue expected to be at least $50 million, totaling $170 to $190 million.

Mark Massaro: In terms of outlook for the full year, we are reaffirming our guidance for 2024 with sell engineering revenue expected to be $120 to $140 million and BioSecurity Revenue expected to be at least $50 million, totaling $107 to $190 million.

Mark Dmytruk: In terms of outlook for the full year, we are reaffirming our guidance for 2024, with cell engineering revenue expected to be $120 to $140 million, and biosecurity revenue expected to be at least $50 million, totaling $170 to $190 million. In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes, which we see as foundational to our path to adjusted EBITDA breakeven. Back over to you, Jason.

Speaker Change: Okay importantly, alongside our cost cutting initiatives, we're continuing to deliver for our customers. This is key so.

So recently, we read.

Jason: Earlier on this call, I mentioned that we expect to see over $85 million in annualized cost savings.

Speaker Change: Delivered on a major technical milestone for a previously announced large biopharma customer. We have are in the midst of all of these restructuring efforts. Marc mentioned, we were able to sign for new agriculture deals the largest of which was with Syngenta, where we're optimizing and microbial strains from their biologics pipeline. This is a molecule that they've earmarked as a pioneering.

Jason: from our reduction in force. As you can see from this chart of the approximate $85 million, we expect to save by mid-25. $75 million of that is expected to be achieved on an annualized run rate basis in 24 based on actions we've already taken.

Jason Kelly: In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes, which we see as foundational to our path to adjusted EVA-deta break even.

Mark Massaro: In conclusion, we're pleased with our overall execution of the restructuring thus far as we navigate substantial cost reductions and commercial changes, which we see as foundational to our path to adjusted eva-deta break even.

Jason: In addition to the people cost savings, we've taken actions expected to result in an additional $25 million in annualized cost savings by the end of year.

Speaker Change: Biological solution that syngenta successful cost effective and large scale production of this metabolite wood expediate their go to market timeline for these biological solutions.

Jason Kelly: Back over to you, Jason. Thanks, Mark. I'm going to use the first strategic section to focus on Ginkgo's efforts to reduce costs, as that's currently my primary focus. Ginkgo is a unique player in the life science tools industry. We're more than 100 active sell engineering programs running on our platform, cross-bioforma industrial and agricultural biotechnology, and we have a unique scale in breadth in both automation and software and sell engineering. We can deliver on that services business profitably, and we're focused on demonstrating that as quickly as we can. I'll cover how we're taking out costs while maintaining delivery for our customers.

Jason: Putting us on track to hit our goal. By a hundred million by, with a majority I'd like to take, dive deeper into what we are. There are a number of interns. Frank Keane, on major spending, At 30 costs.

Jason Kelly: Back over to you, Jason. Thanks, Mark. I'm going to use the first strategic section to focus on Ginkgo's efforts to reduce costs, as that's currently my primary focus.

Jason Kelly: Thanks, Mark. I'm going to use the first strategic section to focus on Ginkgo's efforts to reduce costs, as that's currently my primary focus. Ginkgo is a unique player in the life science tools industry. We have more than 100 active cell engineering programs running on our platform across biopharma, industrial, and agricultural biotechnology, and we have a unique scale and breadth in both automation and software in cell engineering. We can deliver on that services business profitably, and we're focused on demonstrating that as quickly as we can. I'll cover how we're taking out costs, while maintaining delivery for our customers.

Speaker Change: I think that's what I'm trying to hit our goal.

Speaker Change: Next as Mark mentioned, we signed our first two we call them L. Das lab data as a service deals with a large cap Tech company and we're excited to execute on those in the near term and lastly, I'd like to reiterate we're reaffirming guidance and are confident in our ability is to continue executing for our customers. While we act on these cost cutting initiatives.

Jason: by a hundred million

Jason Kelly: Ginkgo is a unique player in the life science tools industry. We're more than 100 active sell engineering programs running on our platform, cross-bioforma industrial and agricultural biotechnology, and we have a unique scale in breadth in both automation and software and sell engineering. We can deliver on that services business profitably, and we're focused on demonstrating that as quickly as we can. I'll cover how we're taking out costs while maintaining delivery for our customers.

Jason: with the majority.

Jason: I'd like to take...

Jason: and I deeper into what we're doing.

Speaker Change: There's a number of interns.

Jason: Thank you.

Speaker Change: on major spending

Jason: Pricing Efficiency with our thing and renegotiation. Just really, we're reducing our External Legal Service. We're reducing as I actively, and looking is there as well. We're adjourned, in service contracts. A Current Utilization. Unknown Speaker, Software Portfolio. Surprise Software application, both in the lab. Square.

Speaker Change: I want to take a minute and thank the team at Ginkgo, who handled really just a crazy last to deliver so well on customer programs in the same quarter, where we had such a large amount of organizational change that's going to get easier I going into the future, but that was no small feat and it's a testament to the strong culture at the company and our focus on delivering for customers.

Speaker Change: Good call.

Jason: I think efficiency will not.

Speaker Change: Teng and Rina Gociation.

Jason Kelly: Second, I want to talk about how we see the opportunity for growth at Ginkgo by opening our platform up directly to our customer's scientists while focusing our existing service offerings around our areas of strength. And then finally, I'd like to spend some time highlighting a growth opportunity within BioSecurity as it tackles emerging threats and modalities, specifically H5N1 or bird flu. Okay, let's get started.

Jason Kelly: Second, I want to talk about how we see the opportunity for growth at Ginkgo by opening our platform up directly to our customers' scientists while focusing our existing service offerings around our areas of strength. And then finally, I'd like to spend some time highlighting a growth opportunity within biosecurity as it tackles emerging threats and modalities, specifically H5N1, or bird flu. Okay, let's get started. During our Q1 call, we announced our plans to cut spending back by a run rate of $100 million by Q4 2024, with an additional $100 million expected to come out by mid-2025. Earlier on this call, I mentioned that we expect to see over $85 million in annualized cost savings from our reduction in force.

Speaker Change: Additionally, we're reducing our

Jason: External Legal Services.

Speaker Change: What are we doing as I make it?

Speaker Change: actively and looking forward to working with them in the future.

Speaker Change: <unk>.

Jason: We're there as well.

Speaker Change: That's an update on where we expect our cost takeout to come from and next I want to talk about how we're building the tools and solutions that are going to grow again goes revenue going forward.

Jason: We're adjourned.

Jason: in service contracts.

Jason: A Current Utilization

Speaker Change: So like these two images if you look how the work of engineering cells is done today. It looks like this picture on the left Alright lab bench and first of all I want to say that it's a little frustrating because this is exactly what my lab bench looked like in graduate school at M. I T 20 years ago.

Jason Kelly: During our Q1 call, we announce our plans to cut spending back by a run rate of $100 million by Q4 2024, with an additional $100 million expected to come out by mid-25. Earlier on this call, I mentioned that we expect to see over $85 million in annualized cost savings from our reduction in force. As you can see from this chart of the approximate $85 million, we expect to save by mid-25, 75 million of that is expected to be achieved on an annualized run rate basis in 24. Based on actions we've already taken. In addition to the people cost savings, we've taken actions expected to result in an additional $25 million in annualized cost savings by the end of the year.

Marjoleine Armstrong: Marjoleine Armstrong,

Speaker Change: Software Portfolio

Jason: Enterprise Software

Jason: Applications.

Jason: and both in the lab.

Jason Kelly: Earlier on this call, I mentioned that we expect to see over $85 million in annualized cost savings from our reduction in force. As you can see from this chart of the approximate $85 million, we expect to save by mid-25, 75 million of that is expected to be achieved on an annualized run rate basis in 24. Based on actions we've already taken. In addition to the people cost savings, we've taken actions expected to results in an additional $25 million in annualized cost savings by the end of year.

Jason: Square, we have

Jason: We have, a law hundreds of programs. Good Decisions, Decisive. Unknown Events, Save Us Money. Importantly, along, We're continuing to... So return our, Technical Milestone. Biopharma customer. Production Efforts, Mark Bradley. Agriculture Deal, Syngenta, screen. Fine.

Speaker Change: And I promise you if you walked into the computer Science Department at M. I E. The tools available to researchers would be wildly different from 20 years ago, but in biotech.

Speaker Change: A-Law, okay.

Jason Kelly: As you can see from this chart, of the approximate $85 million we expect to save by mid-2025, $75 million of that is expected to be achieved on an annualized run rate basis in 2024, based on actions we've already taken. In addition to the people cost savings, we've taken actions expected to result in an additional $25 million in annualized cost savings by the end of the year, putting us on track to hit our goal of reducing costs by $100 million by end of 2024 on a run rate basis. Because we are still in progress with the majority of the non-people cost cutting initiatives, I'd like to take a minute and dive deeper into what we're planning to reduce costs there.

Speaker Change: hundreds of programs.

Speaker Change: Good decisions, the fight.

Jason: this area.

Speaker Change: The tools are changed a lot less than you would expect.

Jason: Save us money.

Jason: Importantly, along.

Speaker Change: And honestly I thought about this and I think it's because this set of tools is actually pretty great for what it's intended to do it allowed bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of days right. They can go in that thermo catalog in order whatever reagents I just read about in the paper pick up a pipette and get to work.

Jason: We're continuing to.

Jason: So reach out to us. Thank you.

Speaker Change: Michael Miles Stone

Jason Kelly: Putting us on track to hit our goal of reducing costs by 100 million by end of 24 on a run rate basis.

Jason Kelly: Putting us on track to hit our goal of reducing costs by 100 million by end of 24 on a run rate basis. Because we are still in progress with the majority of the non-people cost-cutting initiatives, I'd like to take a minute and dive deeper into what we're planning to reduce costs there. So we've established a number of internal work streams, I think 19 or something, focusing on major spending areas, a few examples, streamlining third-party costs.

Speaker Change: by Pharmacosumer.

Jason Kelly: Because we are still in progress with the majority of the non-people cost-cutting initiatives, I'd like to take a minute and dive deeper into what we're planning to reduce costs there. So we've established a number of internal work streams, I think 19 or something, focusing on major spending areas. A few examples: streamlining third-party costs. We're focusing on realizing efficiency with our vendors, strategic sourcing, and renegotiations. Additionally, we're reducing our dependence on third-party technical work and consulting. As well as external legal services. We're reducing, as I mentioned previously, our real estate footprints actively and looking for subtle opportunities there as well.

Speaker Change: We're not showing up for his Mark Dmyt [inaudible]

Speaker Change: Agriculture Deal

Speaker Change: St. Jenza

Jason: This is a Pioneering Biological Success and large-scale production of their go-to-market timeline. Next. We call them... as a service. Arj Kapteka.

Speaker Change: And for many problems this set of tools and a by hand approach to doing lab work is the best solution right. The big Downsides of this approach, though is that since it's manual youre doing it by hand, there are no advantages to scale in other words, it doesn't get cheaper or higher quality as you do more of this genetic engineering.

Speaker Change: Brain Up

Speaker Change: This is a mock interview.

Jason Kelly: So we've established a number of internal work streams, I think 19 or something, focusing on major spending areas. A few examples, streamlining third-party costs. We're focusing on realizing efficiency with our vendors through strategic sourcing and renegotiations. Additionally, we're reducing our dependence on third-party technical work and consulting, as well as external legal services. We're reducing, as I mentioned previously, our real estate footprints actively and looking for sublease opportunities there as well. Equipment cost alignment. We're adjusting our equipment expenses and related service contracts to match the current utilization, and then we'll scale into demand as it comes in. We're undertaking a significant effort to rationalize our software portfolio, a lot of enterprise software, by reducing licenses and consolidating applications.

Speaker Change: pioneering biology

Jason: Six of them.

Jason: and large-scale production

Jason: Their go-to-market timeline.

Jason Kelly: We're focusing on realizing efficiency with our vendors, strategic sourcing and renegotiations. Additionally, we're reducing our dependence on third-party technical work and consulting. As well as external legal services. We're reducing, as I mentioned previously, our real estate footprints actively and looking for subtly opportunities there as well. Equipment costs alignment, we're adjusting our equipment expenses and related service contracts to match the current utilization, and then we'll scale into demand as it comes in.

Jason: Next

Jason: We call them.

Jason: And lastly, I'd like to, Affirming guidance, executing for our customers, the act on these cost-cutting measures and thank those who really handled it to deliver so in the same order where we have. Organizational change, it's easier for me, Paul Feet, a strong culture. Our focus on delivering. That's an update on where we are right now, takeouts to come from, and the tools that are going to grow Ginkgo's revenue going forward. So, like these two images, if you look at how the work of engineering cells is done today, it looks like this picture on the left, all right? The lab bench.

Research work at the lab bench.

Jason: and as a service.

Speaker Change: We have a very different model that ginkgo that relies on automation. So you can see part of our Boston installation of our proprietary rack robotics hardware and the photo on the right.

Speaker Change: ArgeCoup check-up.

Speaker Change: Execute on those in the near...

Speaker Change: And lastly, I'd like to...

Jason: Affirming guidance.

Jason: Executing for our customers.

Speaker Change: It's an automated approach that allows for much more data per research dollar.

Jason Kelly: Equipment costs alignment: we're adjusting our equipment expenses and related service contracts to match the current utilization, and then we'll scale into demand as it comes in. We're undertaking a significant effort to rationalize our software portfolio, a lot of enterprise software, by reducing licenses and consolidating applications. Overall, on the technical side, both in the lab and with software, we have a lot of historical data now on what infrastructure really pays off across these hundreds of programs we've done at Ginkgo. So we've been able to make good decisions, decisive decisions quickly in this area, and so I'm excited to see that play out and save us money.

Jason: the act on these cost-cutting

Jason: and thank

Speaker Change: And it gets better as you do more of it with scale, but it comes at a cost of less flexibility than you get when you work by hand.

Jason: who handled really.

Jason: to deliver soap.

Jason: in the same quarter where we have.

Jason Kelly: We're undertaking a significant effort to rationalize our software portfolio, a lot of enterprise software by reducing licenses and consolidating applications. Overall, on the technical side, both in the lab and with software, we have a lot of historical data now on what infrastructure really pays off across these hundreds of programs we've done at Ginkgo. So we've been able to make good decisions, decisive decisions quickly in this area, and so I'm excited to see that play out and save us money.

Speaker Change: And we've been using this approach of kimco now for hundreds of I'll say, it's like high end R&D projects people tend to send us some of the hardest R&D challenges. They have that's why they're outsourcing it from our customers and we've learned what works and what doesn't work. When you apply this large data approach to genetic engineering and I'm not going to say it's useful for every single.

Speaker Change: Organizational change.

Speaker Change: Greedier I

Paul Feet: Paul Feet, A.

Jason Kelly: Overall, on the technical side, both in the lab and with software, we have a lot of historical data now on what infrastructure really pays off across, you know, these hundreds of programs we've done at Ginkgo. So we've been able to make good decisions, decisive decisions, quickly, in this area, and so I'm excited to see that, that play out and save us, save us money. Okay, importantly, alongside our cost-cutting initiatives, we're continuing to deliver for our customers. This is key. So recently, we delivered on a major technical milestone, for a previously announced large biopharma customer we have.

Jason: Strong Culture Ethics.

Jason: Our focus on delivering

Jason: That's an update on where we're going.

Jason: takeout to come from.

Jason: And first, I want to say that it's a little frustrating because this is exactly what my lab bench looked like in graduate school at MIT 20 years ago. And I promise you, if you walked into the computer science department at MIT today, the tools available to researchers would be wildly different from 20 years ago. But in biotech, the tools have changed a lot less than you would expect. And honestly, I thought about this, and I think it's because this set of tools is actually pretty great for what it's intended to do.

Jason: Tools and

Jason: that are going to grow Ginkgo's revenue going forward.

Speaker Change: Problem in biotechnology, I don't think that Youre going to go away I think situs will still be using those in the thermo catalog, but there is a large set of problems, we see could be better solved with with automation and large data generation in.

Jason: So,

Jason: I like these two images. If you look how the work of engineering cells is done today, it looks like this picture on the left. All right, slab bench.

Jason Kelly: Okay, importantly, alongside our cost-cutting initiatives, we're continuing to deliver for our customers. This is key.

Jason Kelly: Okay, importantly, alongside our cost-cutting initiatives, we're continuing to deliver for our customers. This is key. So recently, we delivered on a major technical milestone for a previously announced large biopharma customer we have. In the midst of all these restructuring efforts, Mark mentioned, we were able to sign four new agriculture deals, the largest of which was with Syngenta, where we're optimizing a microbial strain from their biologics pipeline. This is a molecule that they've earmarked as a pioneering biological solution at Syngenta.

Speaker Change: and first I want to say that it's a little frustrating because this is exactly what my lab bench looked like in graduate school at MIT 20 years ago and I promise you if you walk into the computer science department at MIT the tools available to researchers would be wildly different from 20 years ago but in biotech the tools have changed a lot less than you would expect.

Jason Kelly: So recently, we delivered on a major technical milestone for a previously announced large biopharma customer we have. In the midst of all these restructuring efforts, Mark mentioned, we were able to sign four new agriculture deals, the largest of which was with Syngenta, where we're optimizing a microbial strain from their biologics pipeline. This is a molecule that they've earmarked as a pioneering biological solution at Syngenta. Successful cost-effective and large scale production of this metabolite would expedient their go-to-market timeline for these biological solutions. Next, as Mark mentioned, we signed our first two. We call them LDAS lab data as a service deals with a large cap tech company, and we're excited to execute on those in the near term.

In particular, you've seen a surge of interest recently.

Speaker Change: AI biotech companies that really want to generate large data assets for model training.

Jason Kelly: In the midst of all these restructuring efforts, Mark mentioned, we were able to sign 4 new agriculture deals, the largest of which was with Syngenta, where we're optimizing a microbial strain from their biologics pipeline. This is a molecule that they've earmarked as a pioneering biological solution at Syngenta. Successful, cost-effective, and large-scale production of this metabolite would expedite their go-to-market timeline for these biological solutions. Next, as Mark mentioned, we signed our first two, we call them LDaaS, Lab Data as a Service, deals with a large cap tech company. We're excited to execute on those in the near term. Lastly, I'd like to reiterate, we're reaffirming guidance and are confident in our abilities to continue executing for our customers while we act on these cost-cutting initiatives.

Speaker Change: A big question for Ginkgo is.

Speaker Change: If we're right about that platform and lets say we are it is applicable to a big set of problems, what's the best way to sell it to customers, who do need that large scale data generation and I'll walk through two ways. So the way we've been selling it to date is the approach on the left alright, So were really primarily selling to the decision maker at our customer is the head of R&D or if it's a <unk>.

Speaker Change: And honestly, I thought about this, and I think it's because...

Jason: You know, it allows bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of days, right? They can go to that thermal catalog and order whatever reagent they just read about in a paper, pick up a pipette, and get to work. And for many problems, this set of tools and a by-hand approach to doing lab work is the best solution, right? The big downside to this approach, though, is that since it's manual, you're doing it by hand, there are no advantages to scale.

Jason Kelly: Successful cost-effective and large scale production of this metabolite would expedient their go-to-market timeline for these biological solutions. Next, as Mark mentioned, we signed our first two. We call them LDAS lab data as a service deals with a large cap tech company, and we're excited to execute on those in the near term. And lastly, I'd like to reiterate, we're reaffirming guidance and are confident in our abilities to continue executing for our customers while we act on these cost-cutting initiatives.

Speaker Change: This set of tools is actually pretty great for what it's intended to do.

Jason: It allows bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of days. They can go in that thermocatalog and order whatever reagent they just read about in a paper, pick up a pipette, and get to work. And for many problems, this set of tools...

Speaker Change: Smaller company as the CEO and they're deciding to outsource the whole research program. So he can go we want you to go off and deliver our fastest scientific result, and a small team of ginkgo scientists in the middle there are going to use our platform and automation, but ultimately meet with that customer quarterly at a joint steering Committee meeting and return scientific.

Jason Kelly: And lastly, I'd like to reiterate, we're reaffirming guidance and are confident in our abilities to continue executing for our customers while we act on these cost-cutting initiatives. I want to take a minute and thank the team at Ginkgo, who handled really just a crazy left to deliver so well on customer programs in the same order where we had such a large amount of organizational change. That's going to get easier going into the future, but that was no small feat, and it's a testament to the strong culture at the company and our focus on delivering for customers.

Jason: and a by-hand approach to doing lab work is the best solution, right? The big downside to this approach, though, is that since it's manual, you're doing it by hand, there are no advantages to scale.

Jason: In other words, it doesn't get cheaper or higher quality as you do more of this genetic engineering research work at the lab. We have a very different model at Ginkgo that relies on automation. So you can see part of our Boston installation of our proprietary rack robotics hardware in the photo on the right. This is an automated approach that allows for much more data per research dollar. And it gets better as you do more of it with scale, but it comes at the cost of less flexibility than you get when you work by hand.

Jason Kelly: I want to take a minute and thank the team at Ginkgo, who handled really just a crazy lift to deliver so well on customer programs, in the same quarter where we had such a large amount of organizational change. That's going to get easier going into the future, and but that was no small feat, and it's a testament to the strong culture at the company, and our focus on delivering for customers. Okay, that's an update on where we expect our cost takeouts to come from. And next, I want to talk about how we're building the tools and solutions that are going to grow Ginkgo's revenue going forward. So, like these two images, if you look how the work of engineering cells is done today, it looks like this picture on the left.

Speaker Change: Results to them, but where our scientists are the ones using our platform. So we might return of better manufacturing process to novo nordisk or fertilizer, producing microbes to bear or an improved enzyme for Merck and the other 100 plus.

Jason Kelly: I want to take a minute and thank the team at Ginkgo, who handled really just a crazy left to deliver so well on customer programs in the same order where we had such a large amount of organizational change. That's going to get easier going into the future, but that was no small feat and it's a testament to the strong culture at the company and our focus on delivering for customers. Okay, that's an update on where we expect our cost takeouts to come from.

Jason: In other words, it doesn't get cheaper or higher quality as you do more of this genetic engineering research work at the lab bench.

Speaker Change: We have a very different model I can go that relies on automation, so you can see part of our Boston installation of our proprietary RAC robotics hardware in the photo on the right. This is an automated approach that allows for much more data per research dollar.

Speaker Change: Cell programs, that's the kind of that's how we've been doing that work for our customers.

Speaker Change: We're going to keep doing that business and we see it growing.

Jason Kelly: Okay, that's an update on where we expect our cost takeouts to come from.

Speaker Change: And we're very excited however to open our platform in the way you see on the right by making it directly available to scientists at our customer sites and so I'm Gonna call. These two approaches solutions on the lap the customers coming to us for a kind of solve their problem completely or tools on the rights were providing a set of tools to our customers scientists in there.

Jason Kelly: And next, I want to talk about how we're building the tools and solutions that are going to grow Ginkgo's revenue going forward. So, like these two images, if you look how the work of engineering cells is done today, it looks like this picture on the left, all right, lab bench. And first, I want to say that it's a little frustrating because this is exactly what my lab bench looked like in graduate school at MIT 20 years ago. And I promise you, if you walked into the Computer Science department at MIT, the tools available to researchers would be wildly different from 20 years ago.

Speaker Change: and it gets better as you do more of it with scale, but it comes at the cost of less flexibility than you get when you work by hand.

Jason: And we've been using this approach at Ginkgo now for hundreds of what I'll call high-end R&D projects. People tend to send us some of the hardest R&D challenges they have. That's why they're outsourcing it from our customers, and we've learned what works and what doesn't work when you apply this large data approach to genetic engineering. And I'm not going to say it's useful for every single problem in biotechnology. But I don't think benches are going to go away.

Speaker Change: and we've been using this approach that can go now for hundreds of, well, I'll say it's like high end R&D projects. People tend to send us some of the hardest R&D challenges they have. That's why they're outsourcing it from our customers. And we've learned what works and what doesn't work when you apply this large data approach to genetic engineering. And I'm not going to say it's useful for every single problem in biotechnology. I don't think benches are going to go away. I think scientists will still be using those in the thermocatalogue. But there is a large set of problems we see could be better solved with automation in large data generation.

Jason Kelly: All right? Lab bench. And first, I want to say that, it's a little frustrating, because this is exactly what my lab bench looked like in graduate school at MIT 20 years ago. And I promise you, if you walked into the computer science department at MIT, the tools available to researchers would be wildly different from 20 years ago. But in biotech, the tools have changed, a lot, a lot less than you would expect. And honestly, I thought about this, and I, and I think it's because this set of tools is actually pretty great for what it's intended to do. You know, it allows bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of days, right?

Speaker Change: Going to solve their problems for themselves alright, and so I want to I want to.

Speaker Change: For folks that are new to the life science tool space I wanted to just lay out sort of a spectrum of how I see the industry sort of from solutions to tools. Okay. So on the Y axis. The top of it represents how customized and offering is for what a customer wants like is it is it something we built just specific for the problem you have.

Jason Kelly: And I promise you, if you walked into the computer science department at MIT, the tools available to researchers would be wildly different from 20 years ago. But in biotech, tools have changed a lot less than you would expect. And honestly, I thought about this and I think it's because this set of tools is actually pretty great for what it's intended to do. You know, it allows bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of dates, right?

Jason: I think scientists will still be using those in the thermo catalog. But there is a large set of problems we see that could be better solved with automation and large data generation. In particular, you've seen a surge of interest recently from AI biotech companies that really want to generate large data assets for model training. A big question for Ginkgo is, if we're right about that platform, and let's say we are, it is applicable to a big set of problems, what's the best way to sell it, okay, to customers who do need that large-scale data generation? And I'll walk through them in two ways.

Jason Kelly: But in biotech, tools have changed a lot less than you would expect. And honestly, I thought about this, and I think it's because this set of tools is actually pretty great for what it's intended to do. You know, it allows bench researchers to explore hypotheses quickly and adopt new protocols that they read in papers in a matter of dates, right? They can go in that thermal catalog in order or whatever reagents they just read about in a paper, pick up a pipette and get to work. And for many problems, this set of tools and a bi-hand approach to doing lab work is the best solution, right?

Jason Kelly: They can go in that thermal catalog in order or whatever reagents they just read about in a paper, pick up a pipette and get to work. And for many problems, this set of tools and a bi-hand approach to doing lab work is the best solution, right? The big downside to this approach, though, is that since it's manual, you're doing it by hand, there are no advantages to scale. In other words, it doesn't get cheaper or higher quality as you do more of this to that engineering research work at the lab.

Speaker Change: And it also represents how much technical risk ginkgo is bearing with the offering in other words are we taking all the risk or are we sharing some of it with the customer.

Speaker Change: In particular, you've seen a surge of interest recently from AI biotech companies that really want to generate large data assets for model training.

Speaker Change: And as these two things go up you get the most extreme form of a custom high technical risks <unk> solution in the market up at the top left which is where a small biotech company developed a drug asset with no intention of ultimately becoming a standalone drug company, but really intending to ultimately sell license that drug asset to a major biotech or biopharma.

