Q1 2025 Ginkgo Bioworks Holdings Inc Earnings Call

May 6, 2025

Our senior manager of communications and ownership. It's my third year here at Kimco I've spent much of that time working behind the scenes with our Investor Relations team on these earnings calls, but I'm thrilled to be joining you for the first time live on air on.

Daniel Waid Marshall: Good evening. I'm Daniel Marshall, Senior Manager of Communications and Ownership. It's my third year here at Ginkgo. I've spent much of that time working behind the scenes with our Investor Relations team on these earnings calls, but I'm thrilled to be joining you for the first time live on air. I'm joined by Jason Kelly, our Co-Founder and CEO, and Mark Dmytruk, our CFO. Thanks, as always, for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we'll 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, including our most recent 10-K.

Jason Kelley: I'm joined by Jason Kelley, our co founder and CEO and Mark Dmitry <unk> our CFO.

Jason Kelley: 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, including our most recent 10-K.

Jason Kelley: Today. In addition to updating you on the quarter results were going to provide updates on our path towards adjusted EBITDA breakeven traction with our government clients as well as new offerings and opportunities emerging for our tools businesses.

Daniel Waid Marshall: Today, in addition to updating you on the quarter results, we're going to provide updates on our path towards Adjusted EBITDA, break-even, traction with our government clients, as well as new offerings and opportunities emerging for our tools' businesses. 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, hashtag Ginkgo Results, or email investors@ginkgobioworks.com. All right, over to you, Jason.

Jason Kelley: As usual, we'll end with the Q&A session and I will take questions from analysts investors and the public you can submit those questions to us in advance via ex ash that ginkgo results or E mail investors that ginkgo virus dot com alright.

Jason Kelley: Alright over to you Jason.

Jason Kelley: Thanks, Daniel we always start off with our mission here at Ginkgo, which is to make biology easier to engineer.

Jason Kelly: Thanks, Daniel. We always start off with our mission here at Ginkgo, which is to make biology easier to engineer. Then we had three objectives. I first showed these—or close variants of these—about a year ago when we announced that we were going to be doing a major restructuring of the company. These three objectives were to reach Adjusted EBITDA break-even by the end of 2026, and importantly, doing that while maintaining a cash margin of safety. In other words, we didn't want to get in a position where we were going to need to fundraise when we didn't want to, right? We wanted to be doing that if we needed to fundraise from a position of strength, but ideally not even need to fundraise. Second, we wanted to cut costs while, importantly, serving our current customers.

Jason Kelley: And then we had three objectives and I first showed these are clothes bearing disease about a year ago, when we earn out that where you're going to be doing a major restructuring of the company and these three objectives were to reach adjusted EBITDA breakeven by the end of 2026, and importantly doing that while maintaining a cash margin of safety in other words, we didn't want to get in a position where.

Jason Kelley: We're going to need to fund raise when we didn't want to right. We wanted to be doing that if we needed to fundraise from a position of strength, but ideally not even need to fundraise.

Second we wanted to cut cost while importantly, serving our current customers we had a lot of amazing customers.

Jason Kelly: We had a lot of amazing customers: large pharmas, large ag biotechs, industrial biotechs, as well as the government. We wanted to keep serving those customers well while at the same time focusing the company. And then finally, we wanted to expand the way we sold our platform. And I'll talk more about this in the strategic section. But from not just R&D solutions where we do an end-to-end research project, but also directly as a tools business, like a traditional CRO or an equipment vendor would, these were new ways to go to market to a wider set of potential customers than we had with our solutions business. So those were our three objectives. And I'm very happy to say we made progress on all of them. But after a year, we've just made unbelievable progress on taking out costs while still serving our customers.

Jason Kelley: <unk> pharma large AG biotech industrial biotech as well as the government wanted to keep serving those customers well while at the same time focusing the company.

Jason Kelley: And then finally, we wanted to expand the way we sold our platform and I'll talk more about this in the strategic section, but from not just R&D solutions, where we do an end to end research project, but also directly as a tools business like a traditional CRO or an equipment vendor would these were new ways to go to market to a wider <unk>.

We wanted to cut cost while importantly, serving our current customers. We had a lot of amazing customers large pharma large AG biotech industrial biotech as well as the government. We wanted to keep serving those customers well while at the same time focusing the company.

Jason Kelley: Set of potential customers than we had with our solutions business. So those are our three objectives and I'm very happy to say, we made progress on all of them, but after a year. We've just made unbelievable progress on taking out costs, while still serving our customers. So.

And then finally, we wanted to expand the way we sold our platform and I'll talk more about this in the strategic section, but from not just R&D solutions, where we do an end to end research project, but also directly as a tools business like a traditional CRO or an equipment vendor would these were new ways to go to market to a wider.