Speaker Change: A big question for Ginkgo is...

Jason Kelly: They can go in that Thermo catalog and order whatever reagent they just read about in a paper, pick up a pipette, and get to work. For many problems, this set of tools and a by-hand approach to doing lab work is the best solution, right? The big downside to this approach, though, is that, since it's manual, you're doing it by hand, there are no advantages to scale. In other words, it doesn't get cheaper or higher quality as you do more of this genetic engineering research work at the lab bench. We have a very different model at Ginkgo that relies on automation. You can see part of our Boston installation of our proprietary rack robotics hardware in the photo on the right.

Speaker Change: If we're right about that platform, let's say we are, it is applicable to a big set of problems, what's the best way to sell it? Okay, to customers who do need that large scale data generation, and I'll offer two ways. So the way we've been selling it today is the approach on the left.

Jason: So the way we've been selling it to date is the approach on the left, all right? So we're really primarily selling to the decision-maker at our customer, the head of R&D, or if it's a smaller company, it's the CEO, and they're deciding to outsource a whole research program. So, hey, Ginkgo, we want you to go off and deliver us back this scientific result.

Jason Kelly: The big downside to this approach, though, is that since it's manual, you're doing it by hand; there are no advantages to scale. In other words, it doesn't get cheaper or higher quality as you do more of this to that engineering research work at the lab. We have a very different model at Ginkgo that relies on automation. So you can see part of our Boston installation of our proprietary rack robotics hardware and the photo on the right. This is an automated approach that allows for much more data per research dollar. Any any get better, as you do more of it with scale, but it comes with the cost of less flexibility than you get when you work by hand.

Speaker Change: Alright, so we're really primarily selling to the decision maker at our customer is the head of R&D or if it's a smaller company It's the CEO and they're deciding to outsource a whole research program. So hey Ginkgo We want you to go off and deliver us back this scientific result

Speaker Change: That's the most extreme form of customization and high technical risk and and you see many platform biotech companies in the industry, taking this approach companies like AB sigh of Cellarer recursion. They all have internal drug pipelines and they will profit handsomely if they get a good result in a clinical trial and it was a very functional it's a good business model.

Jason: And a small team of Ginkgo scientists in the middle there are going to use our platform in automation but ultimately meet with that customer quarterly at a joint steering committee meeting and return scientific results to them, but we're, our scientists are the ones using our platform. So we might return a better manufacturing process to Nova Nordisk, or fertilizer-producing microbes to Bayer, or an improved enzyme to Merck, and, you know, the other 100-plus cell programs. That's the kind of, that's how we've been doing that work for our customers. We're going to keep doing that business. And we see it growing.

Jason Kelly: We have a very different model at Ginkgo that relies on automation. So you can see part of our Boston installation of our proprietary rack robotics hardware and the photo on the right. This is an automated approach that allows for much more data per research dollar. Any any get better, as you do more of it with scale, but it comes with the cost of less flexibility than you get when you work by hand.

Speaker Change: And a small team of Ginkgo scientists in the middle there are going to use our platform in automation, but ultimately meet with that customer quarterly at a joint steering committee meeting and return scientific results to them. But we're, our scientists are the ones using our platform.

Speaker Change: <unk>.

Jason Kelly: This is an automated approach that allows for much more data per research dollar, and it gets better as you do more of it with scale, but it comes at the cost of less flexibility than you get when you work by hand. And we've been using this approach at Ginkgo now for hundreds of, well, I'll say it's like high-end R&D projects. People tend to send us some of the hardest R&D challenges they have. That's why they're outsourcing it from our customers. And we've learned what works and what doesn't work when you apply this large data approach to genetic engineering. And I'm not going to say it's useful for every single problem in biotechnology. I don't think benches are going to go away. I think scientists will still be using those in the Thermo catalog.

Speaker Change: We have not taken this approach of kimco.

Speaker Change: But for a variety of reasons. We believe we can bring more of a direct platform services business model into the industry and so we went down that Y axis and you can find ourselves engineering solutions offering there that service business, where ginkgo is definitely bearing less technical risks that a small biotech that's doing their own drug for example, our customers pay us fees, that's where you are.

Speaker Change: So, we might return a better manufacturing process to Nova Nordisk, or fertilizer-producing microbes to Bayer, or an improved enzyme for Merck, and, you know, the other 100-plus cell programs. That's the kind of – that's how we've been doing that work for our customers.

Jason Kelly: And we've been using this approach at Ginkgo now for hundreds of what I'll say is like high-end R&D products. People tend to send us some of the hardest R&D challenges they have. That's why they're outsourcing it from our customers. And we've learned what works and what doesn't work when you apply this large data approach to genetic engineering. And I'm not going to say it's useful for every single problem in biotechnology. I don't think benches are going to go away. I think scientists will still be using those in the thermocatalog. But there is a large set of problems we see could be better solved with automation and large data generation.

Jason: And we're very excited, however, to open our platform in the way you see on the right by making it directly available to scientists at our customer sites. And so I'm going to call these two approaches, solutions on the left, customers coming to us for us to kind of solve their problem completely, or tools on the right. We're providing a set of tools to our customer scientists, and they're going to solve their problems for themselves. All right.

Speaker Change: Our revenue and cell engineering is largely fees today that supports the technical work. So they are paying us to do a lot of that that research service for them.

Speaker Change: Thanks for watching, and don't forget to like, share, and subscribe to our channel.

Speaker Change: We're going to keep doing that business, and we see it growing. And we're very excited, however, to open our platform in the way you see on the right, by making it directly available to scientists at our customer sites.

Speaker Change: But we're making a very customized solution for them, Okay and the key point here is the more customize the solution is in other words on the left hand side of this chart. The more likely ginkgo is to be able to negotiate downstream value share in other words to get royalties are milestones in most of our cell engineering solution deals today have royalties or miles.

Jason Kelly: I think scientists will still be using those in the thermocatalog. But there is a large set of problems we see could be better solved with automation and large data generation. In particular, you see a surge of engineers that interest recently from AI biotech companies that really want to generate large data assets for model training. A big question for Ginkgo is, if we're right about that platform, let's say we are, it is applicable to a big set of problems.

Speaker Change: And so I'm going to call these two approaches solutions on the left, the customers coming to us for us to kind of solve their problem completely, or tools on the right, we're providing a set of tools to our customer scientists, and they're going to solve their problems for themselves. All right. And so I want to I want to

Jason Kelly: But there is a large set of problems we see could be better solved with automation and large data generation. In particular, you've seen a surge of interest recently from AI biotech companies that really want to generate large data assets for model training. A big question for Ginkgo is, if we're right about that platform, and let's say we are, it is applicable to a big set of problems. What's the best way to sell it, okay, to customers who do need that large-scale data generation? And I'll walk through two ways. So the way we've been selling it to date is the approach on the left. All right? So we're really primarily selling to the decision maker at our customer: the head of R&D, or, if it's a smaller company, the CEO.

Jason: And so I want to, you know, for folks that are new to the life science tool space, I want to just lay out sort of a spectrum of how I see the industry sort of from solutions to tools. Okay, so on the y axis, the top of it represents how customized an offering is for what a customer wants. Like, is it, is it something we built just specifically for the problem you have? And it also represents how much technical risk Ginkgo is bearing with the offering. In other words, are we taking all the risk, or are we sharing some of it with the customer?

Jason Kelly: In particular, you see a surge of engineers that interest recently from AI biotech companies that really want to generate large data assets for model training.

Speaker Change: You know for folks that are new to the life science tool space I want to just lay out sort of a spectrum of how I see the industry sort of from solutions to tools

Mark: Stones, and if you see us keep signing them up like Mark mentioned, signing a signing some of those large programs. They will continue to have our royalties and milestones in them in the future.

Jason Kelly: A big question for Ginkgo is, if we're right about that platform, let's say we are, it is applicable to a big set of problems. What's the best way to sell it? To customers who do need that large scale data generation? And I'll walk through two ways. So the way we've been selling it to date is the approach on the left. So we're really primarily selling to the decision maker of our customer, the head of R&D. Or, if it's a smaller company, it's the CEO. And they're deciding to outsource a whole research program. So hey, Ginkgo, we want you to go off and deliver us back to scientific results.

Jason Kelly: What's the best way to sell it? To customers who do need that large scale data generation? And I'll walk through two ways. So the way we've been selling it to date is the approach on the left. So we're really primarily selling to the decision maker of our customer is the head of R&D. Or if it's a smaller company, it's the CEO. And they're deciding to outsource a whole research program. So hey, Ginkgo, we want you to go off and deliver us back to scientific results.

Speaker Change: Okay, so on the y-axis, the top of it, represents...

Speaker Change: How customized an offering is for what a customer wants, like is it is it something we built just specific for the problem you have?

Speaker Change: The dotted line in the in the middle shows that at some point, you're offering something more off the shelf in other words less customized and so then the customers aren't going to share royalties with you right.

Speaker Change: And it also represents how much technical risk Ginkgo is bearing with the offering. In other words, are we taking all the risk or are we sharing some of it with the customer?

Jason: And as these two things go up, you get the most extreme form of a custom, high technical risk, B2B solution in the market up at the top left, which is where a small biotech company develops a drug asset with no intention of ultimately becoming a standalone drug company but really intending to ultimately sell or license that drug asset to a major biotech or biopharma. That's the most extreme form of customization and a high technical risk.

Speaker Change: This is roughly where I draw the line between what I'll call solutions and tools. Okay. So as you move to the right side of the screen, you'll see things like our lab data as a service, where we're producing data at scale for customers, but we arent bearing a ton of technical risk in other words.

Speaker Change: And as these two things go up, you get the most extreme form of a custom, high-technical risk B2B solution in the market up at the top left, which is where a small biotech company develops a drug asset with no intention of ultimately becoming a standalone drug company, but really intending to ultimately sell, license that drug asset to a major biotech or biopharma. That's the most extreme form of customization and high-technical risk, and you see many platform biotech companies in the industry taking this approach. Companies like Abcai, Abcelera, Recursion, they all have internal drug pipelines and they will profit handsomely if they get a good result in a clinical trial. And this is a very functional, it's a good business model, it works.

Jason Kelly: And they're deciding to outsource a whole research program. So hey, Ginkgo, we want you to go off and deliver us back this scientific result. And a small team of Ginkgo scientists in the middle there are going to use our platform and automation, but ultimately meet with that customer quarterly at a joint steering committee meeting and return scientific results to them. But our scientists are the ones using our platform. So we might return a better manufacturing process to Novo Nordisk, or fertilizer-producing microbes to Bayer, or an improved enzyme for Merck, and, you know, the other 100-plus cell programs. That's the kind of... That's how we've been doing that work for our customers. We're going to keep doing that business, and we see it growing.

Jason Kelly: And a small team of Ginkgo scientists in the middle there are going to use our platform and automation. But ultimately, meet with that customer quarterly at a joint steering committee meeting and return scientific results to them. But we're our scientists are the one using our platform. So we might return a better manufacturing process to Nova Nordisk or fertilizer producing microbes. To bear or an improved enzyme for Merck and the other 100 plus cell programs.

Jason Kelly: And a small team of Ginkgo scientists in the middle there are going to use our platform and automation. But ultimately, meet with that customer quarterly at a joint steering committee meeting and return scientific results to them. But we're our scientists are the one using our platform. So we might return a better manufacturing process to Nova Nordisk or fertilizer-producing microbes. To bear or an improved enzyme for Merck and the other 100 plus cell programs. That's the kind of that's how we've been doing that work for our customers. We're going to keep doing that business. And we see it growing.

Speaker Change: The customers coming to us with a design and were generating data if the design is bad that's their fall okay.

Speaker Change: And so when we do those deals we don't expect to see downstream value share.

Jason: And you see many platform biotech companies in the industry taking this approach. Companies like Abcye, Abcelera, Recursion, they all have internal drug pipelines, and they will profit handsomely if they get a good result in a clinical trial. And it's a very viable business model. It works. But we have not taken this approach at Ginkgo for a variety of reasons.

Speaker Change: And towards the end of this tail, you'll see that we have AI and automation listed on this chart and a ginkgo. These two tool pieces are in their early stages, but the idea behind these is that ginkgo can develop modular tools robotics software tools that scientists and developers at our customer could put together to make their own.

Jason Kelly: That's the kind of that's how we've been doing that work for our customers. We're going to keep doing that business. And we see it growing. And we're very excited, however, to open our platform in the way you see on the right by making it directly available to scientists at our customer sites. And so I'm going to call these two approaches solutions on the left because we're coming to us for a kind of solve their problem completely or tools on the right. We're providing a set of tools to our customer scientists and they're going to solve their problems for themselves.

Jason: We believe we can bring more of a direct platform services business model to the industry. And so we went down that y-axis, and you can find our cell engineering solutions offering there, that service business, where Ginkgo is definitely bearing less technical risk than a small biotech that's doing its own drug. For example, our customers pay us fees.

Speaker Change: We have not taken this approach at Ginkgo. For a variety of reasons. We believe we can bring more of a direct platform services business model into the industry. And so we went down that y-axis.

Jason Kelly: And we're very excited, however, to open our platform in the way you see on the right by making it directly available to scientists at our customer sites. And so I'm going to call these two approaches solutions on the left because we're coming to us for a kind of solve their problem completely or tools on the right. We're providing a set of tools to our customer scientists, and they're going to solve their problems for themselves.

Speaker Change: Infrastructure in house to Us and so we'll talk more about that in the future. Okay. So what I wanted to dig in today first on this chart.

Jason Kelly: And we're very excited, however, to open our platform in the way you see on the right, by making it directly available to scientists at our customer sites. And so I'm going to call these two approaches: solutions on the left, the customer is coming to us for us to kind of solve their problem completely, or tools on the right. We're providing a set of tools to our customer scientists, and they're going to solve their problems for themselves. All right? And so I want to... You know, for folks that are new to the life science tool space, I want to just lay out sort of a spectrum of how I see the industry sort of from solutions to tools. Okay, so on the y-axis, the top of it represents how customized an offering is for what a customer wants.

Speaker Change: Is that your selling generic solutions business, we love. This business. Okay. We think we are very differentiated AD ginkgo in this area both in technology, having a wide enough array to build a custom solution for a customer effectively and even in our sales our sales team and our approach.

Speaker Change: And you can find our cell engineering solutions offering there, that service business, where Ginkgo is definitely bearing less technical risk than a small biotech that's doing their own drug. You know, for example, our customers pay us fees. That's where you see, you know, our revenue in cell engineering is largely fees today. That supports the technical work. So they're paying us to do a lot of that research service for them. But we're making a very customized solution for them.

Jason: That's where you see our revenue in cell engineering is largely fees today. That supports the technical work. So they're paying us to do a lot of that research service for them, and we're creating a very customized solution for them. OK, and the key point here is the more customized the solution is, in other words, on the left hand side of this chart, the more likely Ginkgo is to be able to negotiate downstream value share. In other words, to get. Have royalties or miles. And if you see this up, Like Mark mentioned, I'm signing out.

Jason Kelly: All right. And so I want to, I want to, you know, for folks that are new to the life science tool space, I want to just lay out sort of a spectrum of how I see the industry sort of from solutions to tools. Okay. So on the y-axis, the top of it represents how customized an offering is for what a customer wants. Is it something we built just specific for the problem you have? And it also represents how much technical risk Ginkgo is bearing with the offering. In other words, are we taking all the risk, or are we sharing some of it with the customer.

Speaker Change: These are really complex deals to sell that really complex deals to negotiate and we do a lot of them every quarter I think more than anyone else and so the change we made with the restructuring though is that we will no longer be taking kind of any cell engineering work a customer comes and ask for we're going to be limiting that work to a more narrow set of offerings in each market.

Speaker Change: Okay, and the key point here is the more customized the solution is, in other words, on the left hand side of this chart, the more likely Ginkgo is to be able to negotiate downstream value share, in other words, to get.

Jason Kelly: Like, is it, is it something we built just specific for the problem you have? And it also represents how much technical risk Ginkgo is bearing with the offering. In other words, are we taking all the risk or are we sharing some of it with the customer? And as these two things go up, you get the most extreme form of a custom, high technical risk, B2B solution in the market up at the top left, which is where a small biotech company develops a drug asset with no intention of ultimately becoming a standalone drug company, but really intending to ultimately sell, license that drug asset to a major biotech or biopharma. That's the most extreme form of customization, and high technical risk, and you see many platform biotech companies in the industry taking this approach. Companies like Absci, AbCellera, and Recursion.

Jason Kelly: And it also represents how much technical risk Ginkgo is bearing with the offering. In other words, are we taking all the risk or are we sharing some of it with the customer. And as these two things go up, you get the most extreme form of a custom high technical risk B2B solution in the market up at the top left, which is where a small biotech company develops a drug asset with no intention of ultimately becoming a standalone drug company, but really intending to ultimately sell license that drug asset to a major biotech or bioforma.

Speaker Change: That ginkgo can deliver efficiently.

Speaker Change: And so let's dig in and look at AG and then the Biopharma industrial so in agriculture. The first product will be offering a strain optimization for existing products. So agrivisor a customer of ours. They are currently leveraging our strain optimization service to improve the efficacy of one of their existing biocontrol products. So things they already have out there just improve.

Jason Kelly: And as these two things go up, you get the most extreme form of a custom high technical risk B2B solution in the market up at the top left, which is where a small biotech company develops a drug asset with no intention of ultimately becoming a standalone drug company, but really intending to ultimately sell license that drug asset to a major biotech or bioforma. That's the most extreme form of customization and high technical risk. And, and you see many platform biotech companies in the industry taking this approach, companies like Absai, etc. Recursion. They all have internal drug pipelines, and they will profit handsomely if they get a good result in a clinical trial.

Speaker Change: Have royalties or miles.

Jason: They will continue. Okay, these and miles show that it's some, offering something more off. And so then the customer... I'll tease with you, right?

Speaker Change: And if you see...

Speaker Change: like Mark mentioned signing up.

Speaker Change: They will continue.

Speaker Change: and Miles.

Mark: Oh show that it's something

Speaker Change: offering something more

Speaker Change: Them give them back.

Jason: This is roughly where I draw. Okay. Right side of the screen.

Speaker Change: Another product we developed is based on some of the work we've done with bear where we've taken early development lead something thats still in the lab and take it to field trials. The assets, we acquired from <unk> earlier this year fit well into this and so we're excited to continue to expand in that area.

Speaker Change: And so then the customer...

Jason Kelly: That's the most extreme form of customization and high technical risk. And, and you see many platform biotech companies in the industry taking this approach companies like absai, etc. Recursion. They all have internal drug pipelines and they will profit handsomely if they get a good result in a clinical trial. And there's a very functional. It's a good business model. It works. We have not taken this approach at Ginkgo for a variety of reasons.

Speaker Change: I'll take you with you, right?

Speaker Change: is roughly where I draw.

Jason: Our lab data as a, at scale for We are bearing, You know the customer, Fine, and we're generating, Bad, that's their fault. When we do those deals, and C Downstream Values, that came. AI and automation listed on this chart, early stages, but the, Is that Ginkgo condominium? put together to make Infrastructure. So we'll talk more about that. I wanted to dig in today about art and business.

Speaker Change: Bubbles. Okay.

Speaker Change: Right side of the screen.

Speaker Change: our lab data as a

Jason Kelly: They all have internal drug pipelines, and they will profit handsomely if they get a good result in a clinical trial. And it's a very functional, it's a good business model, it works. We have not taken this approach at Ginkgo, for a variety of reasons. We believe we can bring more of a direct platform services business model into the industry, and so we went down that Y-axis. And you can find our cell engineering solutions offering there, that service business, where Ginkgo is definitely bearing less technical risk than a small biotech that's doing their own drug. You know, for example, our customers pay us fees. That's where you see, you know, our revenue in cell engineering is largely fees today. That supports the technical work.

Speaker Change: at scale for

Speaker Change: Third we have bio production. Okay. So this is we believe a major growth opportunity where customers are looking to either develop or improve the production of our bioactive by fermentations youre, putting sells in a tank and producing often a small molecule. This is very similar to the work we do in industrial biotechnology. So we get a lot of efficiency on the technical side.

Speaker Change: We are bearing

Speaker Change: You know, the customer

Jason Kelly: And there's a very functional. It's a good business model. It works. We have not taken this approach at Ginkgo for a variety of reasons. We believe we can bring more of a direct platform services business model into the industry. And so we went down that Y axis. And you can find our self-engineering solutions offering there that service business where Ginkgo is definitely bearing less technical risk than a small biotech that's doing their own drug. You know, for example, our customers pay us fees. That's where you see, you know, our revenue and sell engineering is largely fees today that supports the technical work.

Speaker Change: And we're generating.

Speaker Change: If it's bad, that's their fault.

Speaker Change: When we do those deals,

Jason Kelly: We believe we can bring more of a direct platform services business model into the industry. And so we went down that y axis. And you can find our self engineering solutions offering there that service business where Ginkgo is definitely bearing less technical risk than a small biotech that's doing their own drug. You know, for example, our customers pay us fees. That's where you see, you know, our revenue and sell engineering is largely fees today that supports the technical work.

Speaker Change: to see downstream values.

Taylor: This is Taylor.

Speaker Change: AI and automation listed on this chart.

Speaker Change: The same backend infrastructure, we use here will be reusing in.

Speaker Change: Early stages, but the end of the year.

Speaker Change: The next section when I talk about our industrial work.

Speaker Change: Finally, our last offering is supporting discovery of plant rates. This is typically a customer looking for novel modes of action or protein optimization. It's a large area of research spending in AG and so I think an important one for us in the future.

Anna: and Anna.

Speaker Change: Put together to make...

Speaker Change: infrastructure.

Jason Kelly: So they're paying us to do a lot of that research service for them, and but we're making a very customized solution for them. Okay, and the key point here is the more customized the solution is, in other words, on the left-hand side of this chart, the more likely Ginkgo is to be able to negotiate downstream value share. In other words, to get royalties or milestones, and most of our cell engineering solution deals today have royalties or milestones. And if you see us keep signing them up, like Mark mentioned, signing up, assigning some of those large programs, they will continue to have royalties and milestones in them in the future.

Jason Kelly: So they're paying us to do a lot of that research service for them. And, but we're making a very customized solution. for them. Okay, and the key point here is the more customized the solution is, in other words, on the left-hand side of this chart, the more likely Ginkgo is to be able to negotiate downstream value share. In other words, to get royalties or milestones, and most of our silent engineering solution deals today have royalties or milestones. And if you see us keep signing them up, like Mark mentioned, signing up, assigning some of those large programs, they will continue to have royalties and milestones in them in the future.

Jason Kelly: So they're paying us to do a lot of that research service for them. And, but we're making a very customized solution, for them. Okay, and the key point here is the more customized the solution is, in other words, on the left-hand side of this chart, the more likely Ginkgo is to be able to negotiate downstream value share. In other words, to get royalties or milestones, and most of our silent engineering solution deals today have royalties or milestones.

Speaker Change: So we'll talk more about that.

Jason: We love, at Ginkgo, in this area, a wide enough, A Custom Solution. Customer Effectively, and our sales team. You know, these are really com..., feel free to negotiate.

Speaker Change: I wanted to dig in today.

Jason Kelly: And if you see us keep signing them up, like Mark mentioned, signing up, assigning some of those large programs, they will continue to have royalties and milestones in them in the future. The dotted line in the middle show that at some point you're offering something more off the shelf, in other words, less customized. And so then the customers aren't going to share royalties with you, right? This is roughly where I draw the line between what I'll call solutions and tools.

Speaker Change: Okay. So now I'll talk about pharma industrial solutions.

Speaker Change: We love you.

Speaker Change: Businesses are focused on helping customers discover optimized the manufacturer biologically derived products in three key areas here. Our first offering is protein engineering services. So our job there is to build better proteins and enzymes for both pharma and industrial process enzymes as well as therapeutic and diagnostic biosensors and you can see on the bottom.

Speaker Change: at Ginkgo in this area.

Speaker Change: a wide enough

Speaker Change: A Custom Solution.

Speaker Change: Customer Effectively.

Speaker Change: Our sales team and

Speaker Change: You know, these are really com

Jason: So. Unknown Speaker So is that I'll be taking, hiring work as a customer, That way, set of offerings in and look at ag. Industrial. The first product we'll be offering. Transcription by ESO, translation by — You know, Agravala is a... Leveraging our strain optimization. Just FF Advocacy, FF Advocacy, Unknown Existing bioconsumer. Mah is based on some of my work.

Speaker Change: Fielton Negotiate

Speaker Change: Customer projects, we have in these areas. These are all areas. We already currently do working next we have protein production, which is focused on building and optimizing production strains, including creating better ingredients for foods.

Speaker Change: So.

Speaker Change: So, is that

Jason Kelly: The dotted line in the middle shows that at some point, you're offering something more off the shelf, in other words, less customized, and so then the customers aren't going to share royalties with you, right? This is roughly where I draw the line between what I'll call solutions and tools. Okay? So as you move to the right side of the screen, you'll see things like our Lab Data as a Service, where we're producing data at scale for customers, but we aren't bearing a ton of technical risk. In other words, you know, the customer's coming to us with a design, and we're generating data. If the design is bad, that's their fault, okay? And so when we do those deals, we don't expect to see Downstream value share.

Jason Kelly: The dotted line in the middle shows that at some point you're offering something more off the shelf; in other words, less customized. And so then the customers aren't going to share royalties with you, right? This is roughly where I draw the line between what I'll call solutions and tools. Okay, so as you move to the right side of the screen, you'll see things like our lab data as a service, where we're producing data at scale for customers, but we aren't bearing a ton of technical risk. In other words, you know, the customers coming to us with a design, and we're generating data if the design is bad, that's their fault.

Speaker Change: I'll be taking.

Speaker Change: Bringing work a customer

Speaker Change: Like if milk protein and so on we're finding better ways to manufacture vaccines.

Speaker Change: I'm that one

Speaker Change: The set of offerings in...

Speaker Change: Lastly, we have a strong offering in small molecule bio production, that's what I was mentioning when that when I'm talking about the AG, where we're looking to build and optimize small molecule production strains, including pharma API chemicals food flavor ingredients and so on we're creating new strains to create products with it.

Speaker Change: This is it, life. Bye.

Speaker Change: and look at ag.

Speaker Change: Industrial

Jason Kelly: Okay, so as you move to the right side of the screen, you'll see things like our lab data as a service where we're producing data at scale for customers, but we aren't bearing a ton of technical risk. In other words, you know, the customers coming to us with a design and we're generating data if the design is bad, that's their fault. Okay, and so when we do those deals, we don't expect to see downstream value share.

Speaker Change: First product we'll be offering.

Speaker Change: Action for Existing Products.

Speaker Change: you know, Agravala.

Speaker Change: Our strain optimization

Speaker Change: Wide range of applications. So in all of these cases, you can see ginkgo customers, where we're currently delivering programs. These like I said this span of what we're willing to sell is actually much more narrow than it would have been before but the areas. We're doing in our strongest areas in the areas. We can deliver most efficiently. So again I think this is how we can move on this path to profit.