Jason Kelley: I'm very happy to say, we're at $205 million reduction in our annual run rates between Q1, 'twenty 'twenty four 'twenty five you might remember.

Jason Kelly: So I'm very happy to say we're at a $205 million reduction in our annual run rate between Q1 2024 and Q1 2025. You might remember the target I had set was $200 million, I think, by Q3 or something of this year, like halfway through this year. We already beat that. We've taken actions in the first quarter that are going to improve this even further; Mark will mention. So I really think this sets us up to be in an incredibly strong position. And importantly, because we did it faster, we are at this place while still having $517 million in cash and cash equivalents on the balance sheet and no bank debt. So that, among our peers in sort of the advanced sort of platform technology space in the market today, I think, is a uniquely strong position.

Jason Kelly: So I'm very happy to say we're at a $205 million reduction in our annual run rate between Q1 2024 and Q1 2025. You might remember the target I had set was $200 million, I think, by Q3 or something of this year, like halfway through this year. We already beat that. We've taken actions in the Q1 that are going to improve this even further; Mark will mention. So I really think this sets us up to be in an incredibly strong position. And importantly, because we did it faster, we are at this place while still having $517 million in cash and cash equivalents on the balance sheet and no bank debt. So that, among our peers in sort of the advanced sort of platform technology space in the market today, I think, is a uniquely strong position.

Jason Kelley: The targeted headset was $200 million I think by Q3 or something of this year.

Set of potential customers than we had with our solutions business. So those are our three objectives and I'm very happy to say, we made progress on all of them, but after a year. We've just made unbelievable progress on taking out costs, while still serving our customers. So.

Speaker Change: Halfway through this year, we already beat that or move it and we've taken actions in the first quarter that are going to improve this even further mark mentioned.

Speaker Change: So I really think this sets us up to be an incredibly strong position and importantly, because we did it faster.

I'm very happy to say, we're at $205 million reduction in our annual run rates between Q1, 2024, <unk> 25, you might remember.

We are at this at this place, while still having $517 million in cash and cash equivalents on the balance sheets and no no no no bank debt.

The targeted headset was 200 million I think by Q3 or something of this year.

Halfway through this year, we already beat that we're moving we've taken actions in the first quarter that are going to improve this even further mark mentioned.

Speaker Change: <unk>.

That among our peers in sort of the advanced sort of platform technology space in the market today.

So I really think this sets us up to be an incredibly strong position and importantly, because we did it faster.

Speaker Change: As a uniquely strong position, but biotech on the capital market is going through a tough time right now that is challenging for the companies and it's also opportunity I would say for investors and from my standpoint, the companies that can make it out the other side of that are in a particularly strong position as its biotechnology is I think a fundamental <unk>.

Jason Kelly: Look, biotech on the capital market is going through a tough time right now. That is challenging for the companies in it. It's also opportunity, I would say, for investors. From my standpoint, the companies that can make it out the other side of that are in a particularly strong position, as since biotechnology is, I think, a fundamental industry that's not going away. So this sets us up to be in a place to do that. I want to just give my thanks to the team for what's been an incredibly difficult, challenging ton of work last year to get us to where we are. But it puts us in a very, very strong spot going forward. With that, I'm going to hand it to Mark to go over this quarter's financials.

We are at this at this place, while still having $517 million in cash and cash equivalents on the balance sheet and no no no no bank debt.

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Speaker Change: History, that's not going away and so this sets us up to be in a place to do that and I want to just.

Speaker Change: I'll give my thanks to the team for what's been an incredibly difficult challenging tunnel work last year to get us to where we are but it puts us in a very very strong spot.

Mark: Going forward, so with that I'm going to hand, it to mark to go off over this quarter's financials.

Mark: Thanks, Jason I'll start with the cell engineering business.

Mark Dmytruk: Thanks, Jason. I'll start with the Cell Engineering business. Cell Engineering revenue was $38 million in Q1 2025, up 37% compared to Q1 2024. Q1 this year included $7.5 million in non-cash revenue from a release of deferred revenue relating to the mutual termination of a customer agreement we had with BiomEdit, one of our platform ventures. Excluding this impact, Cell Engineering revenue was $31 million, up 10% compared to Q1 2024. This increase was primarily driven by strong growth with biopharma and government customers. In Q1 2025, we supported a total of 123 revenue-generating programs on the Cell Engineering platform. This represents a 32% increase in revenue-generating programs year-over-year.

Mark: Cell engineering revenue was $38 million in the first quarter of 2025 up 37% compared to the first quarter of 2020 for.

Mark: The first quarter. This year included $7 5 million in noncash revenue from a from a release of deferred revenue relating to the mutual termination of a customer agreement, we had with biome edit one of our platform ventures.