Speaker Change: Just FF advocacy.

Speaker Change: Existing Bioconnections

Jason: Early Development [inaudible] lab and take it to the field from AgBiome. This and so we're..., continue to expand that we have a bioproduct. So this is, we believe, a community where customers are moved into production by fermentation in a tank and produced. This is very... New and Industrial by Transcription by CastingWords, a structure we use. I will be reusing it. The Museum of Contemporary French Industry. The last offering is a... This is typically...

Jason Kelly: Okay, and so when we do those deals, we don't expect to see downstream value share. And towards the end of this tail, you'll see that we have AI and automation listed on this chart. And at Ginkgo, these two tool pieces are in their early stages, but the idea behind these is that Ginkgo can develop modular tools, robotics, and software tools that scientists and developers at our customer could put together to make their own infrastructure in-house to use.

Speaker Change: Good to be back!

Speaker Change: is based on some of the work

Jason Kelly: And towards the end of this tail, you'll see that we have AI and automation listed on this chart. And at Ginkgo, these two tool pieces are in their early stages, but the idea behind these is that Ginkgo can develop modular tools, robotics, software tools, that scientists and developers at our customer could put together to make their own infrastructure in-house to use. And so we'll talk more about that in the future. Okay, so what I wanted to dig in today first on this chart is the our cell engineering solutions business. We love this business, okay? We think we are very differentiated at Ginkgo in this area, both in technology, having a wide enough array to build a custom solution for a customer effectively, and even in our sales, our sales team and our approach.

Speaker Change: Early Development League.

Speaker Change: lab and take it to field

Speaker Change: from AgBiome

Speaker Change: this and so we're

Speaker Change: Ability in the cell and sharing solutions is with this more more tight focus.

Speaker Change: Continue to expand.

Speaker Change: We have bioproducts.

Speaker Change: Okay.

Speaker Change: So this is, we believe it.

Speaker Change: I want to move onto our newer offerings, but before that I want to clear up some confusion I heard after our last call. We will keep signing those solution deals and we will often be getting milestones and royalties on those deals. Okay. So we're not getting out of.

Speaker Change: Danny, we're Customers, we're We're Customers, we're

Danny: of the production

Speaker Change: by fermentations

Jason Kelly: And so we'll talk more about that in the future.

Danny: in a tank and produced

Jason Kelly: Okay, so what I wanted to dig in today first on this chart is that you're selling your solutions business. We love this business. Okay, we think we're very differentiated at Ginkgo in this area, both in technology, having a wide enough array to build a custom solution for a customer effectively and even in our sales, our sales team and our approach. You know, these are really complex deals to sell that really complex deals to negotiate. And we do a lot of them every quarter. I think more than anyone else.

Jason Kelly: Okay, so what I wanted to dig in today first on this chart is that you're selling your solutions business. We love this business. Okay, we think we're very differentiated at Ginkgo in this area, both in technology, having a wide enough array to build a custom solution for a customer effectively and even in our sales, our sales team and our approach, you know, these are really complex deals to sell that really complex deals to negotiate.

Danny: This is very

Danny: Do an industrial life.

Speaker Change: Getting any milestones and royalties it just depends on the type of work we're doing for our customer. So now as we move to the tool side of this chart.

Speaker Change: I should see on the technical side.

Speaker Change: The structure we use.

Speaker Change: I will be reusing

Speaker Change: We have our new lab data as a service offering that I announced that ginkgo for mens back in April we believe we have a major opportunity for <unk> with the drug discovery market in particular, AI and ml is increasingly being used in drug discovery and the need for large datasets to train models is growing so people have mined a lot of what's out there in these public data.

Danny: Must Real Work.

Speaker Change: The laughter offering is upon me.

Timothy: This is Timothy.

Speaker Change: www.thevenusproject.com

Jason Kelly: You know, these are really complex deals to sell. They're really complex deals to negotiate, and we do a lot of them every quarter, I think more than anyone else. So, the change we made with the restructuring, though, is that we will no longer be taking kind of any cell engineering work a customer comes and asks for. We're going to be limiting that work to a more narrow set of offerings in each market that Ginkgo can deliver efficiently. So let's dig in and look at ag, and then the biopharma industrial. So in agriculture, the first product we'll be offering is strain optimization for existing products. So, you know, Agrivida is a customer of ours. They're currently leveraging our strain optimization service to improve the efficacy of one of their existing biocontrol products.

Jason: So now I want to talk... Solutions. Discover. Discover. Discover. Doctor, Bioworks, key areas here. Fuffering is Proofing. There is to build better for both pharma. Process Enzymes, and you can see. Customer Projects we have, areas we already currently do. Production, which is focused, and production string.

Jason Kelly: And we do a lot of them every quarter. I think more than anyone else. And so the change we made with the restructuring, though, is that we will no longer be taking kind of any sell engineering work. A customer comes and asks for we're going to be limiting that work to a more narrow set of offerings in each market that Ginkgo can deliver efficiently.

Speaker Change: [inaudible]

Jason Kelly: And so the change we made with the restructuring, though, is that we will no longer be taking kind of any sell engineering work. A customer comes and asks for, we're going to be limiting that work to a more narrow set of offerings in each market that Ginkgo can deliver efficiently.

Speaker Change: Solutions are...

Speaker Change: Things like Alpha fold and so on were trained on the public structured database of public genome database giggles proprietary automation the ability to deploy it allows customers to generate large new datasets that they can use to train proprietary models or to create data in areas that arent structure, which is really what the big <unk>.

Danny: Discover.

Speaker Change: Sure, bye, logic.

Speaker Change: key areas here

Speaker Change: Offering is

Speaker Change: There is to build better

Jason Kelly: And so let's dig in and look at ag and then the bioparma industrial. So in agriculture, the first product will be offering a strain optimization for existing products, so, you know, Agrivalize a customer of ours. They're currently leveraging our strain optimization service to improve the FF efficacy of one of their existing bio control products. So things they already have out there. Just improve them, give them back. Another product we developed is based on some of the work we've done with bear, where we take an early development leads, something that's still in the lab and take it to field trust.

Jason Kelly: And so let's dig in and look at ag and then the bioparma industrial. So in agriculture, the first product will be offering a strain optimization for existing products, so, you know, agrivalize a customer of ours. They're currently leveraging our strain optimization service to improve the FF efficacy of one of their existing bio control products. So things they already have out there. Just improve them, give them back another product we developed is based on some of the work we've done with bear where we take an early development leads, something that's still in the lab and take it to field trust.

Speaker Change: for both pharma.

Speaker Change: process enzymes

Speaker Change: Listing datasets in public or so like things like <unk>.

Speaker Change: and you can see that.

Speaker Change: Customer projects we have.

Speaker Change: Protein activities and so forth in this case, our customers are designing the experiments themselves taking on the majority of the biological risk for example, the design a ton of antibody sequences and send them. The ginkgo, we synthesize express test those sequences for binding develop ability assays and since were mainly providing data and not providing custom solutions again.

Speaker Change: as we already currently do.

Jason: Creating Better Ingredients. Vaccine. Small Molecule Bioproducts.

Duckshin: Duckshin, which is focused.

Duckshin: I think production strength.

Speaker Change: Creating Better Ingredients

Jason Kelly: So things they already have out there, just improve them, give them back. Another product we developed is based on some of the work we've done with Bayer, where we take an early development lead, something that's still in the lab, and take it to field trials. The assets we acquired from AgBiome earlier this year fit well into this, and so we're excited to continue to expand in that area. Third, we have Bioproduction. Okay, so this is, we believe, a major growth opportunity where customers are looking to either develop or improve the production of a bioactive by fermentation. So you're putting cells in a tank and producing, you know, often a small molecule. This is very similar to the work we do in industrial biotechnology. So we get a lot of efficiency on the technical side.

Speaker Change: And vaccines.

Jason: I'm mentioning when, and to build and optimize trains. Chemicals, Food Flavor, great products, and a range of applications, the Ginkgo customer. Delivery Programs, fans of what we're willing to be much more now, are just the air, and the areas we can deliver. So, again, this slide focuses on our newer offering. Before that... All.

Speaker Change: Small Molecule Bioproducts

Speaker Change: Mentioning

Jason Kelly: The assets we acquired from AgBiome earlier this year fit well into this. And so we're excited to continue to expand in that area. Third, we have bio production. Okay. So this is, we believe, a major growth opportunity where customers are looking to either develop or improve the production of a bioactive by fermentation. So you're putting cells in a tank and producing, you know, often a small molecule. This is very similar to the work we do in industrial biotechnology. So we get a lot of efficiency on the technical side. The same back and infrastructure we use here, we'll be reusing in the next section when I talk about our industrial work.

Speaker Change: Don't expect IP rights, our customers on all the IP at nor royalties or milestones really clean straightforward interaction in the field can sign a lot faster, it's very straightforward in fact.

Jason Kelly: The assets we acquired from ag biome earlier this year fit well into this. And so we're excited to continue expand in that area. Third, we have bio production. Okay. So this is we believe a major growth opportunity where customers are looking to either develop or improve the production of a bioactive by fermentation. So you're putting cells in a tank and producing, you know, often a small molecule. This is very similar to the work we do in industrial biotechnology.

Speaker Change: to build and optimize.

Speaker Change: Strange, Inclusive.

Speaker Change: Chemicals, Food, Flavor

Speaker Change: Great products.

Speaker Change: For larger Biopharma company I think this could just run through procurement rather than needing to be really a sort of a BD negotiation.

Speaker Change: A range of applications.

Jason Kelly: Dmytruk, Jason Kelly.

Duckshin: Delivery Programs

Speaker Change: fan of what we're willing

Speaker Change: Like our solutions okay.

Speaker Change: Okay, much more now.

Speaker Change: So I know, we end up with a lot of customers tuning into these calls so I want to give a little more detail. Because this is really a new offering that ginkgo of what our <unk> offerings look like for drug discovery in particular, so our customer start they're going to give a scope for specific datasets, what they're trying to accomplish and they'll either give us a genetic library or asking you to build it.

Speaker Change: or with the air.

Speaker Change: Pres and the areas we can talk about.

Jason Kelly: So we get a lot of efficiency on the technical side. The same back and infrastructure we use here, we'll be reusing in the next section when I talk about our industrial work. Finally, our last offering is supporting discovery of plant traits. This is typically a customer looking for novel modes of action or protein optimization. It's a large area of research spending in ag and so I think an important one for us. Future.

Jason Kelly: The same back-end infrastructure we use here, we'll be reusing, in the next section when I talk about our industrial work. Finally, our last offering is supporting discovery of plant traits. This is typically a customer looking for novel modes of action or protein optimization. It's a large area of research spending in ag, and so I think an important one for us in the future. Okay, so now I want to talk about pharma industrial solutions. These businesses are focused on helping customers discover, optimize, and manufacture biologically derived products in three key areas here. Our first offering is protein engineering services. So our job there is to build better proteins and enzymes for both pharma and industrial process enzymes, as well as therapeutic and diagnostic biosensors.

Duckshin: So, again.

Jason Kelly: Affordability in the...

Duckshin: is with us.

Jason Kelly: Finally, our last offering is supporting discovery of plant traits. This is typically a customer looking for novel modes of action or protein optimization. It's a large area of research spending in ag, and so I think an important one for us.

Speaker Change: Pipe Togas

Duckshin: to our newer offering.

Jason: We will, from the old and we. It just depends on the type. So now, as we move to the tour. Uh, we have that as a service offer. April, opportunity for with drug discovery. AI and ML is, and Drug Discovery, trained models are growing. I mined a lot of what. Others said things like alfalfa, have your day today at the public. Ginkgo's ability to deploy it is new, used to train for, or to create data. Which is really what the big...

Duckshin: Before that.

Speaker Change: World Class.

Duckshin: Well, we will

Speaker Change: Building.

Speaker Change: DNA contracts and so forth. This is where our proprietary platform comes into play we will use the foundry to generate large multimodal in other words different types of data all assay on the same cell line. For example, and then we have software proprietary software that can curate and annotate that data and make sure. It goes back to your AI.

Duckshin: from the old

Jason Kelly: Future.

Jason Kelly: Okay.

Jason Kelly: So now I want to talk about pharma industrial solutions. These businesses are focused on helping customers discover, optimize, and manufacture biologically derived products in three key areas here. Our first offering is protein engineering services. So our job there is to build better proteins and enzymes for both pharma and industrial process enzymes, as well as therapeutic and diagnostic biosensors. And you can see on the bottom, you know, customer projects we have in these areas. These are all areas we already currently do work in. Next, we have protein production, which is focused on building and optimizing production strains, including creating better ingredients for foods, you know, things like these milk proteins and so on, or finding better ways to manufacture vaccines.

Jason Kelly: Okay. So now I want to talk about pharma industrial solutions. These businesses are focused on helping customers discover, optimize, and manufacture, biologically derived products in three key areas here. Our first offering is protein engineering services. So our job there is to build better proteins and enzymes for both pharma and industrial process enzymes as well as therapeutic and diagnostic biosensors. And you can see on the bottom, you know, customer projects we have in these areas.

Duckshin: It just depends on the type of

Duckshin: So now as we move to the...

Duckshin: We have

Duckshin: That as a service offer

Speaker Change: Pretty brawl.

Speaker Change: Opportunity for

Speaker Change: M L team in a form they can use for model training. That's a real I think unique strengths, we have coupled to the lab data generation.

Speaker Change: with the drug discovery

Duckshin: AI and ML is

Duckshin: and drug discovery.

Jason Kelly: You can see on the bottom, you know, customer projects we have in these areas. These are all areas we already currently do work in. Next, we have protein production, which is focused on building and optimizing production strains, including creating better ingredients for foods, you know, things like these milk proteins and so on, or finding better ways to manufacture vaccines. Lastly, we have a strong offering in small molecule bioproduction. That's what I was just mentioning, when I was talking about the ag, where we're looking to build and optimize small molecule production strains, including pharma APIs, chemicals, food flavor ingredients, and so on. We're creating new strains to create products, with a wide range of applications. So in all of these cases, you can see, Ginkgo customers where we're currently delivering programs.

Speaker Change: The first areas. We're offering these services are functional genomics and antibody develop ability. So in functional genomics, we can provide losses of data for AI model development and target discovery common use cases.

Duckshin: The train models has grown.

Jason Kelly: These are all areas we already currently do work in. Next we have protein production, which is focused on building and optimizing production strains, including creating better ingredients for foods, you know, things like these milk proteins and so on, or finding better ways to manufacture vaccines. Lastly, we have a strong offering and small molecule bioproduction, as I was just mentioning, when I was talking about the ag, where we're looking to build and optimize small molecule production strains, including pharma, API's chemicals, food flavor ingredients and so on.

Speaker Change: Mind a lot of what

Speaker Change: I said things like alfalfa

Speaker Change: Today to make some public.

Speaker Change: Gagos for Thanks for watching, and don't forget to like, share, and subscribe to our channel.

Speaker Change: Ability to deploy it.

Speaker Change: Would be target discovery and validation and then an antibody develop ability.

Speaker Change: are new.

Jason Kelly: Lastly, we have a strong offering in small molecule bioproduction, as I was just mentioning when I was talking about the ag, where we're looking to build and optimize small molecule production strains, including pharma, APIs, chemicals, food flavor ingredients, and so on. We're creating new strains to create products with a wide range of applications. So, in all of these cases, you can see gingo customers were currently delivering programs. These, like I said, this fan of what we're willing to sell is actually much more narrow than it would have been before, but the areas we're doing in are strongest areas and the areas we can deliver most efficiently.

Speaker Change: Robust data packages with key develop a ability metrics for lead optimization or AI ml training that can predict biophysical performance of antibodies based on their amino acid sequences and again a lot more coming here. We are a first sort of customers running now and what we're just at the beginning of this but we are seeing good traction. So please reach.

Speaker Change: used to train proprietors.

Jason: Produced in datasets and protein xp. Unknown Speaker 0 0. Designing the experiments themselves, so Rizk, and you know. Shyam, I'm the Ginkgo, for binding. Thank you. Thank you, data and not provide at Knorr Royalties, straightforward interaction, a lot faster, forward. In fact, I think this could just run, rather than needing to be sort of a BD negotiation.

Speaker Change: or to create data.

Speaker Change: which is really what the

Speaker Change: assisting data sets and

Speaker Change: Protein Act.

Speaker Change: In this case,

Jason Kelly: We're creating new strains to create products with a wide range of applications. So in all of these cases, you can see gingo customers were currently delivering programs. These, like I said, this fan of what we're willing to sell is actually much more narrow than it would have been before, but the areas we're doing in are strongest areas and the areas we can deliver most efficiently. So again, I think this is how we move on this path to profitability in the selling sharing solutions is with this more, more tight focus.

Speaker Change: Designing the experiments themselves.

Speaker Change: the rest for a minute.

Speaker Change: You know, I'll talk to you.

Speaker Change: George if you have a big data set you are planning to generate again, there's a new way to access our platform. We hadn't made available like this directly to customers before so far.

Speaker Change: Last time on the Ginkgo, we...

Jason Kelly: This span of what we're willing to sell is actually much more narrow than it would have been before, but the areas we're doing in are our strongest areas and the areas we can deliver most efficiently. So, again, I think this is how we move on this path to profitability in the cell engineering solutions, is with this more tight focus. Okay, I want to move on to our newer offerings. But, before that, to clear up some confusion I heard after our last call, we will keep signing those solution deals, and we will often be getting milestones and royalties on those deals. Okay? So we're not getting out of getting any milestones and royalties. It just depends on the type of work we're doing for a customer.

Speaker Change: for binding to a

Vincent: and Vincent.

Vincent: data and not provide

Speaker Change: There are people that are really excited to get access to it. So maybe we should have done the sooner, but we're doing it now.

Vincent: At Norgweil teaser.

Jason Kelly: So again, I think this is how we move on this path to profitability in the selling sharing solutions is with this more, more tight focus. Okay, I want to move on to our newer offerings, but before that, to clear up some confusion I heard after our last call, we will keep signing those solution deals, and we will often be getting milestones and royalties on those deals. Okay, so we're not getting out of getting any milestones royalties. It just depends on the type of work we're doing for a customer.

Speaker Change: Okay. So that illustrates the shifts we're making with our cell engineering business.

Vincent: straightforward interaction

Speaker Change: a lot faster.

Speaker Change: I'm now going to turn to what we're seeing within our bio security business, especially with the recent emergence of bird flu H five N. One.

Jason Kelly: Okay, I want to move on to our newer offerings, but before that to clear up some confusion I heard after our last call, we will keep signing those solution deals and we will often be getting milestones and royalties on those deals. Okay, so we're not getting out of getting any milestones royalties. It just depends on the type of work we're doing for a customer.

Speaker Change: ...board. In fact.

Speaker Change: and I think this could just run for...

Speaker Change: rather than needing to be.

Jason: Okay, with a lot of customers, for detail. Offering at Ginkgo. What are our elders?

Speaker Change: Okay. So on the left here you can see some recent articles about the federal funding as well as state and country wide plans to help curtail the spread of H five N. One, but I want to focus more on the rights and the timeline about why this is coming to light today. So H five N. One is not new is first identified 1996, there have been various bouts of it over the years, but the <unk>.

Speaker Change: sort of a beady negotiation.

Speaker Change: Okay.

Speaker Change: But a lot of customers.

Speaker Change: more detail

Jason: Discovery, in particular. For a start, they're going to give us DataSats, either give us a genetically modified Ginkgo to build it, and so forth. Give me a second.

Speaker Change: Offering at Gingko

Jason Kelly: So now, as we move to the tool side of this chart, we have our new lab data as a service offering that I announced at Ginkgo Ferment back in April. We believe we have a major opportunity for LDAS with the drug discovery market. In particular, AI and ML are increasingly being used in drug discovery, and the need for large data sets to train models is growing. So people have mined a lot of what's out there in these public data sets. Things like AlphaFold and so on were trained on the public structure database, the public genome database.

Jason Kelly: So now as we move to the tool side of this chart, we have our new lab data as a service offering that I announced at ginkgo ferment back in April. We believe we have a major opportunity for LDAS with the drug discovery market in particular AI and ML is increasingly being used in drug discovery and the need for large data sets to train models is growing. So people have mined a lot of what's out there in these public data sets things like alpha fold and so on were trained on the public structure database, the public genome database.

Jason Kelly: So now as we move to the tool side of this chart, we have our new Lab Data as a Service offering that I announced at Ginkgo Ferment back in April. We believe we have a major opportunity for LDaaS with the drug discovery market. In particular, AI and ML is increasingly being used in drug discovery, and the need for large data sets to train models is growing. So people have mined a lot of what's out there in these public data sets; things like AlphaFold and so on were trained on the public structure database, the public genome database.

Speaker Change: What are RL....

Speaker Change: Discovery in particular.

Speaker Change: From the start, they're going to give us

Speaker Change: and DataSats.

Speaker Change: Major step change occurred in 2020, when HPA I or highly pathogenic avian influenza was detected in Europe, which then travelled over to North America in 'twenty, one and since January 22, 48 out of the 50 states have seen April outbreaks of H five N. One among poultry impacting over 100 million births you might have.

Speaker Change: either give us a genetic

Speaker Change: and Ginkgo to build it.

Jason: To generate, in other words, different types of all assays. And then we have software. Unidentified Speaker... communicate that data, they can use for modeling, have a couple. Data Generation, areas we're offering these, Antibody Developability, would be target discovery, and then Anna... Unknown Speaker This has been a presentation of the Center for Contemporary Art, the Center for Contemporary Art, the Center for Contemporary Art, and the Center for Contemporary Art at the Center for Contemporary Art. This is a transcript of the webinar's recording, for lead optimization. IML training, and antibodies.

Speaker Change: and so forth.

Terry Flatform: I Terry Flatform comes in.

Terry Flatform: to generate.

Speaker Change: In other words, different types of

Speaker Change: The All Acid.

Jason Kelly: Ginkgo's proprietary automation, the ability to deploy it, allows customers to generate large new data sets that they can use to train proprietary models or to create data in areas that aren't structured, which is really what the big existing data sets in public are, so like things like protein activities and so forth. In this case, our customers are designing the experiments themselves, taking on the majority of the biological risk. For example, they design a ton of antibody sequences, send them to Ginkgo. We synthesize express test those sequences, providing developability assays and since we're mainly providing data and not providing custom solutions.

Jason Kelly: Ginkgo's proprietary automation ability to deploy it allows customers to generate large new data sets that they can use to train proprietary models or to create data in areas that aren't structured, which is really what the big, existing data sets in the public are. So like things like, protein activities and so forth. In this case, our customers are designing the experiments themselves, taking on the majority of the biological risk. For example, they design, you know, a ton of antibody sequences, send them to Ginkgo, we synthesize, express, test those sequences for binding developability assays. And since we're mainly providing data and not providing custom solutions, again, we don't expect IP rights, so our customers own all the IP, nor royalties or milestones. So really clean, straightforward interaction. These deals can sign a lot faster. It's very straightforward.

Jason Kelly: Ginkgo's proprietary automation, the ability to deploy it allows customers to generate large new data sets that they can use to train proprietary models or to create data in areas that aren't structure, which is really what the big existing data sets in public are so like things like protein activities and so forth. In this case, our customers are designing the experiments themselves, taking on the majority of the biological risk, for example, they design a ton of antibody sequences send them to ginkgo.

Terry Flatform: And then we have.

Speaker Change: About this is a big deal.

Speaker Change: Now in the poultry industry. Another step change occurred at the beginning of this year when the virus. Unfortunately, mutated again and became transmissible to mammals specifics.

Terry Flatform: software

Speaker Change: and they can use for model

Speaker Change: Specifically cows, obviously is not great mammals are closer to us it's not the end of the world for humans, because the virus can be passed drives out of milk spent a lot of news about that lately don't drink mantra milk and it can be cooked out of beef, but there is nothing stopping this virus for mutating, yet again into something that could be transmissible to humans.

Terry Flatform: have a couple.

Terry Flatform: Data Generation.

Terry Flatform: areas we're offering these

Terry Flatform: antibody developability.

Terry Flatform: would be target discovery.

Jason Kelly: We synthesize express test those sequences, providing developability assays and since we're mainly providing data and not providing custom solutions. Again, we don't expect IP rights, so our customers on all the IP at nor royalties or milestones really clean straightforward interaction these fields can sign a lot faster very straightforward in fact, you know, for larger biopharm company. I think this could just run through procurement rather than needing to be really a sort of a BD negotiation like our solutions.

Speaker Change: and then it

Speaker Change: So I'm not trying to scare you with this but this is another example of how important persistent pervasive monitoring is we want to catch and crush something like this before hundreds of people are showing up in the hospital with symptoms ideally we detect it much closer to the animal source are that it could jump out of.

Speaker Change: for lead optimizat-

Jason Kelly: Again, we don't expect IP rights, so our customers on all the IP at nor royalties or milestones really clean straightforward interaction. These fields can sign a lot faster, very straightforward in fact, you know, for larger biopharm company. I think this could just run through procurement rather than needing to be really a sort of a BD negotiation like our solutions.

Speaker Change: IML training

Speaker Change: antibodies.

Jason: Thank you, previous customers. Now I'm, This is the beginning of this, but... Reach out to us if you have a.., to generate the forum we had. So far, people have been really.., to it. So maybe we should have done this sooner, but... list, to turn to what we're seeing within our biosecurity business, especially with the federal funding. You can see some recent articles about federal funding, as well as

Speaker Change: Thanks to our customers.

Jason Kelly: In fact, you know, for larger biopharma companies, I think this could just run through procurement, rather than needing to be really a sort of a BD negotiation, like our solutions. Okay, so I know we end up with a lot of customers tuning into these calls, so I want to give a little more detail because this is really a new offering at Ginkgo, of what our LDaaS offerings look like, for drug discovery in particular. So our customers start, they're going to give us scope for specific data sets, you know, what they're trying to accomplish, and they'll either give us a genetic library or ask Ginkgo to build it. We're world-class at building DNA constructs and so forth. This is where our proprietary platform comes into play.

Speaker Change: Now I am

Speaker Change: So now let's go forward a few months to April of this year when the USDA announced an action plan to protect livestock from this particular variance of H five N. One they announced over $800 million in new funding to combat this virus and mandatory testing of dairy cattle that are moved to cross state lines. So from our previous work surrounding bio threat monitoring we know that there are three key.

Speaker Change: This is the beginning of this, but...

Speaker Change: Reach out to us if you have a

Speaker Change: to generate. Again, this is

Jason Kelly: Okay, so I know we end up with a lot of customers tuning into these calls, so I want to give a little more detail because this is really a new offering at Ginkgo of what our LDS offerings look like for drug discovery in particular. So our customers start, they're going to give us a scope for specific data sets, you know what they're trying to accomplish and they'll either give us a genetic library or ask Ginkgo to build it or world class at building DNA constructs and so forth. This is where our proprietary platform comes into play. We'll use the foundry to generate large multimodal, in other words, different types of data, all asset on the same cell line, for example.

Speaker Change: The forum we had

Speaker Change: So far, people didn't relate.

Speaker Change: Let's do it. So maybe we should have done this sooner, but...

Speaker Change: Two a successful plan.

Speaker Change: [inaudible]

Speaker Change: To detect and combat a biological threats, particularly around livestock. So the first is we need to find a way to gather information pervasive Lee second we need to collect genomic information regarding the virus without adding much cost or time to those <unk>.

Speaker Change: to turn to what we're seeing within our biosecurity business, especially with the...

Speaker Change: You can see some recent articles about the federal funding as well as

Jason Kelly: This is where our proprietary platform comes into play, we'll use the foundry to generate large multimodal in other words different types of data all asset on the same cell line, for example. And then we have software, proprietary software that can curate and annotate that data and make sure it goes back to your AIML team in a form they can use for model training. That's a real I think unique strength we have coupled to the lab data generation.

Jason Kelly: We'll use the Foundry, to generate large, multimodal, in other words, different types of data, all assayed on the same cell line, for example. And then we have software, proprietary software, that can curate and annotate that data and make sure it goes back to your AI ML team, in a form they can use for model training. That's a real, I think, unique strength we have, coupled to the lab data generation. The first areas we're offering these services are Functional Genomics and Antibody Developability. So in Functional Genomics, we can provide lots of data for AI model development and target discovery. Common use cases would be target discovery and validation.

Speaker Change: Information gathering plans already there and then third we need to find a way to work with the communities that are impacted while respecting their privacy and concerns and let me tell you. We learned an extreme form of this when we did millions of Covid monitoring tests during COVID-19. The COVID-19 outbreak in K 12 schools, Okay, the privacy and parental concern.

Jason Kelly: And then we have software, proprietary software that can curate and annotate that data and make sure it goes back to your AIML team in a form they can use for model training. That's a real, I think, unique strength we have, coupled to the lab data generation. The first areas we're offering these services are functional genomics and antibody developability. So in functional genomics, we can provide losses of data for AI model development and target discovery. Common use cases would be target discovery and validation. And then an antibody developability robust data packages, the key developed ability metrics for lead optimization or AIML training that can predict biophysical performance of antibodies based on their amino acid sequences.

Speaker Change: There were huge and we have a ton of learnings from scaling that just gigantic business.

Jason Kelly: The first areas we're offering these services are functional genomics and antibody developability. So in functional genomics, we can provide losses of data for AI model development and target discovery common use cases would be target discovery and validation. And then an antibody developability robust data packages, the key developed ability metrics for lead optimization or AIML training that can predict biophysical performance of antibodies based on their amino acid sequences. And again, a lot more coming here, we have our first sort of customers running now and would, you know, we're just at the beginning of this, but we are seeing good traction.

At the peak of it so well there.

Speaker Change: Now in response to these needs I'm excited to announce kinko's proposed genomic analysis program gap for H five N. One giga will use the existing practice of pooling and sampling milk for food safety and add the capability to generate genomic analysis of the H five N. One virus that provides critical data for the science needed to respond to the virus without.

Jason Kelly: And then in antibody developability, robust data packages with key developability metrics for lead optimization or AI ML training that can predict biophysical performance of antibodies based on their amino acid sequences. And again, a lot more coming here. We have our first sort of customers running now, you know, we're just at the beginning of this, but we are seeing good traction. So please reach out to us if you have a big data set you're planning to generate. Again, this is a new way to access our platform. We hadn't made it available like this directly to customers before. So far, people have been really excited to get access to it. So maybe we should have done this sooner, but we're doing it now.

Speaker Change: Adding any extra burden to farmers or the systems. They depend upon the processes noninvasive requires no additional time or logistics from the farms and importantly, the program does not record transmit the source of the milk in the GAAP program. The only information captured the genomic data of the H five N. One virus itself when it's detected okay. So this can be done in a way that is not.

Jason Kelly: And again, a lot more coming here. We have our first sort of customers running now and would, you know, we're just at the beginning of this, but we are seeing good traction.

Jason Kelly: So please reach out to us if you have a big data set you're planning to generate. Again, this is a new way to access our platform. We hadn't made it available like this directly to customers before so far people been really excited to get access to it. So maybe we should done the sooner, but we're doing it now. Okay, so that illustrates the shifts we're making with our cell engineering business.

Dropped into the existing industry now kinko's pilot plan is successful we will begin sequencing H five N. One if we are successful at sequencing. The virus are sequences could potentially be used by pharma companies to develop drugs or vaccines to combat the spread give you extra time to get started on those things and lastly through our sequencing efforts. We're also looking to detect harmful.

Jason Kelly: So maybe we should done the sooner, but we're doing it now.

Jason Kelly: Okay, so that illustrates the shifts we're making with our cell engineering business.

Jason Kelly: Okay, so that illustrates the shifts we're making with our cell engineering business. But I'm now going to turn to what we're seeing within our biosecurity business, especially with the recent emergence of bird flu, H5N1. Okay, so on the left here, you can see some recent articles about the federal funding, as well as state and countrywide plans to help curtail the spread of H5N1. But I want to focus more on the right and the timeline about why this is coming to light today. So H5N1 is not new. It was first identified in 1996. There have been various bouts of it over the years, but the first major step change occurred in 2020, when HPAI, or Highly Pathogenic Avian Influenza, was detected in Europe, which then traveled over to North America in 2021.

Jason Kelly: And I'm now going to turn to what we're seeing within our biosecurity business, especially with the recent emergence of bird flu, H5N1. One. Okay, so on the left here, you can see some recent articles about the federal funding, as well as state and country-wide plans to help curtail the spread of H5N1. But I want to focus more on the right and the timeline about why this is coming to light today. So H5N1 is not new. It's first identified in 1996. There've been various bouts of it over the years, but the first major step change occurred in 2020 when HPAI or highly pathogenic avian influenza was detected in Europe.

Speaker Change: <unk>, specifically ones that could be transmissible to humans. If this does occur we're working on developing partnerships to enable rapid scale up of testing similar to what we did during the Covid pandemic to help get resources to the communities that need them, most you'd like to again test in those areas, where things are happening now the spread of H five N. One may never evolve into a human transmissible diseases.

Jason Kelly: It's first identified 1996. There've been various bouts of it over the years, but the first major step change occurred in 2020 when HPAI or highly pathogenic avian insolenza was detected in Europe. Which then traveled over to North America in 21, and since January 22, 48 out of the 50 states have seen eight outbreaks of H5N1 among poultry impacting over 100 million birds. You might have heard about this a big deal, you know, in the poultry industry.

Speaker Change: Hope, so, but H five N. One shows us how vulnerable we still are as people as a society. We wanted to detect anomalies downwards, where things differ from the norm sequence that you hadn't been seating.

Jason Kelly: Which then traveled over to North America in 21, and since January 22, 48 out of the 50 states have seen eight outbreaks of H5N1 among poultry, impacting over 100 million birds. You might have heard about this big deal, you know, in the poultry industry. Another step change occurred at the beginning of this year when the virus, unfortunately, mutated again and became transmissible to mammals, specifically cows. Obviously, it's not great. Mammals are closer to us. It's not the end of the world for humans because the virus can be pasteurized out of milk, but a lot of news about that lately.

Jason Kelly: And since January 2022, 48 out of the 50 states have seen outbreaks of H5N1 among poultry, impacting over 100 million birds. You might have heard about this; it's a big deal, you know, in the poultry industry. Another step change occurred at the beginning of this year when the virus unfortunately mutated again and became transmissible to mammals, specifically cows. Obviously, it's not great. Mammals are closer to us. It's not the end of the world for humans, 'cause the virus can be pasteurized out of milk. There's been a lot of news about that lately. Don't drink raw milk. And it can be cooked out of beef. But there is nothing stopping this virus from mutating yet again into something that could be transmissible to humans.

Speaker Change: As soon as we can so you get the industry can protect their herds.

Speaker Change: And way of life, and we can all be safer and if when H five N. One does become a risk to humans gingko and its partner stand at the ready to monitor detect and intervene if that time comes I said this before but we should monitor for viruses like we monitor the weather like we do we watch for Hurricanes right.

Jason Kelly: Another step change occurred at the beginning of this year when the virus unfortunately mutated again and became transmissible to mammals, specifically cows. Obviously, it's not great. Mammals are closer to us. It's not the end of the world for humans because the virus can be pasteurized out of milk, but a lot of news about that lately. Don't drink malt raw milk and it can be cooked out of beef, but there is nothing stopping this virus from mutating yet again into something that could be transmissible to humans.

Speaker Change: We're watching all the time, we have a system for evaluating the risk of a storm when it's brewing what category is it H five N. One is a small storm at the moment, but it has the potential to be a category five and we should have our radar running all the time and so hopefully it.

Jason Kelly: Don't drink malt raw milk, and it can be cooked out of beef, but there is nothing stopping this virus from mutating yet again into something that could be transmissible to humans. So I'm not trying to scare you with this, but this is another example of how important persistent, pervasive monitoring is. We want to catch and crush something like this before hundreds of people are showing up in a hospital with symptoms. Ideally, we detected much closer to the animal source that it could jump out of.

Speaker Change: This pilot work is the start of that.

Jason Kelly: So I'm not trying to scare you with this, but this is another example of how important persistent, pervasive monitoring is. We want to catch and crush something like this before hundreds of people are showing up in a hospital with symptoms. Ideally, we detect it much closer to the animal source that it could jump out of. So now let's go forward a few months to April of this year, when the USDA announced an action plan to protect livestock from this particular variant of H5N1. They announced over $800 million in new funding to combat this virus and mandatory testing of dairy cattle when they are moved across state lines.

Jason Kelly: So I'm not trying to scare you with this, but this is another example of how important persistent pervasive monitoring is. We want to catch and crush something like this before hundreds of people are showing up in a hospital with symptoms. Ideally, we detected much closer to the animal source that it could jump out of. So now let's go forward a few months to April of this year when the USDA announced an action plan to protect livestock from this particular variance of H5N1.

Speaker Change: In conclusion, although the second quarter was a difficult one here at kimco as we had to say goodbye to hundreds of friends and coworkers I'm proud of what the team has accomplished truly continuing delivery of our customers for our customers and opening new avenues for growth in.

Speaker Change: In both our tools offerings at H, one offerings, we remain laser focused on our goal to reach profitability, while leading the development of the technology that makes biology easier to engineer Alright, now I'll hand, it back to Megan for the Q&A.

Jason Kelly: So now let's go forward a few months to April of this year when the USDA announced an action plan to protect livestock from this particular variance of H5N1. They announced over $800 million in new funding to combat this virus and mandatory testing of dairy cattle that are moved across state lines.

Jason Kelly: They announced over $800 million in new funding to combat this virus and mandatory testing of dairy cattle that are moved across state lines. So from our previous works surrounding bioprint monitoring, we know that there are three keys to a successful plan to detect and combat a biological threat, particularly around livestock. So the first is we need to find a way to gather information pervasively. Second, we need to collect genomic information regarding the virus without adding much cost or time to those information gathering plans already there. And then third, we need to find a way to work with the communities that are impacted while respecting their privacy and concerns.

Megan: Thanks, Jason as usual I'll start with a question from the public and remind the analysts on the line that if they'd like to ask a question to please raise their hands on them and I'll call on you and open up your line. Thanks al.

Jason Kelly: So from our previous works surrounding bioprint monitoring, we know that there are three keys to a successful plan to detect and combat a biological threat, particularly around livestock. So the first is we need to find a way to gather information pervasively. Second, we need to collect genomic information regarding the virus without adding much cost or time to those information-gathering plans already there. And then third, we need to find a way to work with the communities that are impacted while respecting their privacy and concerns. And let me tell you, we learned an extreme form of this when we did millions of COVID monitoring tests during the COVID outbreak in K-12 schools.

Jason Kelly: So from our previous work surrounding biothreat monitoring, we know that there are three keys to a successful plan to detect and combat a biological threat, particularly around livestock. So the first is we need to find a way to gather information pervasively. Second, we needed to collect genomic information regarding the virus without adding much cost or time to those information gathering plans already there. And then third, we need to find a way to work with the communities that are impacted while respecting their privacy and concerns. And let me tell you, we learned an extreme form of this when we did millions of COVID monitoring tests during COVID, the COVID outbreak in K-12 schools.

Megan: Alright, welcome back everyone as usual, we'll start with retail question and then we will go down our list of analysts so tejas, you'll be up first after a retail question.

Speaker Change: The first one comes from our Investor Inbox and its for you Jason what is the current outlook on some of <unk> Tec any scientific breakthroughs in the next one to two years.

Jason Kelly: And let me tell you, we learned an extreme form of this when we did millions of COVID monitoring tests during COVID outbreak in K-12 schools. Okay, the privacy and parental concerns there were huge, and we have a ton of learnings from scaling that just gigantic business at the peak of it so well there.

Jason: Yeah. So.

Speaker Change: We talked a little bit about opening.

Jason: Opening up our platform directly to customer scientists sort of like democratizing access to our infrastructure I think the great thing about that is it doesn't require a big tech breakthrough.

Jason Kelly: Okay, the privacy and parental concerns there were huge, and we have a ton of learnings from scaling that just gigantic business at the peak of it so well there.

Jason Kelly: Okay, the privacy and parental concerns there were huge, and we have a ton of learnings from scaling that just gigantic business, at the peak of it, so well there. Now, in response to these needs, I'm excited to announce Ginkgo's proposed Genomic Analysis Program, GAP, for H5N1. Ginkgo will use the existing practice of pooling and sampling milk for food safety and add the capability to generate genomic analysis of the H5N1 virus. This provides critical data for the science needed to respond to the virus without adding any extra burden to farmers or the systems they depend on. The process is non-invasive, requires no additional time or logistics from the farm. Importantly, the program does not record or transmit the source of the milk.

Jason Kelly: Now, in response to these needs, I'm excited to announce Ginkgo's proposed genomic analysis program GAP for H5N1. Ginkgo will use the existing practice of pooling and sampling milk for food safety and add the capability to generate genomic analysis of the H5N1 virus. This provides critical data for the science needed to respond to the virus without adding any extra burden to farmers or the systems they depend on. The process is non-invasive, requires no additional time or logistics from the farm. Importantly, the program does not record or transmit the source of the milk. In the gap program, the only information captures the genomic data of the H5N1 virus itself when it's detected.

Jason Kelly: Now in response to these needs, I'm excited to announce Ginkgo's proposed genomic analysis program gap for H5N1. Ginkgo will use the existing practice of pooling and sampling milk for food safety and add the capability to generate genomic analysis of the H5N1 virus. This provides critical data for the science needed to respond to the virus without adding any extra burden to farmers or the systems they depend on. The process is non-invasive requires no additional time or logistics from the farm.

Jason: Ginkgo scientists have had access to all of this infrastructure, we've been able to use it very successfully across customer programs. We have that evidence, but it just hasn't been made directly available against assigned to send our customers and so we have we have a number of interesting things there like we shared last time around how effective the rack automation has.

Speaker Change: Ben in house, both compared to traditional automation and certainly compared to doing work by hand, right getting that out into customers hands would be amazing right lab.

Jason Kelly: Importantly, the program does not record or transmit the source of the milk. In the gap program, the only information captures the genomic data of the H5N1 virus itself when it's detected. Okay, so this can be done in a way that's not disrupted to the existing industry. Now if Ginkgo's pilot plan is successful, we will begin sequencing H5N1. If we are successful at sequencing the virus, our sequences could potentially be used by pharma companies to develop drugs or vaccines to combat the spread.

Speaker Change: Lab data as a service we are seeing pick up on that now even in an interesting new areas.

Jason Kelly: In the GAP program, the only information captured is the genomic data of the H5N1 virus itself when it's detected, okay? So this can be done in a way that's not disruptive to the existing industry. Now, if Ginkgo's pilot plan is successful, we will begin sequencing H5N1. If we are successful at sequencing the virus, our sequences could potentially be used by pharma companies to develop drugs or vaccines to combat the spread, give you extra time to get started on those things. And lastly, through our sequencing efforts, we're also looking to detect harmful variants, specifically ones that could be transmissible to humans. If this does occur, we're working on developing partnerships to enable rapid scale-up of testing, similar to what we did during the COVID pandemic, to help get resources to the communities that need them most.

Speaker Change: You know that that is leveraging our whole suite of ginkgo infrastructure like a flow through.

Jason Kelly: Okay, so this can be done in a way that's not disruptive to the existing industry. Now, if Ginkgo's pilot plan is successful, we will begin sequencing H5N1. If we are successful at sequencing the virus, our sequences could potentially be used by pharma companies to develop drugs or vaccines to combat the spread. Give you extra time to get started on those things. And lastly, through our sequencing efforts, we're also looking to detect harmful variants, specifically ones that could be transmissible to humans. If this does occur, we're working on developing partnerships to enable rapid scale-up of testing, similar to what we did during the COVID pandemic to help get resources to the communities that need them most.

Jason Kelly: Give you extra time to get started on those things. And lastly, through our sequencing efforts, we're also looking to detect harmful variants, specifically ones that could be transmissible to humans. If this does occur, we're working on developing partnerships to enable rapid scale-up of testing, similar to what we did during the COVID pandemic to help get resources to the communities that need them most. You'd like to, again, test in those areas where things are happening.

Speaker Change: Both our assay technology, our build technology, a whole number of different things package together again, that's not something that a customer scientists could just shoot off a bunch of designs and get that kind of data back before.

Speaker Change: So I'm pretty excited about that building large amount a large piece of DNA computational design tools, we have a ton of in house infrastructure that really are already tech breakthroughs and we just need to make them available to folks so that that's sort of what I'm. Most excited about on the tool side.

Speaker Change: Thanks, Jason like I said Tejas here at first your line is now open.

Jason Kelly: You'd like to, again, test in those areas where things are happening. Now the spread of H5N1 may never evolve into a human transmissible disease; let us hope so. But H5N1 shows us how vulnerable we still are as people, as a society. We wanted to detect anomalies, downwards, where things differ from the norm of a sequence that you hadn't been seeing. As soon as we can, so you get the industry can protect their hers and way of life, and we can all be safer. And if one H5N1 does become a risk to humans, Ginkgo and its partner stand at the ready to monitor, detect, and intervene if that time.

Jason Kelly: We'd like to, again, test in those areas where things are happening. Now, the spread of H5N1 may never evolve into a human transmissible disease. Let us hope so. But H5N1 shows us how vulnerable we still are as people, as a society. We wanted to detect anomalies, in other words, where things differ from the norm, of sequence that you hadn't been seeing, as soon as we can, so you could- the industry can, protect their herds, and way of life, and we can all be safer. And if when H5N1 does become a risk to humans, Ginkgo and its partners stand at the ready to monitor, detect, and intervene if that time comes. I've said this before, but we should monitor for viruses like we monitor the weather, like we watch for hurricanes, right?

Tejas: Great can you guys hear me Okay, yes, it does.

Jason Kelly: Now the spread of H5N1 may never evolve into a human transmissible disease, let us hope so. But H5N1 shows us how vulnerable we still are as people, as a society. We wanted to detect anomalies, downwards, where things differ from the norm of a sequence that you hadn't been seeing. As soon as we can, so you get the industry can protect their hers and way of life, and we can all be safer. And if one H5N1 does become a risk to humans, Ginkgo and its partner stand at the ready to monitor, detect, and intervene if that time.

Tejas: So Jason maybe I'll kick it off here with one on the.

Speaker Change: The slide deck can be automated system stuff that you've been working on.

Tejas: How has the progress been with accelerating the startup time for new projects using the rack CCAR can you have in your Boston study and are there any metrics you can share to help us sort of benchmark progress and some of the sort of question on lap.

Speaker Change: Data as a service just any color on <unk>.

Jason Kelly: I said just before, but we should monitor for viruses like we monitor the weather. Like we watch for hurricanes, right? You know, we're watching all the time. We have a system for evaluating the risk of a storm when it's brewing; you know, what category is it? H5N1 is a small storm at the moment, but it has the potential to be a category 5, and we should have our radar running all the time.

Jason Kelly: I said just before but we should monitor for viruses like we monitor the weather like we watch for hurricanes right you know we're watching all the time we have a system for evaluating the risk of a storm when it's brewing you know what category is it H5N1 is a small storm at the moment but it has the potential to be a category five and we should have our radar running all the time and so hopefully this pilot work is the start of that.

Speaker Change: Faction, there relative to expectations and what type of customers you see showing the strongest demand in terms of the order funnel for.

Jason Kelly: You know, we're watching all the time. We have a system for evaluating the risk of a storm when it's brewing. You know, what category is it? H5N1 is a small storm at the moment, but it has the potential to be a category five, and we should have our radar running all the time. And so hopefully, this pilot work is the start of that. In conclusion, although Q2 was a difficult one here at Ginkgo, as we had to say goodbye to hundreds of friends and coworkers, I'm proud of what the team has accomplished, truly, in continuing delivery of our customers—for our customers, and opening new avenues for growth in both our tools offerings and H1 offerings.

Speaker Change: The lab data offering.

Yeah. So let me I'll go in reverse order so on the.

Speaker Change: Data as a service yes, we are seeing traction I think I think the biggest so the biggest category for US I think is going to be companies that are like you can call them like tech bio companies, our AI in bio companies, but you have a whole bunch of.

Jason Kelly: So hopefully, this pilot work is the start of that.

Jason Kelly: In conclusion, although the second quarter was a difficult one, here at Ginkgo, as we had to say goodbye to hundreds of friends and co-workers, I'm proud of what the team has accomplished, truly continuing delivery of our customers for our customers and opening new avenues for growth in both our tools offerings and H5N1 offerings. We remain laser focused on our goal to reach profitability while leading the development of the technology that makes biology easier to engineer. All right.

Jason Kelly: In conclusion although the second quarter was a difficult one here at Ginkgo as we had to say goodbye to hundreds of friends[inaudible] I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going to ask you a question I'm going[inaudible] Yeah, so let me go and reverse order. So on the lab data is the service.

Speaker Change: Either new startups or occasionally like a group within our large biopharma, that's really trying to build in a AI model.

Speaker Change: That sort of proprietary to them to help them discover drugs and they're often starting.

Jason Kelly: We remain laser-focused on our goal to reach profitability while leading the development of the technology that makes biology easier to engineer. All right, now I'll hand it back to Megan for the Q&A.

Speaker Change: With you know some.

Speaker Change: Some of the public models are out there maybe some of the protein design models.

Megan LeDuc: Now I'll hand it back to Megan for the Q&A. Great. Thanks, Jason.

Speaker Change: Sounds of the Alpha bowls or things like that but then when they want to do is fine tune those models with a bunch of additional proprietary data.

Megan LeDuc: Great. Thanks, Jason. As usual, I'll start with a question from the public and remind the analysts on the line that if they'd like to ask a question, to please raise their hands on Zoom, and I'll call on you and open up your line. Thanks, all. All right, welcome back, everyone. As usual, we'll start with retail question, and then we will go down our list of analysts. So Tejas, you'll be up first after our retail question. The first one comes from our investor inbox, and it's for you, Jason. "What is the current outlook on some of Ginkgo's tech? Any signs of breakthroughs in the next 1 to 2 years?

Megan LeDuc: As usual, I'll start with a question from the public and remind the analysts on the line that if they'd like to ask questions, to please raise their hands on Zoom, and I'll call on you and open up your line. Thanks all. All right.

Speaker Change: And so they want to generate large amounts of this data and that drive them quickly I showed that chart of sort of the the.

Speaker Change: The lab bench and the automation.

Speaker Change: Theres no way to generate that amount of data without deploying automation and so so our usual fight with our whole approach even if we're selling a solutions deal is sort of to say hey.

Megan LeDuc: Welcome back, everyone. As usual, we'll start with a retail question, and then we'll go down our list of analysts. So pages, you'll be up first after our retail question.

Speaker Change: For this type of biotech problem, we think generating a huge amount of data is really the way to solve the problem and what's great about the AI Biofog is they believe that implicitly.

Jason Kelly: The first one comes from our investor inbox, and it's for you, Jason. What is the current outlook on some of Ginkgo's tech, any scientific breakthroughs in the next one to two years? Yeah. So, you know, we talked a little bit about opening up our platform directly to customer scientists, sort of like democratizing access to our infrastructure. I think the great thing about that is it doesn't require a big tech breakthrough. You know, Ginkgo scientists have had access to all this infrastructure. We've been able to use it very successfully across customer programs. We have that evidence, but it just hasn't been made directly available, again, to scientists that are customers.

Jason Kelly: Yeah. So, you know, we, we talked a little bit about opening up our platform directly to customer scientists, sort of like democratizing access to our infrastructure. I think the great thing about that is it, it doesn't require a big tech breakthrough. You know, Ginkgo scientists have had access to all this infrastructure. We've been able to use it very successfully across customer programs. We have that evidence, but it just hasn't been made directly available again to scientists that are customers. And so we have, we have a number of interesting things there, like we shared last time, around how effective the Rack automation has been in-house, both compared to traditional automation and certainly compared to doing work by hand, right? Getting that out into customers' hands would be amazing, right?

Speaker Change: Right like that that is foundational to model training as having large amounts of data. So that's a real boon for us and I would say that that's really going to be.

Speaker Change: The big demand side, Mark mentioned, we have even got the deal with like a large tech company right like there's even new entrants into this space that are kind of interesting, but but but.

Mark: In general that category will be first and then I think you'll see the AI efforts intra the biopharma companies.

Mark: And sort of the next layer of demand for lab data as a service.

Jason Kelly: And so we have a number of interesting things there, like we shared last time around how effective the rack automation has been in house, both compared to traditional automation and certainly compared to doing work by hand, right? Getting that out into customers' hands would be amazing, right? Lab data as a service. We're seeing pickup on that now, even in interesting new areas. You know, that is leveraging a whole suite of Ginkgo infrastructure, like a flow through, you know, both our assay technology or build technology, a whole number of different things packaged together. Again, that's not something that a customer scientist could just shoot off a bunch of designs and get that kind of data back before.

Speaker Change: That makes sense.

Speaker Change: Yeah, no that makes sense and then and then on the automation side sort of Onboarding things and racks. So I think it was right about.

Speaker Change: Sort of the rack system as we've had as you know our group out in Emeryville, where are we sort of the Emeryville, California.

Jason Kelly: Lab Data as a Service. We're seeing pickup on that now, even in interesting new areas. You know, that, that is leveraging a whole suite of Ginkgo infrastructure, like a flow through, you know, both our assay technology, our build technology, a whole number of different things packaged together. Again, that's not something that a customer scientist could just shoot off a bunch of designs and get that kind of data back before. So I'm pretty excited about that. Building large amounts, you know, large pieces of DNA, computational design tools. We have a ton of in-house infrastructure that really are already tech breakthroughs, and we just need to make them available to folks. So, that- that's sort of what I'm most excited about on the tool side.

Speaker Change: Zymogen site and team that has been basically developing and improving on the rack hardware since we acquired as I mentioned, a few years ago. They made it much more manufacturable and much more scalable cheaper to build it out proof of software and they've sort of I can.

Speaker Change: <unk> has almost been giggling, Boston like an external customer to that group and so we've not gotten a lot of experience sort of deploying racks quickly. So I'd say the thing I'm. Most excited about is our ability to.

Jason Kelly: So, I'm pretty excited about that building large amount, you know, large fees of DNA, computational design tools. We have a ton of in-house infrastructure that really are already tech breakthroughs, and we just need to make them available to folks. So that's sort of what I'm most excited about on the tool side. Thanks, Jason.

Speaker Change: At Gingko say, hey, we need this new set of equipment added to Iraq setup.

Speaker Change: Getting that quickly assembled into Iraq shipped to Boston, and then just plugged into our existing automation setup by attaching Iraq to it is really exciting to see in practice.

Megan LeDuc: Thanks, Jason. Like I said, Tejas, you're up first. Your line is now open.

Tejas Savant: Like I said, Tages, you're up first. Your line is now open. Great. Can you guys join me, okay? Yeah, hey Tages. Hey.

Steve Mah: Great. Can you guys hear me okay?

[Analyst]: Great. Can you guys hear me okay?

Speaker Change: Because that is just so different than a traditional automation setup right. If you go to a traditional automation vendor your ability to expand the existing inbuilt infrastructure you have.

Jason Kelly: Yeah. Hey, Tejas.

Steve Mah: Okay. So, Jason, maybe I'll kick it off here with one on, you know, the synthesized tech and the automated system stuff that you've been working on. How has the progress been with accelerating the startup time for new projects using the racks you currently have in your Boston facility? And are there any metrics you can share to help us sort of benchmark progress? And similar sort of question on, you know, Lab Data as a Service, just any color on traction there relative to expectations, and what type of customers do you see showing the strongest demand in terms of the order funnel for the Lab Data as a Service offering?

[Analyst]: Okay. So, Jason, maybe I'll kick it off here with one on, you know, the synthesized tech and the automated system stuff that you've been working on. How has the progress been with accelerating the startup time for new projects using the racks you currently have in your Boston facility? And are there any metrics you can share to help us sort of benchmark progress? And similar sort of question on, you know, Lab Data as a Service, just any color on traction there relative to expectations, and what type of customers do you see showing the strongest demand in terms of the order funnel for the Lab Data as a Service offering?

Tejas Savant: So, Jason, maybe I'll kick it off here with one on, you know, the simplified deck, if you automate it, system stuff that you've been working on. How has the progress been with accelerating the startup time for new projects, using the racks you currently have in your Boston facility? And other any metrics, you can share to help us sort of benchmark progress.

Speaker Change: Is basically zero right like if you want to add to your system you got to go through a whole new process going to sit down with downplaying. It all out, whereas we're now just being able to add new systems. We've now expanded the system in Boston twice.

Speaker Change: Easily and so so that that I think is probably the bigger proof 0.1.

Tejas Savant: And some of the sort of question on, you know, lap data service, just any color on traction there, relative to expectations, and what type of customers do you see showing the strongest demand in terms of the order funnel for the lap data offering? Yeah, so let me go and reverse order. So on the lab data is the service. Yeah, we are seeing traction. I think I think the biggest, so the biggest category for us I think is going to be companies that are like you can call them like tech bio companies or AI in bio companies, but you have a whole bunch of either new startups or occasionally like a group within a large bioforma that's really trying to build an AI model.

Speaker Change: When it comes to doing our solutions business, yet we leveraged the rocks, we lever the automation there. We also leverage other infrastructure again go so it really depends on the project how much.

Speaker Change: The racks are really driving change, but as a as an example of how <unk>.

Jason Kelly: ... Yeah, so let me-- I'll go in reverse order. So on the Lab Data as a Service, yeah, we are seeing traction. I think the biggest category for us, I think, is going to be companies that are like, you can call them, like, tech bio companies or AI in bio companies. But you have a whole bunch of either new startups or occasionally, like a group within a large biopharma that's really trying to build a AI model that's sort of proprietary to them to help them discover drugs. And they're often starting with, you know, some of the public models that are out there, maybe it's some of the protein design models, you know, the ESMs or the AlphaFolds or things like that.

Speaker Change: Quickly you can bring in new equipment into an automation setup I think it goes a proof point and I'm hopeful that we can actually bring that to other customers who want to have those racks ultimately land in the hands of our customers labs and ginkgo is a great proof point for that.

Jason Kelly: Yeah, we are seeing traction. I think I think the biggest, so the biggest category for us I think is going to be companies that are like you can call them like tech bio companies or AI in bio companies, but you have a whole bunch of either new startups or occasionally like a group within a large bioforma that's really trying to build an AI model. That's sort of proprietary. And they're often starting with, you know, some of the public models that are out there, maybe some of the protein design models, you know, the SMs or the alpha folds or things like that.

Speaker Change: Got it Super helpful and then one maybe.

Speaker Change: Can chime in here as well, but just curious to get your perspective on you know decent quarter on both sides of the house last guarantee as well as the cell engineering piece.

Speaker Change: That's the guide sort of intact. Despite that is that just you basically de risking the back half of the year in the context of the question as you know recently earlier. This week one of the largest preclinical cro's talks about of a rapid deterioration in the demand environment on the on the globals.

Tejas Savant: That's sort of proprietary. And they're often starting with, you know, some of the public models that are out there, maybe some of the protein design models, you know, the SMs or the Alpha Folds or things like that. But then when they want to do is fine-tune those models with a bunch of additional proprietary data. And so they want to generate large amounts of this data. And that drives them quickly. I showed that chart of sort of the lab bench and the automation. There's no way to generate that amount of data without deploying automation. And so, so our usual fight with our whole approach, even if we're selling a solutions deal, is sort of to say, hey, for this type of biotech problem, we think generating a huge amount of data is really the way to solve the problem.

Jason Kelly: But then what they want to do is fine-tune those models with a bunch of additional proprietary data. And so they want to generate large amounts of this data, and that drives them quickly. I showed that chart of sort of the lab bench and the automation. There's no way to generate that amount of data without deploying automation. And so our usual fight with our whole approach, even if we're selling a solutions deal, is sort of to say, "Hey, for this type of biotech problem, we think generating a huge amount of data is really the way to solve the problem." And what's great about the AI bio folks is they believe that implicitly, right? Like, that is foundational to model training, is having large amounts of data.

Jason Kelly: But then when they want to do is fine tune those models with a bunch of additional proprietary data. And so they want to generate large amounts of this data. And that drives them quickly. I showed that chart of sort of the lab bench and the automation. There's no way to generate that amount of data without deploying automation. And so, so our usual fight with our whole approach, even if we're selling a solutions deal is sort of to say, hey, for this type of biotech problem, we think generating a huge amount of data is really the way to solve the problem.

Speaker Change: Larger pharma side of things and the biotech improvement that's coming through is coming through slower than anticipated as well. So I'm just curious as to what you guys are seeing from those two cause customer constituencies and then as you sort of contemplate at the back half would that really sort of being in the back of your minds and you thought about the guide.

Speaker Change: Yeah, I'd be happy to adjacent to start on the question and Tejas I'll start with bio security first just because I think that's a little bit easier than we can get into cell engineering. So in.

Speaker Change: In the case of bio security of the revenue really popped in the quarter, but you should not interpret that as sort of a new run rate.

Tejas Savant: And what's great about the AI bio folks is they believe that implicitly, right? Like that is foundational to model training, is having large amounts of data. So that's a real boon for us. And I would say that's, that's really going to be the big demand set. You know, Mark mentioned we have even got a deal with like a large tech company, right? Like there's even new entrants into this space that are kind of interesting. But, but, but in general, that category will be first.

Jason Kelly: And what's great about the AI bio folks is they believe that implicitly right like that is foundational to model training is having large amounts of data. So that's a real boon for us. And I would say that's that's really going to be the big demand set. You know, Mark mentioned we have even got a deal with like a large tech company, right? Like there's even new entrants into this space that are kind of interesting.

Speaker Change: Four bio security right now what what happened there was we in effect had some revenue booked in Q2 that we thought originally would have been scheduled or was originally scheduled for Q1, and so you had a little bit of sort of I would just call. It lumpiness tied to a customer contract in Q2.

Jason Kelly: So that's a real boon for us, and I would say that's really going to be the big demand set. We, you know, Mark mentioned we have even got a deal with, like, a large tech company, right? Like, there's even new entrants into this space that are kind of interesting. But in general, that category will be first, and then I think you'll see the AI efforts in the biopharma companies, as sort of the next layer of demand for lab data as a service. Does that make sense?

Jason Kelly: But, but, but in general, that category will be first. And then I think you'll see the AI efforts intra the bio farm accompanies as sort of the next layer of demand for the lab data service. Does that make sense?

Tejas Savant: And then I think you'll see the AI efforts intra the bio farm accompanies as sort of the next layer of demand for the lab data service. Does that make sense? Yeah, that makes sense. And then, and then on the automation side, sort of onboarding things and racks.

Speaker Change: And so you sort of want to average Q1, and Q2 on the Biosecurity side and.

Speaker Change: And not think of Q2 is kind of a run rate and so that's why we kept about security guide intact on the Celgene airing side.

Steve Mah: Yeah, that makes sense.

[Analyst]: Yeah, that makes sense.

Jason Kelly: And then on the automation side, sort of onboarding things and Racks. So I think what's great about sort of the Rack system is we've had this, you know, our group out in Emeryville, where we sort of the Emeryville, California, this is the previous Zymergen site and team that has been basically developing and improving on the Rack hardware. Since we acquired Zymergen a few years ago, they made it much more manufacturable, much more scalable, cheaper to build it out, improve the software. And they've sort of Ginkgo has almost been, you know, Ginkgo in Boston, like an external customer to that group. And so we've had gotten a lot of experience sort of deploying Racks quickly.

Jason Kelly: Yeah, that makes sense. And then and then on the automation side sort of onboarding things and racks. So I think what's great about sort of the rack system is we've had this, you know, our group out in Emoryville where we sort of Emoryville, California, this is the previous Imaging site and team that has been basically developing and improving on the rack hardware. Yeah, since we we applied as Imaging a few years ago, they made it much more manufacturerable much more scalable cheaper to build it out prove the software.

Tejas Savant: So I think what's great about sort of the rack system is we've had this, you know, our group out in Emoryville, where we sort of Emoryville, California, this is the previous Imaging site and team that has been basically developing and improving on the rack hardware. Yeah, since we applied as Imaging a few years ago, they made it much more manufacturable, much more scalable, cheaper to build it out, prove the software. And they've sort of Ginkgo has almost been, you know, Ginkgo in Boston like an external customer to that group. And so we've gotten a lot of experience sort of deploying racks quickly.

Speaker Change: First of all we are going through a restructuring.

Speaker Change: So we consider that when we were.

Speaker Change: When we brought the guidance back in May.

Speaker Change: And we are pleased with the revenue number this quarter, but.

Speaker Change: There's still a lot of work for us to do in terms of both the restructuring as well as the changes we've made in terms of the <unk>.

Jason Kelly: And they've sort of ginkgo has almost been, you know, ginkgo in Boston like an external customer to that group. And so we've gotten a lot of experience sort of deploying racks quickly. So I say the thing I'm I'm most excited about is our ability to add ginkgo say, hey, we need this new set of equipment added to our rack setup. Getting that quickly assembled into a rack shipped to Boston and then just plugged into our existing automation setup by by attaching a rack to it is really exciting to see in practice.

Speaker Change: Commercial terms etcetera, and so we just felt it was appropriate to keep.

Speaker Change: Keep it where it was right now.

Speaker Change: Got it.

Tejas Savant: So I say the thing I'm most excited about is our ability to add ginkgo. Say, hey, we need this new set of equipment added to our rack setup. Getting that quickly assembled into a rack shipped to Boston and then just plugged into our existing automation setup by attaching a rack to it is really exciting to see in practice. Because that's just so different than a traditional automation setup, right? If you go to a traditional automation vendor, your ability to expand the existing inbuilt infrastructure you have is basically zero. Right? Like if you want to add to your system, you got to go through a whole new process, get a sit down with them, plan it all out.

Jason Kelly: So I'd say the thing I'm, I'm most excited about is our ability to, at Ginkgo, say, "Hey, we need this new set of equipment added to our Rack setup." Getting that quickly assembled into a Rack, shipped to Boston, and then just plugged into our existing automation setup by, by attaching a Rack to it, is really exciting to see in practice. Because that's just so different than a traditional automation setup, right? If you go to a traditional automation vendor, your ability to expand the existing inbuilt infrastructure you have is, is basically zero, right? Like, if you want to add to your system, you've got to go through a whole new process, you've got to sit down with them, plan it all out. Whereas we are now just being able to add new systems. We've now expanded the system in Boston twice, very easily.

Jason: And then last one from me, Jason instead of a fuzzy question for you, but you know organizationally in light of all the head count got some sure there's rules or are those people in the organization with Volta evolve expand it changed over the last few months and probably more to come in the next few months as well where are you in terms of that process are you.

Speaker Change: <unk> steady state.

Jason Kelly: Because that's just so different than a traditional automation setup, right? If you go to a traditional automation vendor, your ability to expand the existing inbuilt infrastructure you have is basically zero. Right? Like if you want to add to your system, you got to go through a whole new process, get a sit down with them, plan it all out. Whereas we are now just being able to add new systems we've now expanded the system in Boston twice.

Speaker Change: And if not Mark I mean to your comments there can you just help us think through the degree of sort of.

Jason Kelly: Very easily. And so that that I think is probably the bigger proof point when it comes to doing our solutions business yet we leverage the racks. We love the automation there. We also leverage other infrastructure at ginkgo. So it really depends on the project. How much, you know, the racks are really driving change, but as an example of how quickly you can bring in new equipment into an automation setup, I think it goes a proof point and I'm hopeful that we can actually bring that to other customers who want to have those racks ultimately land in the hands of our customers labs and it goes a great proof point for that. Got it.

Speaker Change: Disruption from that that you anticipate or have already contemplated in the guide. Thank you.

Speaker Change: Yeah, I can speak to that so yeah.

Speaker Change: Yeah, we've made a lot of those changes right out of the gate resort or restructured a little bad grades some business units within the company that are smaller scale than the entire organization.

Tejas Savant: Whereas we are now just being able to add new systems, we've now expanded the system in Boston twice. Very easily. And so that, that I think is probably the bigger proof point when it comes to doing our solutions business. Yet we leverage the racks. We love the automation there. We also leverage other infrastructure at Ginkgo. So it really depends on the project.

Jason Kelly: And so I think is probably the bigger proof point. When it comes to doing our solutions business, yeah, we leverage the racks, we leverage the automation there. We also leverage other infrastructure at Ginkgo, so it really depends on the project, how much, you know, the racks are really driving change. But as an example of how quickly you can bring in new equipment into an automation setup, I think Ginkgo is a proof point, and I'm hopeful that we can actually bring that to other customers who want to have those racks ultimately land in the hands of our customers' labs, and Ginkgo is a great proof point for that.

Speaker Change: <unk> drive a little more P&L accountability and have leaders in charge of those and all of those changes were made alongside like during the restructuring process that those leaders good made choices about who would be on their teams and how to do that work and this was really important to us because we felt if we were going to deliver well for our customers while spending less doing it.

Tejas Savant: How much, you know, the racks are really driving change, but as an example of how quickly you can bring in new equipment into an automation setup, I think it goes a proof point, and I'm hopeful that we can actually bring that to other customers who want to have those racks ultimately land in the hands of our customers' labs, and it goes a great proof point for that. Got it. Super helpful.

Speaker Change: It wasn't just as simple as you know keeping things the same and just having less people and we were going to have to do it in a better way and so I think again.

Speaker Change: Along with Mark I'm pleased with.

Speaker Change: With our revenue this quarter and how that process has been going I think those major changes have occurred and there'll be more bits and pieces here, it's not like you're going to get it right yeah exactly perfect on the first shot but.

Steve Mah: Got it. Super helpful. And then one, maybe, Mark can chime in here as well. But Jason, curious to get your perspective on, you know, decent quarter on both sides of the house, biosecurity as well as, you know, the cell engineering piece. You kept the guide sort of intact besides that. Is that just you, basically de-risking the back half of the year? And the context of the question is, you know, recently, you know, earlier this week, one of the largest sort of preclinical CROs talked about a very rapid deterioration of the demand environment on the global larger pharma side of things. And the biotech improvements that's coming through is coming through slower than anticipated as well. So I'm just curious as to what you guys are seeing from those two customer constituencies.

[Analyst]: Got it. Super helpful. And then one, maybe, Mark can chime in here as well. But Jason, curious to get your perspective on, you know, decent quarter on both sides of the house, biosecurity as well as, you know, the cell engineering piece. You kept the guide sort of intact besides that. Is that just you, basically de-risking the back half of the year? And the context of the question is, you know, recently, you know, earlier this week, one of the largest sort of preclinical CROs talked about a very rapid deterioration of the demand environment on the global larger pharma side of things. And the biotech improvements that's coming through is coming through slower than anticipated as well. So I'm just curious as to what you guys are seeing from those two customer constituencies.

Tejas Savant: Super helpful. And then one maybe Markton chime in your as well, producer, you used to get your perspective on, you know, decent border on on both sides of the house by security as well as, you know, the sell engineering piece. You step the guide sort of intact aside that is that just you basically de-rusting the back half of the earth and the context of the question is, you know, recently, you know, earlier to speak one of the larger certain clinical CROs talked about a very rapid deterioration of the demand environment on the global larger pharmaceutical side of things and the biotech improvement that's coming through is coming to slower than anticipated as well.

Mark Massaro: And then one maybe Markton chime in your as well, producer, you used to get your perspective on, you know, decent border on both sides of the house by security as well as, you know, the sell engineering piece. You step the guide sort of intact aside that is that just you basically de-rusting the back half of the earth and the context of the question is, you know, recently, you know, earlier to speak one of the larger certain clinical CROs talked about a very rapid deterioration of the demand environment on the global larger pharmaceutical side of things and the biotech improvement that's coming through is coming to slower than anticipated as well.

Speaker Change: The major changes have been made.

Speaker Change: Got it thanks, guys appreciate the color. Thanks.

Speaker Change: And.

Speaker Change: Next up we have Matt <unk> at Goldman Sachs. Matt. Your line is now open.

Speaker Change: Great can you.

Matt: Hear me yeah.

Speaker Change: Hey, Mike, Great, Hey, Jason Hey, Mark Hey, Matt.

Speaker Change: Thanks for taking my question.

Matt: Maybe first question for me just how do you make sure your commercial capabilities. So I'm talking about like footprint knowledge based skill set match with your shifts into the tools market, particularly in light of some of the cost reductions you're making.

Mark Massaro: So I'm just curious as to what you guys are seeing from those two customer constituencies. And then, as you sort of contemplated the back half, would that really sort of playing in the back reminds us about the guy.

Tejas Savant: So I'm just curious as to what you guys are seeing from those two customer constituencies. And then as you sort of contemplated the back half, would that really sort of playing in the back reminds us about the guy.

Steve Mah: And then as you sort of contemplated the back half, was that really sort of playing in the back of your minds as you thought about the guide?

Speaker Change: Yeah. So some actually go out a little bit so I think one of the things I like about us entering the tool space.

Mark Massaro: Yeah, I'd be happy, Jason, to start on the question, and Tejas, I'll start with biosecurity first just because I think that's a little bit easier than we can get into cell engineering. So, in the case of biosecurity, the revenue really popped in the quarter, but you should not interpret that as sort of a new run rate for biosecurity right now. What happened there was we, in effect, had some revenue booked in Q2 that we thought originally would have been scheduled, or was originally scheduled, for Q1. And so you had a little bit of sort of I would just call it lumpiness tied to a customer contract in Q2.

Mark Dmytruk: Yeah, I'd be happy, Jason, to start on the question. Tejas, I'll start with Biosecurity first, just because I think that's a little bit easier, and then we can get into Cell Engineering. So, in the case of Biosecurity, the revenue really popped in the quarter, but you should not interpret that as sort of a new run rate for Biosecurity right now. What happened there was, we in effect had some revenue booked in Q2 that we thought originally would have been scheduled or was originally scheduled for Q1. And so you had a little bit of, sort of, I would just call it, lumpiness tied to a customer contract in Q2. And so you sort of want to average Q1 and Q2 on the Biosecurity side and not think of Q2 as kind of a run rate.

Mark Massaro: Yeah, I'd be happy, Jason, to start on the question and Tejas, I'll start with biosecurity first just because I think that's a little bit easier than we can get into cell engineering. So in the case of biosecurity, the revenue really popped in the quarter, but you should not interpret that as sort of a new run rate for biosecurity right now. What happened there was we in effect had some revenue booked in Q2 that we thought originally would have been scheduled or was originally scheduled for Q1.

Speaker Change: Because I think we can kind of ramp into it nicely right like I mentioned is with regard to like the automation, but I think this is effectively is true when it comes to like the lab data generation. The scientific team. So if you look on that I showed that slide where I said, hey, we're selling our customer with the head of R&D and we were an outsource research team delivering them a scientific outcomes.

Mark Massaro: And so you had a little bit of sort of I would just call it lumpiness tied to a customer contract in Q2. And so you sort of want to average Q1 in Q2 on the biosecurity side and and not think of Q2 is kind of a run rate.

Speaker Change: Well the way that was structured our ginkgo was we had ginkgo scientists who were basically internal customers of our platform.

Speaker Change: That that interaction I mean, it was it's a little unfair because they're all under the same roof, but we had so many of those teams.

Mark Massaro: And so you sort of want to average Q1 in Q2 on the biosecurity side and not think of Q2 as kind of a run rate. And so that's why we kept the biosecurity guide intact on the cell engineering side. First of all, we are going through a restructuring. And so we considered that when we were when we brought the guidance back in May, and we are pleased with the revenue number this quarter, but there's still a lot of work for us to do in terms of both the restructuring as well as the changes we've made in terms of the commercial terms, et cetera.

Speaker Change: 100 active R&D projects, all with a a leader for each one all ordering lab work from the boundary of Jingo, that's not too different from receiving lab data as a service requests from an external scientists. So so the nature of how ginkgo managed to do our work that we were able to scale to so many projects across the.

Mark Dmytruk: And so that's why we kept the biosecurity guidance intact. On the cell engineering side, first of all, we are going through a restructuring, and so we considered that when we were, when we brought the guidance down back in May. And we, we are pleased with the revenue number this quarter, but there's still a lot of work for us to do in terms of both the restructuring as well as the changes we've made in terms of the commercial terms, et cetera. And so we just felt it was appropriate to keep it where it was right now.

Mark Massaro: And so that's why we kept the biosecurity guide intact on the cell engineering side. First of all, we are going through a restructuring. And so we considered that when we were when we brought the guidance back in May, and we are pleased with the revenue number this quarter, but there's still a lot of work for us to do in terms of both the restructuring as well as the changes we've made in terms of the commercial terms, et cetera. And so we just felt it was appropriate to keep it where it was right now.

Speaker Change: Worse markets AG industrial Biopharma, all with the same infrastructure and I know, we're spending too much but it's still I think it is quite impressive amount of.

Speaker Change: Lab research would be doing all in one place efficiently was because we were already operating with a certain tools like model internally right and so again, we'll see how it goes but I'm optimistic that by pointing that externally there's going to be some changes, but you know maybe maybe less than you would think just by the nature of how ginkgo did.

Mark Massaro: And so we just felt it was appropriate to keep it where it was right now. Got it.

Steve Mah: ... Got it. And then last one for me, Jason, a bit of a fuzzy question for you, but, you know, organizationally, in light of all the headcount cuts, I'm sure, you know, there's roles, or there's people in your organization whose roles have, you know, evolved, expanded, changed over the last few months and probably more to come in the next, few months as well. Where are you in terms of that process? Are you already in steady state? And if not, Mark, I mean, to your comments there, can you just help us think through, the degree of sort of, disruption from that that you anticipate or have already contemplated in the guide? Thank you.

[Analyst]: ... Got it. And then last one for me, Jason, a bit of a fuzzy question for you, but, you know, organizationally, in light of all the headcount cuts, I'm sure, you know, there's roles, or there's people in your organization whose roles have, you know, evolved, expanded, changed over the last few months and probably more to come in the next, few months as well. Where are you in terms of that process? Are you already in steady state? And if not, Mark, I mean, to your comments there, can you just help us think through, the degree of sort of, disruption from that that you anticipate or have already contemplated in the guide? Thank you.

Jason Kelly: And then last one for me, Jason, a bit of a fuzzy question for you, but you know, organizationally, in light of all the headshot cuts and sure, you know, there's roles or there's people in the organizational roles of, you know, evolved, expanded, changed over the last few months and probably more to come in the next few months as well. Where are you in terms of that process? Are you already in steady state? And if not, Mark, I mean to your comments there, do you just help us think through the degree of sort of disruption from that that you anticipate or have already contemplated, the guys?

Jason Kelly: Got it. And then last one for me, Jason, a bit of a fuzzy question for you, but you know, organizationally in light of all the headshot cuts and sure, you know, there's roles or there's people in the organizational roles of, you know, evolved, expanded, changed over the last few months and probably more to come in the next few months as well. Where are you in terms of that process? Are you already in steady state? And if not, Mark, I mean to your comments there, do you just help us think through the degree of sort of disruption from that that you anticipate or have already contemplated the guys?

Speaker Change: Our work.

Speaker Change: Got it thanks for that and then.

Speaker Change: Maybe just kind of conceptualizing the tools business and and just in the context of the kind of environment, we're in particularly with Biopharma customers.

Speaker Change: It seems like a lot of what you're offering is sort of would come out of like an opex budget for a customer you know libraries software AI models things like that.

Speaker Change: Then there's the Capex side, which I can think of rack systems, but I'm curious about others. As you think about sort of maybe a longer term at a high level sort of a split between sort of an opex purchasing of capex purchase from your customers.

Jason Kelly: Thank you. Yeah, I can speak to that. So we made a lot of those changes right out of the gate. We sort of restructured a little bit, created some business units within the company that are smaller scaled in the entire organization. You know, drive a little more, you know, accountability and have leaders in charge of those. And all those changes were made alongside, like during the restructuring process, that those leaders could make choices about who would be on their teams and how to do that work. And this was really important to us because we felt if we were going to deliver well for our customers while spending less doing it, you know, it wasn't just as simple as, you know, keeping things the same and just having less people.

Jason Kelly: Yeah, I can speak to that. Yeah, we made a lot of those changes right out of the gate. We sort of restructured a little bit, created some business units within the company that are smaller scale than the entire organization to, you know, drive a little more P&L accountability and have leaders in charge of those. And all those changes were made alongside, like, during the restructuring process, so that those leaders could make choices about who would be on their teams and how to do that work. And this was really important to us 'cause we felt if we were gonna deliver well for our customers while spending less doing it, you know, it wasn't just as simple as, you know, keeping things the same and just having less people.

Speaker Change: What do you think the tools business will look like and what would you like it to look like going forward.

Yeah. This is a very good question, yeah. So I think when it comes to <unk>.

Speaker Change: Capex I think the only thing we really have in mind are the rack systems. So we don't have other sort of things in mind, there and we don't see ourselves as sort of experts.

Jason Kelly: And this was really important to us because we felt if we were going to deliver well for our customers while spending less doing it, you know, wasn't just as simple as, you know, keeping things the same and just having less people. We were going to have to do it in a better way. And so I think again, I'm along with Mark. I'm pleased with our revenues is quarter and how that process has been going. I think those major changes have occurred. There'll be more bits and pieces here. It's not like you're going to get it right exactly perfect on the first shot, but the major changes have been made.

Speaker Change: Specialized equipment developers or anything else like that what we're going to have really had a unique need.

And this is true of XI emergent to frankly, which is why the technology was getting developed there at the same time it was for flexible automation right and so I think that's the thing that we can bring out on our equipment basis that whats happened to capex budgets, but even then you now have.

Jason Kelly: We were going to have to do it in a better way. And so I think again, I'm along with Mark. I'm pleased with our revenues in quarter and how that process has been going. I think those major changes have occurred. There'll be more bits and pieces here. It's not like you're going to get it right exactly perfect on the first shot, but the major changes have been made. Thanks, guys. Appreciate the color. Yeah, thanks.

Jason Kelly: We were gonna have to do it in a better way. And so I think, again, I'm along with Mark. I'm pleased with our revenue this quarter and how that process has been going. I think those major changes have occurred. There'll be, you know, more bits and pieces here. It's not like you're gonna get it right exactly perfect on the first shot, but the major changes have been made.

Speaker Change: A lot of how we see that sale happening is we've got our cloud software on top of it that allows you to essentially add more equipment to a setup and then download new protocols and be able to do new things right. So there is also the opportunity for sort of a SaaS.

Steve Mah: Got it. Thanks, guys. Appreciate the color.

[Analyst]: Got it. Thanks, guys. Appreciate the color.

Operator: Thanks guys. Appreciate the color.

Operator: Yeah, thanks.

Jason Kelly: Yeah, thanks.

Matthew Larew: I think they just next up, we have Matt Sykes at Goldman Sachs. Matt, your line is now open. Great. Can you hear me? Yeah. Hey, Matt. Great. Hey, thank you. Hey, Mark. Hey, Megan.

Operator: Thanks, Tejas. Next up, we have Matt Sykes at Goldman Sachs. Matt, your line is now open.

Megan LeDuc: Thanks, Tejas. Next up, we have Matt Sykes at Goldman Sachs. Matt, your line is now open.

That type of business on top of it and we and as I mentioned before we acquired them actually already sold a few systems like that so over the last couple of years, we've had external customers that do pay us.

Matt Sykes: Great, can you hear me?

Jason Kelly: Yeah. Hey, Matt.

Matt Sykes: Great. Hey. Hey, Jason and Mark. Hey, Megan. Thanks for taking my question. Maybe first question for me, just how do you make sure your commercial capabilities, so I'm talking about, like, footprint, knowledge base, skill set, match with your shift into the tools market, particularly in light of some of the cost reductions you're making?

Matthew Larew: Thanks for taking my question. Maybe first question for me just how do you make sure your commercial capabilities. So I'm talking about like footprint knowledge base skill set match with your shift into the tools market, particularly in light of some of the cost reduction. Okay.

Speaker Change: As a small thing.

Speaker Change: One customer too.

Speaker Change: But they pay us a SaaS license.

Speaker Change: License for the software, so and Mercer Enver.

Services and so that so that that's I think that that model otherwise everything will come out of Opex I think pretty much. So when we offer like lab data as a service and things like that we really see it as a still a services business just no no royalties right. It would it really just come straight in as used.

Matthew Larew: Yeah, so I'm actually going to talk about that a little bit. So I think one of the things I like about us entering the tool space is I think we can kind of ramp into it nicely, right? Like I mentioned this with regard to like the automation, but I think this is effectively as true when it comes to like the lab data generation. The scientific team, so if you looked on that, I showed that slide where I said, hey, we're selling our customer with the head of R&D, and we were an outsourced research team delivering them a scientific outcome.

Jason Kelly: Yeah. So, Matt, I can speak to that a little bit. So I think one of the things I like about us entering the tool space is I think we can kind of ramp into it nicely, right? Like, I mentioned this with regard to, like, the automation, but I think this is as effectively as true when it comes to, like, the lab data generation. The scientific team – so if you looked on that, I showed that slide where I said, "Hey, we're selling." Our customer was the head of R&D, and we were an outsourced research team delivering them a scientific outcome. Well, the way that was structured at Ginkgo was we had Ginkgo scientists who were basically internal customers of our platform. That interaction, I mean, we...

Mark Massaro: Yeah, so I'm actually going to talk about that a little bit. So I think one of the things I like about us entering the tool space is I think we can kind of ramp into it nicely, right? Like I mentioned this with regard to like the automation, but I think this is effectively as true when it comes to like the lab data generation. The scientific team, so if you looked on that, I showed that slide where I said, hey, we're selling our customer with the head of R&D, and we were an outsourced research team delivering them a scientific outcome.

Speaker Change: One of the customers buying it right.

Speaker Change: What the customers consuming it we'd be getting paid directly so it's a bit different than the solutions model, where you have these like longer time horizon things that are really going to be ultimately the source of the profit here, we'd have to we'd hopefully be driving our margin on the sales directly of the services.

Matthew Larew: Well, the way that was structured at Ginkgo was we had Ginkgo scientists who were basically internal customers of our platform. That interaction, I mean, it was, you know, it's a little unfair because they're all under the same roof, but we had so many of those teams. We have, you know, 100 active R&D projects, all with a leader for each one, all ordering lab work, you know, from the Foundry at Ginkgo. That's not too different from receiving lab data as a service requests from an external scientist. So the nature of how Ginkgo managed to do our work, the way we're able to scale the so many projects across diverse markets, ag, industrial, biopharma, all with the same infrastructure.

Mark Massaro: Well, the way that was structured at Ginkgo was we had Ginkgo scientists who were basically internal customers of our platform. That interaction, I mean, it was, you know, it's a little unfair because they're all under the same roof, but we had so many of those teams. We have, you know, 100 active R&D project all with a leader for each one, all ordering lab work, you know, from the Foundry at Ginkgo, that's not too different from receiving lab data as a service requests from an external scientist.

Speaker Change: Got it thank you very much.

Speaker Change: Thanks, Matt next up we have Steve MA and TD Count Steve Your line is now open.

Jason Kelly: It was, you know, it's a little unfair 'cause they're all under the same roof, but we had so many of those teams. We have, you know, 100 active R&D projects, all with a leader for each one, all ordering lab work, you know, from the Foundry at Ginkgo. That's not too different from receiving lab data as a service request from an external scientist. So the nature of how Ginkgo managed to do our work, the way we're able to scale to so many projects across diverse markets, ag, industrial, biopharma, all with the same infrastructure, and I know we were spending too much, but it's still, I think it's quite impressive amount of lab research to be doing all in one place efficiently, was because we were already operating with a certain tools like model internally, right?

Steve MA: Oh great.

Steve MA: Hey, guys. Thanks for taking the questions.

I've got a two part question on the reduction in force.

Steve MA: Can you talk about your confidence in the ability to service your.

Speaker Change: Your existing customers New partners and then also be able to onboard the new the cell engineering tools business if it takes off.

Mark Massaro: So the nature of how Ginkgo managed to do our work, the way we're able to scale the so many projects across diverse markets, ag, industrial, biopharma, all with the same infrastructure. And I know we were spending too much, but it's still, I think it's quite impressive amount of lab research to be doing all in one place efficiently was because we were already operating with a certain tools like model internally, right?

Speaker Change: And then the second part of the question can you provide some color on the scope of the risks.

Matthew Larew: And I know we were spending too much, but it's still, I think it's quite impressive amount of lab research to be doing all in one place efficiently. Was because we were already operating with a certain tools like model internally, right?

Speaker Change: Did it impact like all sides equally or are there any concentrations to note.

Speaker Change: Facilities closed or any facility is going to be consolidated they specifically ask that because.

Jason Kelly: And so, I am, you know, again, we'll see how it goes, but I'm optimistic that by pointing that externally, there is gonna be some changes, but, you know, maybe, maybe less than you would think, just by the nature of how Ginkgo did our work.

Matthew Larew: And so I am, you know, again, we'll see how it goes, but I'm optimistic that by pointing that externally, there is going to be some changes. But, you know, maybe, maybe less than you would think, just like the nature of how Ginkgo did our work. Got it, thanks for that.

Jason Kelly: And so I am, you know, again, we'll see how it goes, but I'm optimistic that by pointing that externally, there is going to be some changes, but, you know, maybe, maybe less than you would think, just like the nature of how Ginkgo did our work. Got it, thanks for that.

Speaker Change: Syngenta collaboration announced.

Speaker Change: Announced in July just wondering if that's being done that at Sacramento and if there was any impact to the Sacramento facility.

Speaker Change: Okay. So let me I'll work on.

Matt Sykes: Got it. Thanks for that. And then maybe just kind of conceptualizing the tools business and just in the context of the kind of environment we're in, particularly with biopharma customers, it seems like a lot of what you're offering is sort of would come out of, like, an OpEx budget for a customer, you know, libraries, software, AI models, things like that. Then there's the CapEx side, which I can think of Rack Systems, but I'm curious about others. As you think about sort of maybe in a longer term, at a high level, sort of the split between sort of an OpEx purchase and a CapEx purchase from your customers, what do you think the tools business will look like? And what would you like it to look like going forward?

Speaker Change: Speak to the first one in the market is going to talk a little bit about facilities.

Matthew Larew: And then maybe just kind of conceptualizing the tools business. And just in the context of the kind of environment we're in, particularly with biopharma customers, it seems like a lot of what you're offering is sort of would come out of like an op-x budget for a customer, you know, libraries, software, AI models, things like that. Then there's the CapEx side, which I can think of rack systems, but I'm curious about others. As you think about sort of maybe in a longer term at a high level, sort of the split between sort of an op-x purchase and a CapEx purchase from your customers, what do you think the tools business will look like?

Jason Kelly: And then maybe just kind of conceptualizing the tools business. And just in the context of the kind of environment we're in, particularly with biopharma customers, it seems like a lot of what you're offering is sort of would come out of like an op-x budget for a customer, you know, libraries, software, AI models, things like that. Then there's the CapEx side, which I can think of rack systems, but I'm curious about others.

Speaker Change: So yes, so it wasn't like it was a number one concern for US obviously, we are a high touch white glove services business and protecting all of our existing customer relationships was really critical and so that's why again I was very happy to see you can see it reflected in the revenue, but behind the scenes I think that went really well without a hitch right in the sense that I don't think our customer.

Jason Kelly: As you think about sort of maybe in a longer term at a high level, sort of the split between sort of an op-x purchase and a CapEx purchase from your customers, what do you think the tools business will look like? And what would you like it to look like going forward?

Speaker Change: Our programs were impacted and.

Speaker Change: In our releases, so a negative way even going through the ramp process now we did restructure how we're doing things and that meant that that different groups were affected differently right like the folks working directly on customer programs were affected less than folks and sort of indirect roles and things like that.

Matthew Larew: And what would you like it to look like going forward? Yeah, this is a very good question. Yeah, so I think when it comes to CapEx, I think the only thing we really have in mind are the rack systems. So we don't have other sort of things in mind there. And we don't see ourselves as sort of experts, you know, specialized equipment developers, or anything else like that. What we're getting to really had a unique need, and this was true of Zymrogen too, frankly, which is why the technology was getting developed there at the same time, was for flexible automation, right?

Speaker Change: A large part to make sure we did maintain consistency of delivery for current customer projects and the ability to keep selling new solutions businesses. So our commercial team selling.

Jason Kelly: Yeah, this is a very good question. Yeah, so I think when it comes to CapEx, I think the only thing we really have in mind are the rack systems. So we don't have other sort of things in mind there. And we don't see ourselves as sort of experts, you know, specialized equipment developers or anything else like that. What we're getting to really had a unique need, and this was true of Zymrogen too, frankly, which is why the technology was getting developed there at the same time, was for flexible automation, right?

Jason Kelly: Yeah, this is a very good question. Yeah, so I think when it comes to CapEx, I think the only thing we really have in mind are the Rack systems. So we don't have other sort of things in mind there, and we don't see ourselves as sort of experts, you know, specialized equipment developers or anything else like that. Where Ginkgo really had a unique need, and this was true of Zymergen too, frankly, which is why the technology was getting developed there at the same time, was for flexible automation, right? And so I think that's the thing that we can bring out on an equipment basis that would tap into CapEx budgets.

Speaker Change: Selling you know in those product areas that we're maintaining our also protected and and are still out there selling and adding to that business. As you saw even in the last quarter, which I think was a tough quarter to sell enduring.

Speaker Change: The.

Speaker Change: You also asked about how we expand its tools.

Speaker Change: Given that and so that's where you'll see us make more selective growth, that's where we're really asking a team to operate almost like a startup within gingko and if they demonstrate success. If we see a ton of purchases whether it's on the racks. The AI stuff lab data as a service and it starts to run you'll see us push block.

Matthew Larew: And so I think that's the thing that we can bring out on an equipment basis that would tap into CapEx budgets. But even then, you know, a lot of how we see that sale happening is we've got our cloud software on top of it that allows you to essentially add more equipment to a setup and then download new protocols and be able to do new things, right? Like, so there is also the opportunity for sort of a SaaS type of business on top of it. And we end, you know, as I mentioned before, we acquired them and actually already sold a few systems like that.

Jason Kelly: And so I think that's the thing that we can bring out on an equipment basis that would tap into CapEx budgets. But even then, you know, a lot of how we see that sale happening is we've got our cloud software on top of it that allows you to essentially add more equipment to a setup and then download new protocols and be able to do new things, right? Like, so there is also the opportunity for sort of a SaaS type of business on top of it.

Jason Kelly: But even then, you know, a lot of how we see that sale happening is we've got our cloud software on top of it that allows you to essentially add more equipment to a setup and then download new protocols and be able to do new things, right? Like, so there is also the opportunity for sort of a SaaS type of business on top of it. And we, and, you know, Zymergen, before we acquired them, had actually already sold a few systems like that. So over the last couple of years, we've had external customers that do pay us; it's a small thing, you know, it's only one customer, two. But they pay us a SaaS license for the software, so, and for services. And so that, that's, I think, that model.

Speaker Change: Of resources behind that right and I think you know Google has a good history of this right like I think our experience for example, during the K 12, Covid testing that that grew to a I don't know it was ultimately it's 300 million plus revenue business in a matter of 12 to 18 months, because we had a strong poll and we were able to go behind it product is it in scale against.

Jason Kelly: And we end, you know, as I mentioned before, we acquired them and actually already sold a few systems like that. So over the last couple of years, we've had external customers that do pay us, you know, it's a small thing, you know, the one customer too, but they pay us a SaaS license for the software and for services. And so that's, I think that model. Otherwise, everything would come out off X, I think, pretty much.

Matthew Larew: So, over the last couple of years, we've had external customers that do pay us, you know, it's a small thing, you know, the one customer too, but they pay us a SaaS license for the software and for services. And so that's, I think, that model. Otherwise, everything would come out off X, I think, pretty much. So when we offer like lab data as a service and things like that, we really see it as a still services business. Just no royalties, right? It would really just come, you know, straight in as used when the customer is buying it, right?

That demand if that happens in any of these tool areas I don't think we'll have trouble scaling behind that I think where were those kind of people, but we do need to kind of turn those cards over and see if any of them at ace.

Jason Kelly: Otherwise, everything would come out of OpEx, I think, pretty much. So when we offer, like, lab data as a service and things like that, we really see it as still a services business. Just no royalties, right? It would really just come, you know, straight in as used when the customer is buying it, right? So or when the customer is consuming it, we'd be getting paid directly. So it's a bit different than the solutions model, where you have these, like, longer time horizon things that are really going to be ultimately the source of the profit. Here, we'd hopefully be driving a margin on the sales directly of the services.

Speaker Change: That's worth pouring all bunch of resource behind but we're certainly kind of at we're running the experiment and if it hits, you'll you'll see us lean more into it.

Jason Kelly: So when we offer like lab data as a service and things like that, we really see it as a still services business. Just no royalties, right? It would really just come, you know, straight in as used when the customer is buying it, right? So or wouldn't customers consuming it? We'd be getting paid directly. So it's a bit different than the solutions model where you have these like longer time horizon things that are really going to be ultimately the source of the profit.

Mark: And then Mark Mark you want speak to the yeah, Yeah I'll take the second part of the questions of first of all West Sacramento It wasn't.

Matthew Larew: So, or wouldn't customers consuming it? We'd be getting paid directly. So it's a bit different than the solutions model where you have these like longer time horizon things that are really going to be ultimately the source of the profit. Here, we'd have to, we'd hopefully be driving a margin on the sales directly of the. Thank you very much.

Speaker Change: Isn't going to be impacted in terms of sage.

Mark Mark: <unk>. So we're happy with the agriculture business, we've rolled up really good capabilities. It is centered at west as you know and yeah, there's a little bit of excess space. There. So you'll you'll probably still see a few small sub leases on that excess space sort of opportunistically, but.

Matthew Larew: Here, we'd have to, we'd hopefully be driving a margin on the sales directly of the Thank you very much. Thanks Matt.

Mike Ryskin: Got it. Thank you very much.

Matt Sykes: Got it. Thank you very much.

Jason Kelly: Yep.

Steve MA: Thanks, Matt. Next up, we have Steve Ma at TD County. Steve, your line is now open. Oh great. Hey, how are you doing? Thanks for taking the question. I got a two-part question on the reduction force. You know, can talk about your confidence and the ability to service your, you know, your existing customers, new partners, and then also be able to onboard the new sell engineering tools. Business, if it takes off. And then the second part of the question, can you provide some color on the scope of the riff? You know, did it impact like, you know, all sites equally, or are there any concentrations to note, or any facilities closed, or any facilities going to be consolidated?

Operator: Thanks, Matt. Next up, we have Steve Mah at TD Cowen. Steve, your line is now open.

Megan LeDuc: Thanks, Matt. Next up, we have Steve Mah at TD Cowen. Steve, your line is now open.

Steve MA: Next up, we have Steve Ma at TD County. Steve, your line is now open. Oh great. Hey, how are you doing? Thanks for taking the question. I got a two-part question on the reduction force. You know, can talk about your confidence and the ability to service your, you know, your existing customers, new partners, and then also be able to onboard the new sell engineering tools. Business, if it takes off. And then the second part of the question, can you provide some color on the scope of the riff?

Mark Mark: But no that's a room.

Jason Kelly: Hey, Steve.

Steve Mah: Oh, great. Hey, how you doing? Thanks for taking the questions. I got a two-part question on the reduction in force. You know, can you talk about your confidence in the ability to service your, you know, your existing customers, new partners, and then also be able to onboard the new cell engineering tools business if it takes off? And then the second part of the question, can you provide some color on the scope of the RIF? You know, did it impact like, you know, all sites equally, or are there any concentrations to note, or any facilities closed, or any facilities going to be consolidated?

Mark Mark: <unk>.

Steve MA: Generally speaking Steve.

Steve MA: You know, did it impact like, you know, all sites equally or are there any concentrations to note or any facilities closed or any facilities going to be consolidated? They specifically asked that because, you know, on the Syngenta collaboration announced in July, just want to know if that's being done at Sacramento. And if there was any impact to the Sacramento facility. Okay.

Speaker Change: The risk was like.

Steve MA: Fairly broad based meaning that it touched.

Speaker Change: I'd say all parts of the company when you think about operational or foundry types apartments, as well as G&A functions.

Just as well as various locations. So I would just describe it as sort of like pretty broad based as opposed to focus on a particular location.

Speaker Change: Okay. Thanks for the color.

Speaker Change: The only thing although I would add about you will see us like a big thing that we have to get out of these spaces that that reduces the kind of overhead costs of maintaining the H S costs and facilities costs and everything else that already save us a lot of money and then once we're out of them, we would like to sublease them.

Steve MA: They specifically asked that because, you know, on the Syngenta collaboration announced in July, just want to know if that's being done at Sacramento. And if there was any impact to the Sacramento facility. Okay.

Steve Mah: I specifically ask that because, you know, on the Syngenta collaboration announced in July, just wondering if that's being done at Sacramento and if there was any impact to the Sacramento facility.

Jason Kelly: Okay. So I'll speak to the first one, and then, Mark, if you want to talk a little bit about facilities. So yes, this is, like, was the number one concern for us. Obviously, we are a, you know, high-touch, white-glove, services business, and protecting all of our existing customer relationships was really critical. And so that's why, again, I was very happy to see. You can see it reflected in the revenue, but behind the scenes, I think that went really well without a hitch, right? In the sense that I don't think our customer programs were impacted and, you know, in a really significantly negative way, even going through the RIF process.

Jason Kelly: So I'll, maybe I'll work on, I'll speak to the first one in the market and talk a little bit about facilities. So, yes, so this is like a, with a number one concern for us. Obviously, we are a, you know, high-touch white glove services business, and protecting all of our existing customer relief just was really critical. And so that's why, again, I was very happy to see you can see it reflected in the revenue, but behind the scenes. I think that went really well, without a hitch, right in the sense that I don't think our customer programs were impacted.

Jason Kelly: So I'll, maybe I'll work on, I'll speak to the first one in the market and talk a little bit about facilities. So, yes, so this is like a, with a number one concern for us. Obviously we are a, you know, high-touch white glove services business and protecting all of our existing customer relief just was really critical. And so that's why again, I was very happy to see you can see it reflected in the revenue, but behind the scenes.

Speaker Change: And so I think you'll also see us be strategic right like if someone want to rent all by a fab one sounds good to me right like we get we can say right here in dry dock right like you we will be hungry for.

Where we can pick up cash quickly so that I can offsets our cash burn and make sure. We have the stability to grow this business right. So you'll see us be opportunistic about where we see where we see sublease opportunities with our real estate.

Jason Kelly: I think that went really well without a hitch, right in the sense that I don't think our customer programs were impacted. And, you know, in an interview, it really is a negative way, even going through the riff process. Now, we did restructure how we're doing things. And that meant that that different groups were affected differently, right? Like the folks working directly on customer programs were affected less than folks and sort of indirect roles and things like that.

Jason Kelly: And, you know, in an interview, it really is a negative way, even going through the riff process. Now, we did restructure how we're doing things. And that meant that different groups were affected differently, right? Like the folks working directly on customer programs were affected less than folks in sort of indirect roles and things like that. In a large part to make sure we did maintain consistency of delivery for current customer projects and the ability to keep selling new solutions businesses. So our commercial team that's selling, you know, in those product areas. That we're maintaining are also, you know, protected and are still out there selling and adding to that business.

Speaker Change: Okay. Thanks, I'll call out there.

Jason Kelly: Now, we did restructure how we're doing things, and that meant that, that different groups were affected differently, right? Like, the folks working directly on customer programs were affected less than, folks in sort of indirect roles and things like that. For a large part, to make sure we did maintain consistency of delivery for current customer projects and the ability to keep selling new solutions businesses. So, our commercial team, that's selling, you know, in those product areas that we're maintaining, are also, you know, protected and are still out there selling and adding to that business, as you saw even in the last quarter, which I think was a tough quarter to sell during. You also asked about how we expanded tools, given that.

Speaker Change: Thanks, Steve next up we have Mike Raskin at Bank of America, Mike. Your line is now open.

Speaker Change: No Mike.

Mike Raskin: Hey can you guys hear me.

Speaker Change: Okay.

Jason Kelly: In a large part to make sure we did maintain consistency of delivery for current customer projects and the ability to keep selling new solutions businesses. So our commercial team that's selling, you know, in those product areas. That we're maintaining are also, you know, protected and are still out there selling and adding to that business. As you saw, even in the last quarter, which I think was a top quarter to sell during the you also asked about how we expanded tools.

Mike Raskin: Couple of quick follow up questions first on the you know the <unk> workflows some of the things you highlighted.

Speaker Change #101: Obviously, you guys have a lot of capability.

Speaker Change #102: About breakdown component by component.

Speaker Change #101: And certainly there are a.

Speaker Change #101: For a more traditional pharma that could probably benefit from it.

Speaker Change #103: Football nation.

Jason Kelly: As you saw, even in the last quarter, which I think was a top quarter to sell during the, you also asked about how we expanded tools. I given that. And so that's where you'll see us make more selective growth bets, where we're really asking a team to operate almost like a startup within Gingo. And if they demonstrate success, if we see a ton of purchases, whether it's on the racks, the AI stuff, the lab data is a service and it starts to run, you'll see us push lots of resources behind that, right? And I think, you know, Gingo has a good history of this, right?

Speaker Change #101: Incorporating AI.

And just sort of high throughput.

Speaker Change #101: Screening for some of these.

Speaker Change #101: Programs, but youre not the only ones doing this right now there are a number of companies who have come up over the last five years that are doing some sort of high throughput functional genomics antibody development.

Jason Kelly: I given that. And so that's where you'll see us make more selective growth bets, where we're really asking a team to operate almost like a startup within Gingo. And if they demonstrate success, if we see a ton of purchases, whether it's on the racks, the AI stuff, the lab data is a service and it starts to run, you'll see us push lots of resources behind that, right? And I think, you know, Gingo has a good history of this, right?

Jason Kelly: And so that's where you'll see us make more selective growth bets, where we're really asking a team to operate almost like a startup within Ginkgo. And if they demonstrate success, if we see a ton of purchases, whether it's on the racks, the AI stuff, lab data as a service, and it starts to run, you'll see us push lots of resources behind that, right? And I think, you know, Ginkgo has a good history of this, right? Like, I think our experience, for example, during the K-12 COVID testing, you know, that grew to a, I don't know what it was ultimately, you know, $300 million-plus revenue business in a matter of 12 to 18 months. Because we had a strong pull, and we were able to go behind it, productize it, and scale against that demand.

Speaker Change #104: If you really look at each of these capabilities as a technology that already exists. So I'm. Just wondering you have the capabilities here, but you sort of are coming out a little bit of wait and some of the existing.

Speaker Change #104: Players so.

How do you view.

Catching up in that space, and what I think actually as a relatively competitive.

Jason Kelly: I think our experience, for example, during the K-12 COVID testing, you know, that that grew to a, I don't know what it was ultimately, a 300 million plus revenue business in a matter of 12 to 18 months, because we had a strong pull and we were able to go behind it, productize it and scale against that demand. If that happens in any of these tool areas, I don't think we'll have trouble scaling behind it. I think we're those kind of people, but we do need to kind of turn those cards over and see if any of them is an ace.

Jason Kelly: I think our experience, for example, during the K 12 COVID testing, you know, that that grew to a, I don't know what it was ultimately a 300 million plus revenue business in a matter of 12 to 18 months, because we had a strong pull and we were able to go behind it, productize it and scale against that demand. If that happens in any of these tool areas, I don't think we'll have trouble scaling behind it.

Space when it comes to.

Speaker Change #104: Some of these new.

Speaker Change #104: A large multimodal datasets.

Speaker Change #104: Yeah, I mean, I think the best way.

Speaker Change #104: And kind of feathers out pretty quick right. So I think you do see a couple of players who.

Jason Kelly: If that happens in any of these tool areas, I don't think we'll have trouble scaling behind it. I think we're those kind of people. But we do need to kind of turn those cards over and see if any of them is an ace, that's worth pouring a bunch of resource behind. But we're certainly kind of, we're like running the experiment, and if it hits, you'll see us lean more into it. Mark, do you want to speak to the,

Speaker Change #104: Sort of invested early in the AI space built up lab infrastructure like a reversion or something.

Jason Kelly: I think we're we're those kind of people, but we do need to kind of turn those cards over and see if any of them is an ace. That's that's worth pouring a bunch of resource behind, but we're certainly kind of running the experiment and if it hits, you'll, you'll see us lean more into it.

Speaker Change #104: Or do you think they are really proprietary good Tac, but again are largely using it for their own pipeline and not really trying to do like a broad based services thing maybe they change that in the future, but I think that's the just.

Jason Kelly: That's that's worth pouring a bunch of resource behind, but we're certainly kind of running the experiment, and if it hits, you'll see us lean more into it.

Mark Massaro: Mark, Mark, do you want to speak to the? Yeah, yeah, I'll take the second part of the question. So first of all, West Sacramento wasn't and isn't going to be impacted in terms of site rationalization. So we're happy with the agriculture business. We've rolled up really good capabilities. It is centered at West, as you know, and yeah, there's a little bit of excess space there. So you'll probably see a few small subleases on that excess space, sort of opportunistically, but. But now that site is it remains generally speaking, see the the the riff was like fairly broad based, meaning that it touched.

Mark Massaro: Mark, Mark, do you want to speak to the yeah, yeah, I'll take the second part of the question. So first of all, West Sacramento wasn't and isn't going to be impacted in terms of site rationalization. So what we're happy with the agriculture business. We've rolled up really good capabilities. It is centered at West, as you know, and yeah, there's a little bit of excess space there. So you'll probably see a few small sub leases on that excess space, sort of opportunistically, but.

Speaker Change #105: Traditional <unk> that are out there I think I take antibody develop ability. Okay. I think on the antibody binding side you have a lot of players, but when it comes to develop ability like those assays are kind of tough to do at high throughput and honestly with the customers that are coming to us are coming to us because they can't get hundreds or thousands of data points and develop ability. So I don't I don't actually think we're behind.

Mark Dmytruk: Yeah, yeah. I'll take the second part of the question. So first of all, West Sacramento wasn't and isn't going to be impacted in terms of site rationalization. So we're happy with the agriculture business. We've rolled up really good capabilities. It is centered at West Sac, as you know. And yeah, there's a little bit of excess space there, so you'll probably see us do a few small subleases on that excess space, sort of opportunistically. But, but no, that site remains. Generally speaking, Steve, the RIF was, like, fairly broad-based, meaning that it touched, I would say, all parts of the company when you think about operational or foundry-type departments, as well as G&A functions, just as well as various locations.

Speaker Change #104: Been there.

Speaker Change #106: Okay, Yeah, I don't want to name any names, but I think we all know who the existing players are so we're talking about the same one okay and then on the it's probably been one that was an interesting overview and something we've been following for a couple of different reasons, but just curious.

Mark Massaro: But now that site is it remains generally speaking, see the the the riff was like fairly broad based, meaning that it touched. I would say all parts of the company when you think about operational or foundry type departments as well as G&A functions, just as well as various locations. So I would just describe it as sort of like pretty broad base as opposed to focus on a particular location. Okay. Thanks for the caller.

Speaker Change #106: You know that the proposal the genomic analysis program all of that.

Speaker Change #106: Makes sense.

Mark Massaro: I would say all parts of the company when you think about operational or foundry type departments, as well as G&A functions, just as well as various locations. So I would just describe it as sort of like pretty broad base as opposed to focus on a particular location. Okay. Thanks for the caller. Maybe only else I would add about you will see us like a big thing. We have to get out of these spaces. That reduces the kind of overhead costs of maintaining them, the NHS costs, and the facilities costs and everything else. That already saves us a lot of money.

Speaker Change #106: Any.

Speaker Change #106: Our minds, we should look to as this is sort of like how do you get this from theoretical too.

Speaker Change #106: Actually implemented.

Speaker Change #107: Yeah, So to address where we are today is we're currently entering into agreements with dairy farms for sort of H five N. One testing under that pilot I think if those go well and we start to be able to show data coming out of that then I. Then I think that's what opens the door to ultimately tapping either government or private sector money. There. So we'll have to see how the kind of day.

Mark Dmytruk: So, I would just describe it as sort of like pretty broad-based, as opposed to focused on a particular location.

Steve Mah: Okay. Thanks for the color.

Jason Kelly: And maybe the only thing else I would add about, you know, you will see us, like a big thing, we have to get out of these spaces. That reduces the kind of overhead costs of maintaining them, the EHS costs, and the facilities costs, and everything else. That already saves us a lot of money. And then once we're out of them, we would like to sublease them. And so, I think you will also see us be strategic, right? Like, if someone wanted to rent all BioFab1, sounds good to me, right? Like, we could stay right here in dry dock, right? Like, we will be hungry for where we can pick up cash quickly so that I can offset our cash burn and make sure we have the stability to grow this business, right?

Mark Massaro: Maybe only else I would add about you will see us like a big thing. We have to get out of these spaces. That reduces the kind of overhead costs of maintaining them, the NHS costs and the facilities costs and everything else. That already saves us a lot of money. And then once we're out of them, we would like to sub release them. And so, so I think you will also see us be strategic, right?

Speaker Change #107: Jen goes in the coming months.

Speaker Change #107: Alright, Thank you yep.

Mark Massaro: And then once we're out of them, we would like to sub-release them. And so, so I think you will also see us be strategic, right? Like if someone wanted to rent all via Fab1, sounds good to me, right? Like we could say right here in dry dock, right? Like we will be hungry for where we can pick up cash quickly so that I can offset our cash burn and make sure we have this ability to grow this business, right? So you'll see us be opportunistic about where we see sublies opportunities with the real estate. Okay.

Mark Massaro: Thanks, Mike next definitely is Mark Massaro at DTA, Jean Marc Your line is now open.

Mark Massaro: Like if someone wanted to rent all via Fab1, sounds good to me, right? Like we could say right here in dry dock, right? Like we will be hungry for where we can pick up cash quickly so that I can offset our cash burn and make sure we have this ability to grow this business, right? So you'll see us be opportunistic about where we see where we see sublies opportunities with the real estate. Okay. Thanks for the call out there. Yeah. Thanks, Steve.

Mark Massaro: Great can you hear me okay.

Mark Massaro: Yeah, Hey, Mark Hey, great.

Mark: Great Hey, guys.

Speaker Change #109: So my first question is on the lab data as a service.

Mark: Transition.

Mark: How should we think about the.

Jason Kelly: So you'll see us be opportunistic about where we see, where we see sublease opportunities with the real estate.

Mark: Potential or expected value or maybe the economics of these types of deals relative.

Speaker Change #110: Relative to some of the existing cell programs do you have a 140 active so programs what I'm just trying to determine is like.

Steve Mah: Okay. Thanks for the call, sir.

Steve MA: Thanks for the call out there. Yeah. Thanks, Steve.

Jason Kelly: Yeah.

Operator: Thanks, Steve. Next up, we have Mike Ryskin at Bank of America. Mike, your line is now open.

Megan LeDuc: Thanks, Steve. Next up, we have Mike Ryskin at Bank of America. Mike, your line is now open.

Mike Reifian: Next up, we have Mike Reifian at Bank of America. Mike, your line is now open. Mike. Hey, can you guys hear me? Yeah. Okay. That's one.

Speaker Change #110: One of these <unk> projects comparably similar to your existing cell engineering programs is any Intel on expected value economics, I think would be helpful.

Megan LeDuc: Hey, Mike.

Steve Mah: Hey, can you guys hear me?

Mike Ryskin: Hey, can you guys hear me?

Jason Kelly: Yeah. Yeah.

Steve Mah: Okay, excellent. Yeah. A couple quick follow-up questions. First, on the, you know, the LDaaS workflow, some of the things you highlighted. Obviously, you guys have a lot of capabilities here to sort of take it down, break it down component by component. And certainly, there are a lot of more traditional pharma that could probably benefit from, you know, improved automation, you know, incorporating AI, and just sort of high-throughput screening for some of these programs. But you're not the only ones doing this, right? You know, there are a number of companies that have come up over the last five years that are doing some sort of high-throughput functional genomics, antibody development.

Mike Ryskin: Okay, excellent. Yeah. A couple quick follow-up questions. First, on the, you know, the LDaaS workflow, some of the things you highlighted. Obviously, you guys have a lot of capabilities here to sort of take it down, break it down component by component. And certainly, there are a lot of more traditional pharma that could probably benefit from, you know, improved automation, you know, incorporating AI, and just sort of high-throughput screening for some of these programs. But you're not the only ones doing this, right? You know, there are a number of companies that have come up over the last five years that are doing some sort of high-throughput functional genomics, antibody development.

Mike Reifian: Couple of questions first on the, you know, the LDS workflow, some of the things you highlighted. Obviously, you guys have a lot of capabilities here to sort of take it down, bring it down component by component. And certainly there are a lot of more traditional form of the properly benefit from improved automation, you know, incorporating AI and just sort of hide the root, but screening for some of these programs. But you're not the only ones doing this, right? Now there are a number of companies that have come up over the last five years that are doing some sort of high throughput functional genomics, antibody development.

Mike Reifian: Couple of questions first on the, you know, the LDS workflow, some of the things you highlighted. Obviously you guys have a lot of capabilities here to sort of take it down, bring it down component by component. And certainly there are a lot of more traditional form of the properly benefit from improved automation, you know, incorporating AI and just sort of hide the root, but screening for some of these programs. But you're not the only ones doing this, right?

So they are much smaller in size than a typical end to end. So engineering program. They would also be much shorter in duration. So the.

Speaker Change #110: Revenue would burn faster on those.

Speaker Change #110: And I think the idea, though is that our customers not just buying one el Das project from ginkgo, but the after.

Speaker Change #110: After buying and getting data, they're buying more data and more data and so the customers become.

Mike Reifian: Now there are a number of companies that have come up over the last five years that are doing some sort of high throughput functional genomics, antibody development. You know, if you if you really look at each of these capabilities, this is the technology that already exists. So I'm just wondering, you know, you have the capabilities here, but you serve are coming out of what a little way to some of the existing players.

Speaker Change #110: It could very well be that the aggregate amount that's purchased would look like.

Mike Ryskin: ... you know, if you really look at each of these capabilities, this is technology that already exists. So I'm just wondering, you know, you have the capabilities here, but you sort of are coming at it a little bit later than some of the existing players. So, how do you view, you know, catching up in that space, in what I think actually is a relatively competitive space when it comes to some of these new, you know, large multimodal data sets?

Mike Reifian: You know, if you really look at each of these capabilities, this is the technology that already exists. So I'm just wondering, you know, you have the capabilities here, but you serve are coming out of what a little way to some of the existing players. So how do you, you know, catching up in that space? And what I think actually is a relatively competitive space when it comes to some of these new, you know, large multimodal data stuff. Yeah, I mean, it depends what, like, it kind of feathers out pretty quick, right? So I think you do see a couple players who sort of invested early in the AI space, built up lab infrastructure like Recursion or something.

Jay: A larger sell engineering program Jay.

Speaker Change #110: Jason.

Speaker Change #110: And I think that covers I think we're a little bit early in the market to know, but I would say the gist is faster to close last total dollars a shorter period of time and so each one you shouldn't think of it like it's the same as our sell engineering solutions or does early so I'm actually hopeful we end up having a lot more of the as Alt AST and we would be able to close of cylinder.

Mike Reifian: So how do you, you know, catching up in that space? And what I think actually is a relatively competitive space when it comes to some of these new, you know, large multimodal data stuff. Yeah, I mean, it depends what like it kind of feathers out pretty quick, right? So I think you do see a couple players who sort of invested early in the AI space built up lab infrastructure like recursion or something.

Jason Kelly: Yeah, I mean, I think it depends what-- like, it kind of feathers out pretty quick, right? So I think you do see a couple players who sort of invested early in the AI space, built up lab infrastructure, like Recursion or something, or I do think they have really proprietary good tech. But again, are largely using it for their own pipeline and not really trying to do, like, a broad-based services thing. Maybe they change that in the future, but I think that's the gist. Among traditional CROs that are out there, I think, like, take antibody developability, okay? I think on the antibody binding side, you have a lot of players, but when it comes to developability, like, those assays are kind of tough to do at high throughput.

Solutions deals that I'm pretty much has to be that way for for this business to work. So they wont end up being apples to apples the solutions deals are great. They just.

Speaker Change #110: They're just they take a long time to close you know like they're really I'm working with each one is like a research partnership right, whereas the old asking much more transactional and I imagine its a bit on the call that we're finding will likely engage through procurement. If we're dealing with a larger company. There. So it'll just be something people are like buying off the rack.

Jason Kelly: Or I do think they have really proprietary good tech, but again, are largely using it for their own pipeline and not really trying to do like a broad-based services thing. Maybe they change that in the future, but I think that's just among traditional CROs that are out there. I think I take antibody development ability. Okay, I think on the antibody binding side, you have a lot of players, but when it comes to develop ability, like those assays are kind of tough to do at high throughput, and honestly, with the customers that are coming to us, are coming to us because they can't get hundreds or thousands of data points in development.

Mike Reifian: Or I do think they have really proprietary good tech, but again, are largely using it for their own pipeline and not really trying to do like a broad based services thing. Maybe they change that in the future, but I think that's the just among traditional CROs that are out there. I think I take antibody development ability. Okay, I think on the antibody binding side, you have a lot of players, but when it comes to develop ability, like those assays are kind of tough to do at high throughput and honestly with the customers that are coming to us are coming to us because they can't get hundreds or thousands of data points in development. So I don't actually think we're behind there. Yeah, I don't want to name any names, but I think we all know what the existing players are. So we're talking about the same ones.

Speaker Change #110: Okay, Great and then my other one is just.

Speaker Change #110: Recognizing that anytime you do a ramp it's difficult and so you know.

Speaker Change #112: Clearly understand the difficulty of that I think I heard you guys say that 300, if I have this right 300 individuals were notified or terminated by the end of Q2.

Jason Kelly: And honestly, with the customers that are coming to us, are coming to us 'cause they can't get hundreds or thousands of data points in developability. So I, I don't, I don't actually think we're behind there.

Jason Kelly: So I don't actually think we're behind there. Yeah, I don't want to name any names, but I think we all know what the existing players are. So we're talking about the same ones.

Speaker Change #113: There might be another 150 that may be notified by mid 'twenty five I guess.

Mike Ryskin: Okay. Yeah, I don't want to name any names, but I think we all know who the, the existing players are, so we're talking about the same ones. Okay. And then on the H5N1, that was an interesting overview and, you know, something we've been following for a couple other different reasons. But just curious, you know, that proposal, the genomic analysis program, all of that, makes sense. Any, you know, any timelines we should look to? Is this just sort of like, how do you get this from theoretical to, you know, actually implemented?

Speaker Change #114: Or were you message messaging this internally.

Jason Kelly: Okay, and then on the H5N1, that was an interesting overview, and you know, something we've been following for a couple of different reasons, but just curious. You know, that proposal that you know what I'm going to ask. Program all that makes sense. Any, you know, any time on's we should look to is this just sort of like, how do you get this from theoretical to, you know, actually implemented? Yeah, so as where we are today is we're currently entering into agreements with Gary Farms for sort of H5N1 testing under that pilot. I think if those go well and we start to be able to show data coming out of that, then I think that's what opens the door to ultimately tapping either government or private sector money there.

Jason Kelly: Okay, and then on the H5N1, that was an interesting overview and you know, something we've been following for a couple of different reasons, but just curious. You know, that proposal that you know what I'm going to ask program all that makes sense. Any, you know, any time on's we should look to is this just sort of like, how do you get this from theoretical to, you know, actually implemented? Yeah, so so as where we are today is we're currently entering into agreements with Gary Farms for sort of H5N1 testing under that pilot.

Speaker Change #115: Just to keep people motivated.

Speaker Change #115: Keep people.

Speaker Change #115: You know incentivize them to keep doing good work with ginkgo.

Speaker Change #116: Yeah, and just for clarity that though that there's 150 have already been notified its just our folks have period of time, where if there's a program that's concluding or things like that that they're there for a period.

Speaker Change #116: And so that's the biggest thing that we wanted to try to do as much of that at once as we could.

Jason Kelly: Yeah. So where we are today is we're currently entering into agreements with dairy farms for sort of H5N1 testing under that pilot. I think if those go well, and we start to be able to show data coming out of that, then I think that's what opens the door to ultimately tapping either government or private sector money there. So we'll have to just see how the kind of data gen goes in the coming months.

Speaker Change #117: And then and then yeah look I mean.

Speaker Change #118: People believe in the mission again go I think we're trying to do our thing and so I think there's a lot of motivation like a pool of motivation there, but ultimately I think what will drive people is to see continued success right. So as we see ourselves.

Jason Kelly: I think if those go well and we start to be able to show data coming out of that, then I think that's what opens the door to ultimately tapping either government or private sector money there. So we'll have to just see how the kind of data that goes in the coming months. Alright, thank you. Yep.

Speaker Change #119: <unk> success and ladder as a surface building success of robotics, and we are actually delivering on our cell engineering solutions business getting closer and closer to profitability. There. Those are those are the things that are going to drive kind of momentum and you know good cultural energy I can't go that set of symbols that like you know.

Jason Kelly: So we'll have to just see how the kind of data that goes in the coming months.

Mike Ryskin: Awesome. All right, thank you.

Jason Kelly: Alright, thank you.

Mike Reifian: Yep. Thanks, Mike.

Jason Kelly: Yep.

Operator: Thanks, Mike. Next up, we have Mark Massaro at BTIG. Mark, your line is now open.

Megan LeDuc: Thanks, Mike. Next up, we have Mark Massaro at BTIG. Mark, your line is now open.

Mark Massaro: Next up, we have Mark and Sarah at BTIG. Mark, your line is now open. Great. Can you hear me? Okay. Yeah. Hey, Mark. Great. Hey guys.

Mark and Sarah: Thanks Mike. Next up, we have Mark and Sarah at BTIG. Mark, your line is now open. Great. Can you hear me? Okay. Yeah. Hey, Mark. Great. Hey guys.

Mark Massaro: Great. Can you hear me okay?

Speaker Change #119: The only way out is through so that for sure.

Jason Kelly: Yeah. Hey, Mark. Hi.

Speaker Change #120: Understood. Thank you for the clarification.

Mark Massaro: Great. Hey, guys. So my first question is on the Lab Data as a Service transition. How should we think about the potential or expected value, or maybe the economics of these types of deals, relative to some of the existing cell programs? So you have 140 active cell programs. What I'm just trying to determine is, like, is one of these LDaaS projects comparably similar to your existing cell engineering programs? Just any intel on expected value or economics, I think would be helpful.

Mark Massaro: So my first question is on the lab data as a service transition. How should we think about the potential of global or expected value, or maybe the economics of these types of deals relative to some of the existing cell programs? You have 140 active cell programs. What I'm just trying to determine is, like, is one of these LDS projects, comparably similar to your existing cell engineering programs, is any until on expected value or economics, I think would be able to. So they're much smaller in size than a typical end-to-end cell engineering program. They would also be much shorter in duration.

Mark and Sarah: So my first question is on the lab data as a service transition. How should we think about the potential of global or expected value, or maybe the economics of these types of deals relative to some of the existing cell programs. You have 140 active cell programs. What I'm just trying to determine is, like, is one of these LDS projects, comparably similar to your existing cell engineering programs, is any until on expected value or economics, I think would be able to.

Matt Larew: Thanks, Mark our last set of questions will come from Matt Larew William Blair. Your line is now open.

Mark and Sarah: So they're much smaller in size than a typical end to end cell engineering program. They would also be much shorter in duration. So the revenue would burn faster on those. And I think the idea though, is that a customer is not just buying one LDS project from Ginkgo, but they after, after buying it, getting data, they're buying more data and more data. And so that customers become. Like it couldn't very well be that the aggregate amount that's purchased would look like a larger cell engineering program Jason.

Matt Larew: Hey, Good morning can you hear me.

Matt Larew: Oh, Hello, Okay and everything.

Matt Larew: So.

Matt Larew: You are now.

Speaker Change #122: In a quarter since you've announced.

Speaker Change #122: The plan to achieve adjusted EBITDA breakeven here, but in 2006 and you've talked.

Speaker Change #123: Certainly about the roof and that's going be a piece of it.

Speaker Change #123: But you can also the composition of revenue.

Speaker Change #123: You're expecting over time is different than obviously when you. Initially went public in terms of now contemplating tools, obviously L Dash I think.

Mark Dmytruk: So they're much smaller in size than a typical end-to-end cell engineering program. They would also be much shorter in duration, so the revenue would burn faster on those. I think the idea, though, is that a customer is not just buying one LDaaS project from Ginkgo, but they, after buying it, getting data, they're buying more data and more data, and so the customers become, like, it could very well be that the aggregate amount that's purchased would look like a larger cell engineering program. Jason, do you want to-

Speaker Change #123: Newer opportunity.

Speaker Change #124: How are we thinking about the sort of what the revenue mix will look like at that at that level and maybe to that point are you expecting an ELD asset scale and your tools entry can be things that can be.

Mark Massaro: So the revenue would burn faster on those. And I think the idea, though, is that a customer is not just buying one LDS project from Ginkgo, but they, after buying it, getting data, they're buying more data and more data. And so that customers become. Like it couldn't very well be that the aggregate amount that's purchased would look like a larger cell engineering program, Jason. Yeah, I think that covers. I think we're a little bit early and I market to know, but I would say that just is faster to close last total dollars, shorter period of time.

Speaker Change #124: Margin accretive to perhaps the the legacy cell engineering business at scale.

Speaker Change #124: Yes.

Speaker Change #125: Very good questions. So I think we will see on the tool side like I said earlier like the particularly in the next the second half of this year, we're going to be turning over a bunch of cars there to know how well that's going right and if we see Paul and Youll see us March behind that and then absolutely I wouldn't expect to have that obviously would be then a big contributor.

Mark and Sarah: Yeah, I think that covers I think we're a little bit early and I market to know, but I would say that just is faster to close last total dollars, shorter period of time. And so each one, you shouldn't give it like it's the same as a. Cell engineering solutions or just early, so I'm actually hopeful we end up having lots more of these LDS than we would be able to close of selling during solutions deals.

Jason Kelly: Yeah, no, I think that covers it. I think we're a little bit early in the market to know, but I would say the gist is faster to close, less total dollars, shorter period of time. And so you'll-- each one, you shouldn't think of it like it's the same as a Cell Engineering solutions. We're just early, so I'm actually hopeful we end up having lots more of these LDaaS than we would be able to close of Cell Engineering solutions deals. And it pretty much has to be that way for, for this business to work. So it-- they won't end up being apples to apples. The, the solutions deals are great, they just, they're just-- they take a long time to close, you know? Like, they're really... Well, each one is like a research partnership, right?

Speaker Change #124: Peter we don't want to have that be a requirement for us to get to profitability right and so if those weren't hitting at all then I think you'd make different decisions about what you're investing in your booth pare back how much you're investing in those things, but ultimately the solutions business.

Mark Massaro: And so each one, you shouldn't give it like it's the same as a. Cell engineering solutions or just early, so I'm actually hopeful we end up having lots more of these LDS than we would be able to close of selling during solutions deals. It pretty much has to be that way for. For this business to work.

Mark and Sarah: It pretty much has to be that way for. For this business to work. So they won't end up being apples apples. The solutions deals are great. They just. They're just they take a long time to close, you know, like they're really I'm where each one is like a research partnership, right. Whereas the LDS being much more transactional and I mentioned a bit on the call, but we're finding. We'll likely engage through procurement if we're dealing with a larger company there, so it'll just be something people are like buying off the rack. Okay, great.

Speaker Change #126: We believe we could scale up ultimately to a profitable ginkgo on that it's just a matter of cutting and right sizing and making sure. We do it right, but yeah, I think the tools up and eat right like it's it's a proven platform we have used it for hundreds of projects and.

Mark Massaro: So they won't end up being apples to apples. The solutions deals are great. They just. They're just they take a long time to close, you know, like they're really I'm where each one is like a research partnership, right. Whereas the LDS being much more transactional, and I mentioned a bit on the call, but we're finding. We'll likely engage through procurement if we're dealing with a larger company there, so it'll just be something people are like buying off the rack.

Jason Kelly: Whereas the LDaaS will be much more transactional. And I mentioned this a bit on the call, but we're finding we'll likely engage through procurement if we're dealing with a larger company there. So it'll just be something people are, like, buying off the rack.

Speaker Change #126: But frankly I'm pretty excited to get that democratize on out in more people's hands right.

Speaker Change #126: I'm I'm optimistic, we'll see that but we don't want a hostile work.

Mark Massaro: Okay, great. And then my other one is just no recognizing that anytime you do a risk, it's difficult. And so, you know, I completely understand the difficulty of that. I think I heard you guys say that 300. If I have this right, 300 individuals were notified or terminated by the end of Q2. I think there might be another 150 that may be notified by mid 25. I guess.

Mark Massaro: Okay, great. And then my other one is just, you know, recognizing that any time you do a RIF, it's difficult. And so, you know, I completely understand the difficulty of that. I think I heard you guys say that 300, if I have this right, 300 individuals were notified or terminated by the end of Q2. I think there might be another 150 that may be notified by mid-2025. I guess, how are you messaging this internally, mainly just to keep people motivated and keep people, you know, incentivized to keep doing good work for Ginkgo?

Jason Kelly: And then my other one is just no recognizing that anytime you do a risk, it's difficult. And so, you know, I completely understand the difficulty of that. I think I heard you guys say that 300. If I have this right 300 individuals were notified or terminated by the end of Q2. I think there might be another 150 that may be notified by mid 25. I guess. How are you messaging messaging this internally mainly just to keep people motivated and keep people, you know, incentivize to keep doing good work.

Speaker Change #126: Yeah, No I agree I think it'd be linked in to see what.

Speaker Change #127: Looks like there.

Speaker Change #127: Is that a role like like.

Speaker Change #127: Another thing I think it goes been good at over the years and obviously like.

Speaker Change #128: Doing the restructuring is another example of this is like the mission stays back. So we Wanna make biology is easier to engineer right like that as I promised you that that is the goal you know that if that is the mission of my life and a bunch of the folks, particularly early folks and longtime committed folks that ginkgo, how we go about doing that.

Jason Kelly: How are you messaging messaging this internally, mainly just to keep people motivated and keep people, you know, incentivized to keep doing good work. Yeah, and just for clarity, those additional 150 have already been notified. It's just folks have periods of time where, if there's a program that's concluding or things like that, that they're there for a period. And so that's the biggest thing that we wanted to try to do as much of that at once as we could. And then, and then, yeah, look, I mean, I think people believe in the mission of Ginkgo. I think we're trying to do a hard thing.

Speaker Change #129: It depends what we learned in the market right. It depends what we learn on the technology side right. Both ends of that are changing all the time and so I think we are still excellent.

Jason Kelly: Yeah, and just for clarity, those additional 150 have already been notified. It's just folks have periods of time where if there's a program that's concluding or things like that, that they're there for a period. And so that's the biggest thing that we wanted to try to do as much of that at once as we could. And then and then yeah, look, I mean, I think people believe in the mission of Ginkgo, I think we're trying to do a hard thing.

Jason Kelly: Yeah, and just for clarity, those additional 150 have already been notified.

Speaker Change #130: Excellent position in the market to pursue that we have a great cash position, we have ridiculous technical talent over the last couple of years, we rolled up a lot of the core technology in the industry. So that we have the best technology base. So if you believe that you can fundamentally change how genetic engineering is done I think ingo still your best and we will remain flexible.

Mark Massaro: Okay.

Jason Kelly: It's just folks have periods of time where if there's a program that's concluding or things like that, that they're there for a period. And so that's the biggest thing, that we wanted to try to do as much of that at once as we could. And then, yeah, look, I mean, I think people believe in the mission of Ginkgo. I think we're trying to do a hard thing. And so I think there's a lot of motivation, like a pool of motivation there. But ultimately, I think what will drive people is to see continued success, right?

Jason Kelly: And so I think there's a lot of motivation, like a pool of motivation there, but ultimately, I think what will drive people is to see continued success. Right. So we see ourselves, fielding success in and lab days of service, building success robotics, as we are actually delivering on our self engineering solutions business, getting closer and closer to profitability there. Those are the things that are going to drive kind of momentum and good cultural energy. I can't go; that's as simple as that. Like, you know, the only way out is through, for sure understood.

Jason Kelly: And so I think there's a lot of motivation, like a pool of motivation there, but ultimately, I think what we'll drive people is to see continued success. Right. So as we see ourselves, fielding success in and lab days of service, building success robotics, as we are actually delivering on our self engineering solutions business, getting closer and closer to profitability there, those are the things that are going to drive kind of momentum and good cultural energy. I can't go that's as simple as that, like, you know, the only way out is through for sure understood. Thank you for the clarification. Yep.

Speaker Change #130: Where are the best ways to do that.

Speaker Change #130: Yes.

Speaker Change #130: My next question, which is really clearing sort of.

Jason Kelly: So as we see ourselves building success in lab data and service, building success in robotics, as we are actually delivering on our cell engineering solutions business, getting closer and closer to profitability there, those are the things that are going to drive kind of momentum and, you know, good cultural energy at Ginkgo. That's it. As simple as that. Like, you know, the only way out is through, and that's for sure.

Speaker Change #130: Just to add scale and.

Speaker Change #131: And whatever kind of program format that takes until I guess, if I think back a couple of years ago. A barrier initially was educating customers both from a technical offering but also legal structure potential downstream value perspective.

Speaker Change #131: Just as you think about going forward. After you added programs this quarter with UBS and Youre going to continue to but with an emphasis on scale, how do you kind of balance.

Mark Massaro: Understood. Thank you for the clarification.

Mark Massaro: Thank you for the clarification. Yep.

Jason Kelly: Yep.

Matthew Larew: Thanks, Mark. Our last set of questions will come from Matt LaRue at William Blair. Matt, your line is now open. Hey, good morning. Can you hear me?

Matthew Larew: Thanks Mark, our last set of questions will come from Matt LaRue at William Blair Matt, your line is now open. Hey, good morning, can you hear me? Hello, hello, okay, I never knew you. So, you know, you're now in a quarter, since you're not sort of the, the plan to achieve just an even a break getting here, but in 26, you've talked. Certainly about the riff, and that's going to be a piece of it.

Operator: ... Thanks, Mark. Our last set of questions will come from Matt Larew at William Blair. Matt, your line is now open.

Megan LeDuc: ... Thanks, Mark. Our last set of questions will come from Matt Larew at William Blair. Matt, your line is now open.

Speaker Change #132: Which where you pick your battles to some extent in your battle and your customers, but where where that is really important to you versus just added scale and the new customer relationships.

Matthew Larew: But you also be the composition of revenue of it, you know, you're expecting over time is different than obviously when you initially went public in terms of now contemplating tools, obviously, L that I think, you know, being a newer opportunity. Just how are you thinking about the sort of what the revenue mix will look like at that, at that level, and maybe to that point, are you expecting L bass at scale and your tools entry to be things that can be, you know, margin of career to perhaps the legacy.

Matt Larew: Hey, good morning. Can you hear me? Or afternoon.

Matthew Larew: Hello, hello. Okay, I never knew you. So, you know, you're now in a quarter, since you're not sort of the, the plan to achieve just an even a break getting here, but in 26, you've talked. Certainly about the riff, and that's going to be a piece of it. But you also be the composition of revenue of it, you know, you're expecting over time is different than obviously when you initially went public in terms of now contemplating tools, obviously, L that I think, you know, being a newer opportunity. Just how are you thinking about the sort of what the revenue mix will look like at that, at that level, and maybe to that point, are you expecting L bass at scale and your tools entry to be things that can be, you know, margin of career to perhaps the legacy.

Jason Kelly: Yeah, I can.

Matt Larew: Oh, hello. Okay, Edward, it's you. So, you know, you're now at a quarter since you've announced sort of the plan to achieve adjusted EBITDA breakeven here by the end of 2026. You've talked certainly about the RIF, and that's going to be a piece of it. But, you know, also the composition of revenue that, you know, you're expecting over time is different than obviously when you initially went public in terms of now contemplating tools, obviously, LDaaS, I think, you know, being a newer opportunity. Just how are you thinking about the sort of what the revenue mix will look like at that level?

Speaker Change #133: Yeah. So a couple of comments on that I think for further so what are they so I talked about on the last call, but the two points of friction with customers or our reuse of intellectual property on the foreground IP like the work we do that they are paying us to do okay, and I was thinking of getting a right to reuse some of that.

Speaker Change #133: And then the second area of friction can be around sort of royalties and milestones on commercial success of the product. What we've found as we've gone back to customers and offered to kind of turn those knobs is that the <unk> is a real point of friction and honestly that when it comes to a solutions deal where we're doing a complex project over a long period of time, putting in a lot of ginkgo scientific effort in Te.

Matt Larew: Maybe to that point, are you expecting LDaaS at scale and your tools entry to be things that can be, you know, margin accretive to perhaps the legacy Cell Engineering business at scale?

Speaker Change #133: <unk> technical risk the.

Speaker Change #133: The downstream value here is not as big of an issue right because.

Speaker Change #134: They are also concerned about whether the research will work right like biotech is they call. It research for a reason right.

Jason Kelly: Yes. Very good questions. So, I think we will see on the tool side, like I said earlier, like the particularly in the second half of this year, we're going to be turning over a bunch of cards there to know how well that's going, right? And if we see pull, you know, you'll see us march behind that, and then absolutely, I would expect to have that obviously be then a big contributor. We don't want to have that be a requirement for us to get to profitability, right? And so if those weren't hitting at all, then I think you'd make different decisions about what you're investing in. You would, like, pare back how much you're investing in those things.

Matthew Larew: Yes, very good questions. So I think we will see on the tools side, like I said earlier, like the, probably in the next, the second half of this year, we're going to be turning over a bunch of cards there to know how well that's going, right? And if we see pull and, you know, you'll see us march behind that, and then absolutely I would expect to have that obviously be done a big contributor. We don't want to have that be a requirement for us to get to profitability, right? And so if those weren't hitting at all, then I think you'd make different decisions about what you're investing in. You move like, pair back, how much you're investing in those things.

Speaker Change #135: Sometimes it doesn't work and so when it does work there they were pretty happy to share the upside right. So I do think that's like the correct pricing strategy for solution has to include downstream value. So that's why I did want to point out that yes, we signed more deals with it and we'll keep doing that I think it's great.

Speaker Change #136: <unk> occasionally on the total amount of milestones we have tons of potential milestone payments in the future. That's all very exciting it takes a while to get to it in biotech, but that sort of upside potential is really nice to have in the solutions business would you keep signing it up.

Matthew Larew: We don't want to have that be a requirement for us to get to profitability, right? And so if those weren't hitting at all, then I think you'd make different decisions about what you're investing in, you move like, pair back, how much you're investing in those things. But ultimately, the solutions business, we believe we could scale up ultimately to a profitable ganko on that. It's just a matter of, you know, cutting and right sizing and making sure we do it right.

Jason Kelly: But ultimately, the solutions business, we believe we could scale up ultimately to a profitable ganko on that. It's just a matter of, you know, cutting and right sizing and making sure we do it right. But I'm, you know, I think the tool stuff is neat, right? Like it's the proven platform we have used it for hundreds of projects, and frankly, I'm pretty excited to get that democratized and out in more people's hands, right? So I'm optimistic we'll see that, but we don't want to have to have that work. You know, a good thing of people, you shouldn't just see what have to take looks like there.

Jason Kelly: But ultimately, the solutions business, we believe we could scale up ultimately to a profitable Ginkgo on that. It's just a matter of, you know, cutting, right-sizing, and making sure we do it right. But I'm, you know, I think the tool stuff is neat, right? Like, it's a proven platform. We have used it for hundreds of projects, and frankly, I'm pretty excited to get that democratized and out in more people's hands, right? So I'm optimistic we'll see that, but we don't want to have to have that work.

The volume problem, there isn't really about that it's just about how much willingness there is to fully outsource a research project math right like that's something that many companies considered a thing they need to do themselves right and so that that's where I do think we have a much better opportunity, we don't necessarily need to read.

Matthew Larew: But I'm, you know, I think the tool stuff is neat, right? Like it's the proven platform we have used it for hundreds of projects and frankly, I'm pretty excited to get that democratized and out in more people's hands, right? So I'm optimistic we'll see that, but we don't want to have to have that work. You know, a good thing of people, you shouldn't just see what have to take looks like there.

Speaker Change #137: <unk> I think we can focus instead, that's why I mentioned, the AI sort of like first customer set for <unk>. We can focus on the niche of biotech customers that believe in big data.

Matt Larew: Yeah, no, I agree. I think it'll be interesting to see what, what uptake looks like there. Just in terms of,

Jason Kelly: Just to turn it around and roll, you know, like another thing I think it goes been good at over the years and obviously like, you know, doing the restructuring is another example of this is, you know, like the mission states fix, we want to make biology easier to engineer, right? Like that is I promise you the goal, you know, that is that is the mission of my life and a bunch of the folks, particularly early folks and longtime committed folks at ganko. How we go about doing that, you know, it depends what we learn in the market, right?

Jason Kelly: Just to turn it around and roll, you know, like another thing I think it goes been good at over the years and obviously like, you know, doing the restructuring is another example of this is, you know, like the mission states fix, we want to make biology easier to engineer, right? Like that is I promise you the goal, you know, that is that is the mission of my life and a bunch of the folks, particularly early folks and longtime committed folks at ganko how we go about doing that, you know, it depends what we learn in the market, right?

Jason Kelly: I think on a roll, you know, like, another thing I think Ginkgo's been good at over the years, and obviously, like, you know, doing the restructuring is another example of this, is, you know, like, the mission stays fixed. We want to make biology easier to engineer, right? Like, that is, I promise you, the, that is the goal. You know, that is, that is the mission of my life, and a bunch of the folks, particularly early folks and longtime committed folks at Ginkgo. How we go about doing that, you know, it depends what we learn in the market, right? It depends what we learn on the technology side, right? Both ends of that are changing all the time. And so I think we are still excellent, you know, we have an excellent position in the market to pursue that.

Speaker Change #138: And just just give them every tool they need right because ginkgo has believed in big data generation for the last 10 years and so let me tell you we have built out amazing tools for our scientists again at the DNA construct design level like the ability to build large pieces to build many pieces pool test sorry.

Speaker Change #139: Like Barcoding and pooled analysis.

Speaker Change #140: All the automation flexible automation those are all like really great tools. If you believe in generating a huge amount of data to do the work of genetic engineering and honestly if you don't believe in that.

Jason Kelly: It depends what we learn on the technology side, right? Both ends of that are changing all the time. And so I think we are still excellent, you know, we have an excellent position in the market to pursue that. You know, we have a great cast position. We have a ridiculous technical talent over the last couple of years; we rolled up a lot of the core technology in the industry. So I think we have the best technology base. So if you believe that you can fundamentally change how genetic engineering is done, I think ganko still your best and we will remain flexible to where the best way is to do that.

Jason Kelly: It depends what we learn on the technology side, right? Both ends of that are changing all the time. And so I think we are still excellent, you know, we have an excellent position in the market to pursue that, you know, we have a great cast position. We have a ridiculous technical talent over the last couple of years, we rolled up a lot of the core technology in the industry. So I think we have the best technology base. So if you believe that you can fundamentally change how genetic engineering is done, I think ganko still your best and we will remain flexible to where the best way is to do that.

Jason Kelly: And so I think we are still excellent, you know, we have an excellent position in the market to pursue that.

Speaker Change #141: Your benches sitting right there on the thermo catalogs on the shelf like go ahead and get to work you're fine I'm not going to try to fight that right now I'm gonna I'm going to talk to the to the people that do believe in it but our underserved on the tool side in terms of large data generation and I'm going to just I'm going to I'm going to nail that niche and then we're going to grow with it.

Jason Kelly: You know, we have a great cash position. We have ridiculous technical talent. Over the last couple of years, we rolled up a lot of the core technology in the industry, so I think we have the best technology base. So if you believe that you can fundamentally change how genetic engineering is done, I think Ginkgo is still your bet, and we will remain flexible to where the best way is to do that.

Okay, great. Thanks, Jason.

Speaker Change #142: It's just going to chime in on your points about balance and scale. The other thing I would add is that we do have a.

Matt Larew: Yes, and it goes directly, I think, to my next question, which is clearly sort of an emphasis to add scale, right? And whatever kind of program format that takes. And so again, if I think back a couple of years ago, obviously, a barrier initially was educating customers-

Jason Kelly: I think my next question, which is clearly sort of an emphasis to add scale, and whatever kind of program format that takes. And so again, if I think back a couple of years ago, obviously a barrier initially was educating customers, both from a technical offering, but also legal structure, potential downstream value perspective. So just as you think about going forward, after you added programs this quarter with DVS and you're going to continue to, but with an emphasis on scale, how do you kind of balance. Yeah, you know, which where you pick your battles to some extent in your battle and your customers, you know, but where that is really important to versus, you know, just adding scale and, you know, customer relationships, you know, that kind of.

Speaker Change #143: We're more focused on the upfront sort of Kashi economics on a deal just relatively speaking and so that's.

Speaker Change #144: That's obviously you can grow here by toggling that and we did that in the past, but we got.

Jason Kelly: Yeah

Matt Larew: ... both from a technical offering, but also legal structure, potential downstream value perspective. So just as you think about going forward, after you added programs this quarter with DVS, and you're going to continue to, but with an emphasis on scale, how do you kind of balance-

Speaker Change #145: <unk> got misaligned with our cost structure and revenue so you will see us.

Speaker Change #145: We will be thinking a lot about the nearer term cash kind of service fee economics.

Jason Kelly: Yeah

Matt Larew: ... you know, which, where you pick your battles to some extent, you're not battling your customers, you know, but, but where, where that is really important to you-

Jason Kelly: Yeah, you know, which where you pick your battles to some extent in your battle and your customers, you know, but where that is really important to versus, you know, just adding scale and, you know, customer relationships, you know, that kind of. Yeah, yeah, so a couple comments on that I think for for the so what one of the so I talked about the last call, but the two points of friction with customers are our reuse of intellectual property on the foreground IP, like the work we do that they're paying us to do.

Speaker Change #145: Before entering into a new contract with the customer.

Jason Kelly: Got it

Matt Larew: ... versus, you know, just adding scale and, you know, new customer relationships, you know, that kind of thing.

Margaret: Okay understood. Thanks Margaret.

Margaret: Thanks, Matt I'm not seeing any other questions in the queue. So I'll hand, it over to Jason for some closing thoughts.

Jason Kelly: Yeah, yeah, so a couple comments on that. I think for the, so I talked about the last call, but the two points of friction with customers are our reuse of intellectual property on the foreground IP, like the work we do that they're paying us to do. Okay, I'm asking you getting a right to reuse some of that, and then the second area of friction can be around sort of royalties and milestones on commercial success of the product. What we found as we've gone back to customers and offered to kind of turn those knobs is that the IP one is a real point of friction, and honestly, that when it comes to a solutions deal where we're doing a complex project over a long period of time, putting in a lot of ginkgo scientific effort and taking technical risk.

Jason Kelly: Okay, I'm asking you getting a right to reuse some of that and then the second area of friction can be around sort of royalties and milestones on commercial success of the product. What we found as we've gone back to customers and offered to kind of turn those knobs is that the IP one is a real point of friction and honestly that when it comes to a solutions deal where we're doing a complex project over a long period of time, putting in a lot of ginkgo scientific effort and taking technical risk.

Jason Kelly: Yeah. So, a couple comments on that. I think for the—so one of the... So I talked about this on the last call, but the two points of friction with customers are our reuse of intellectual property on the foreground IP, like the work we do that they're paying us to do, okay? And us, Ginkgo, getting a right to reuse some of that. And then the second area of friction can be around sort of royalties and milestones on commercial success of the product. What we found as we've gone back to customers and offered to kind of turn those knobs, is that the IP one is a real point of friction.

Speaker Change #147: Yes, so again I'll say, it again tough wherever ginkgo.

Speaker Change #148: I want to say, thanks again to the departed employees.

Jason: So we had to let go as part of the risk I think we are doing the right things.

Jason: Kind of create a solid base here and can go and build on it and we appreciate all the support of those listening in and our mission to make biology easier to engineer. So thanks again.

Jason Kelly: And honestly, that when it comes to a solutions deal, where we're doing a complex project over a long period of time, putting in a lot of Ginkgo scientific effort and taking technical risk, the downstream value share is not as big of an issue, right? Because they, they're also concerned about whether the research will work, right? Like, biotech is, they call it research for a reason, right? Like, you know, like, it, it sometimes doesn't work. And so when it does work, they, they, they're pretty happy to share the upside, right? So I do think that's, like, the correct pricing strategy for solutions, is to include downstream value share. That's why I did want to point out that, yes, we've signed more deals with it, and we'll keep doing that. I think it's great.

Jason Kelly: The downstream value here is not as big of an issue, right? Because they're also concerned about whether the research will work, right? Like biotech, is they call it research. For a reason right like you know like it sometimes doesn't work and so when it does work that they're pretty happy to share the upside right. So I do think that's like the correct pricing strategy for solutions is to include downstream value share. That's why I did want to point out that yes we signed more deals with it and we'll keep doing that. I think it's great you know yet we report occasionally on the total amount of milestones. We have tons of potential milestone payments in the future that's all very exciting.

Jason Kelly: The downstream value here is not as big of an issue right because they're also concerned about whether the research will work right like biotech is they call it research. For a reason right like you know like it sometimes doesn't work and so when it does work that they're pretty happy to share the upside right so I do think that's like the correct pricing strategy for solutions is to include downstream value share that's why I did want to point out that yes we signed more deals with it and we'll keep doing that I think it's great you know yet we report occasionally on the total amount of milestones we have tons of potential milestone payments in the future that's all very exciting.

Jason Kelly: You know, we have, we report occasionally on the total amount of milestones. We have tons of potential milestone payments in the future. That's all very exciting. It takes a while to get to it in biotech, but, but that sort of upside, you know, potential is really nice to have in the solutions business. We should keep signing it up. The volume problem there isn't really about that. It's just about how much willingness there is to fully outsource a research project, Matt, right? Like, that's something that many companies consider a thing they need to do themselves, right? And so that, that's where I, I do think we have a much better opportunity. We don't necessarily need to re-educate. I think we can focus instead, that's why I mentioned the AI, sort of like, first customer set for LDaaS.

Jason Kelly: It takes a while to get to it in biotech, but that sort of upside that you know potential is really nice to have in the solutions business. We should keep signing it up. The volume problem there isn't really about that; it's just about how much willingness there is to fully outsource a research project that, right? Like, that's something that many companies considered a thing they need to do themselves, right? And so that, that's where I do think we have a much better opportunity. We don't necessarily need to reeducate. I think we can focus instead that's why I mentioned the AI sort of like first customer set for LDAS we can focus on the niche of biotech customers that believe in big data and just just give them every tool they need right because Ginkgo has believed in big data generation for the last 10 years and so let me tell you we have built out amazing tools for our scientists again at the DNA construct design level like the ability to build large pieces to build many pieces pool test you know sorry like bar coding and and tools analysis all the automation flexed automation those are all like really great tools if you believe in generating a huge amount of data to do the work of genetic engineering.

Jason Kelly: It takes a while to get to it in biotech but but that sort of upside that you know potential is really nice to have in the solutions business we should keep signing it up. The volume problem there isn't really about that it's just about how much willingness there is to fully outsource a research project that right like that's something that many companies considered a thing they need to do themselves right and so that that's where I do think we have a much better opportunity we don't necessarily need to reeducate.

Jason Kelly: We don't necessarily need to re-educate. I think we can focus instead, that's why I mentioned the AI, sort of like, first customer set for LDaaS.

Jason Kelly: I think we can focus instead that's why I mentioned the AI sort of like first customer set for LDAS we can focus on the niche of biotech customers that believe in big data and just just give them every tool they need right because ginkgo has believed in big data generation for the last 10 years and so let me tell you we have built out amazing tools for our scientists again at the DNA construct design level like the ability to build large pieces to build many pieces pool test you know sorry like bar coding and and tools analysis all the automation flexed automation those are all like really great tools if you believe in generating a huge amount of data to do the work of genetic engineering. And honestly if you don't believe in that your bench is sitting right there on the thermal catalogs on the shelf like go ahead and get to work you're fine I'm not going to try to fight that right now I'm going to talk to the people that do believe in it but are underserved on the tool side in terms of large data generation and I'm going to just I'm going to I'm going to nail that niche and then we're going to grow it. Okay, great. Thank you.

Jason Kelly: We can focus on the niche of biotech customers that believe in big data, and just, just give them every tool they need, right? Because Ginkgo has believed in big data generation for the last 10 years. And so let me tell you, we have built out amazing tools for our scientists, again, at the DNA construct design level. Like, the ability to build large pieces, to build many pieces, tool testing, you know, like bar coding and, and tools, analysis, all the automation, flexible automation, those are all like really great tools if you believe in generating a huge amount of data to do the work of genetic engineering. And then honestly, if you don't believe in that, your bench is sitting right there, and the Thermo catalog's on the shelf. Like, go ahead and get to work. You're fine.

Jason Kelly: And honestly, if you don't believe in that, your bench is sitting right there on the thermal catalogs on the shelf. Like, go ahead and get to work; you're fine. I'm not going to try to fight that right now. I'm going to talk to the people that do believe in it but are underserved on the tool side in terms of large data generation, and I'm going to just, I'm going to nail that niche, and then we're going to grow it. Okay, great.

Jason Kelly: You're fine. I'm not going to try to fight that right now. I'm gonna talk to the people that do believe in it, but are underserved on the tool side in terms of large data generation. I'm gonna just nail that niche, and then we're going to grow with it.

Jason Kelly: I'm not going to try to fight that right now. I'm gonna talk to the people that do believe in it, but are underserved on the tool side in terms of large data generation. I'm gonna just nail that niche, and then we're going to grow with it.

Megan LeDuc: Okay, great. Thanks, Jason.

Matt Larew: Okay, great. Thanks, Jason.

Mark Massaro: Thank you. Man, I was just going to chime in on your points about balance and scale. The other thing I would add is that we do have a more focused on the upfront sort of cash economics on the deal, just relatively speaking. And so that's that. Obviously, you can grow here by toggling that, and we did that in the past, but we got misaligned with our cost structure and revenue. It's a lot. So you will see us. We will be thinking a lot about the near term cash kind of service fee economics before entering into a new contract with the customer.

Mark Massaro: Man, I was just going to chime in on your points about balance and scale. The other thing I would add is that we do have a more focused on the upfront sort of cash economics on the deal, just relatively speaking. And so that's that's that obviously you can grow here by toggling that and we did that in the past, but we got misaligned with our cost structure and revenue. It's a lot. So you will see us. We will be thinking a lot about the near term cash kind of service fee economics before entering into a new contract with the customer. Okay, understood. Thanks, Mark. Thanks, Matt.

Mark Dmytruk: Matt, I was just going to chime in on your points about balance and scale. The other thing I would add is that we do have a more focus on the upfront sort of cash economics on a deal, just relatively speaking. And so that's obviously you can grow here by toggling that, and we did that in the past, but we got misaligned with our cost structure and revenue. And so you will see us. We will be thinking a lot about the nearer-term cash kind of service fee economics before entering into a new contract with a customer.

Mark Massaro: Okay, understood. Thanks, Mark.

Megan LeDuc: Okay, understood. Thanks, Mark.

Matt Larew: Okay, understood. Thanks, Mark.

Mark Massaro: Thanks, Matt.

Operator: Thanks, Matt. I'm not seeing any other questions in the queue, so I'll hand it over to Jason for some closing thoughts.

Jason Kelly: I'm not seeing any other questions in the queue, so I'll hand it over to Jason for some closing thoughts. Yeah, so again, I'll say again, tough word for Ginkgo.

Jason Kelly: Yeah. So again, I'll say again, tough quarter for Ginkgo. I want to say thanks again to the part of employees that we had to let go as part of the RIF. I think we are doing the right things to kind of create a solid base here at Ginkgo and build on it, and we appreciate all the support of those listening in in our mission to make biology easier to engineer. So thanks again.

I want to say thanks again to the department employees that we had to let go as part of the risk. I think we are doing the right things to kind of create a solid base here at Ginkgo and build on it, and we appreciate all the support of those listening in our mission to make biology easier to engineer. So thanks again.

Jason Kelly: I want to say thanks again to the department employees that we had to let go as part of the risk. I think we are doing the right things to kind of create a solid base here at Ginkgo and build on it and we appreciate all the support of those listening in our mission to make biology easier to engineer. So thanks again.

Q2 2024 Ginkgo Bioworks Holdings Inc Earnings Call - Q&A

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