To go off over this quarter's financials.

Thanks, Jason I'll start with the cell engineering business.

<unk> this impact cell engineering revenue was $31 million up 10% compared to the first quarter of 2024. This increase was primarily driven by strong growth with Biopharma and government customers.

Cell engineering revenue was $38 million in the first quarter of 2025 up 37% compared to the first quarter of 2024.

The first quarter. This year included $7 $5 million in noncash revenue from a from a release of deferred revenue relating to the mutual termination of a customer agreement, we had with biome edit one of our platform ventures <unk>.

Mark: In the first quarter of 2025, we supported a total of 123 revenue generating programs on the cell engineering platform. This represents a 32% increase in revenue generating programs year over year.

Excluding this impact cell engineering revenue was $31 million up 10% compared to the first quarter of 2024. This increase was primarily driven by strong growth with Biopharma and government customers.

Mark: As discussed on our last earnings call. This quarter represents the first time, we are reporting the new revenue generating program metric and are no longer reporting the original program metrics.

Mark Dmytruk: As discussed on our last earnings call, this quarter represents the first time we are reporting the new revenue-generating program metric and are no longer reporting the original program metrics. As a reminder on the rationale here, the nature of programs that we take on with our customers has evolved significantly following our adjustments to commercial terms and the launch of our tools offerings in 2024. This new metric includes all programs that generated meaningful revenue in the quarter, including smaller programs that were previously reported as other contracts, and further excludes programs that did not generate meaningful revenue in the quarter, which typically would be those programs either just starting or in final stages of completion. We believe the new metric will be more useful to analysts who are using this to model revenue. We have also updated the 2024 comparables using this new metric in the appendix.

Mark: As a reminder, on the rationale here the nature of programs that we take on with our customers has evolved significantly following our adjustments to commercial terms and the launch of our tools offerings in 2024.

In the first quarter of 2025, we supported a total of 123 revenue generating programs on the cell engineering platform. This represents a 32% increase in revenue generating programs year over year.

Mark: This new metric includes all programs that generated meaningful revenue in the quarter, including smaller programs that were previously reported as other contracts.

As discussed on our last earnings call. This quarter represents the first time, we are reporting the new revenue generating program metric and are no longer reporting the original program metrics.

Mark: And further excludes programs that did not generate meaningful revenue in the quarter, which typically would be those programs either just starting or in final stages of completion.

As a reminder, on the rationale here the nature of programs that we take on with our customers has evolved significantly following our adjustments to commercial terms and the launch of our tools offerings in 2024.

Mark: We believe the new metric will be more useful to analysts who are using this to model revenue.

This new metric includes all programs that generated meaningful revenue in the quarter, including smaller programs that were previously reported as other contracts and further excludes programs that did not generate meaningful revenue in the quarter, which typically would be those programs either just starting or in final stages of completion.

Mark: We have also updated the 2024 comparable using this new metric in the appendix.

Mark: Now turning to bio security, our bio security business generated $10 million of revenue in the first quarter of 2025, and a segment gross margin of 28%.

Mark Dmytruk: Now, turning to biosecurity, our biosecurity business generated $10 million of revenue in Q1 2025 at a segment gross margin of 28%. Segment gross margin excludes stock-based compensation. Turning to the next slide, I'll provide more commentary on key items for the rest of the P&L. Now that we are almost a year into our restructuring, you can see the very substantial cost reductions and improvements in profitability that we have executed when compared to Q1 2024. As a reminder, a full reconciliation between segment operating loss, Adjusted EBITDA, and GAAP net loss can be found in the appendix. Starting with the more significant items in segment OpEx. In Q1 2025, cell engineering R&D expense decreased 41% from $82 million in Q1 2024 to $49 million in Q1 2025.

Mark: <unk> gross margin excludes stock based compensation.

We believe the new metric will be more useful to analysts who are using this to model revenue.

Mark: Turning to the next slide I'll provide more commentary on key items for the rest of the P&L now that we're almost a year into our restructuring you can see the various substantial cost reductions and improvements in profitability that we have executed when compared to the first quarter of 2024 as of.

We have also updated the 2024 comparable using this new metric in the appendix.

Now turning to bio security, our bio security business generated $10 million of revenue in the first quarter of 2025 at a segment gross margin of 28%.

Mark: Reminder, a full reconciliation between segment operating loss adjusted EBITDA and GAAP net loss can be found in the appendix.

Segment gross margin excludes stock based compensation.

Turning to the next slide I'll provide more commentary on key items for the rest of the P&L.

Mark: Starting with the more significant items in segment Opex in the first quarter of 2025 cell engineering R&D expense decreased 41% from $82 million in the first quarter of 2000 $24 million to $49 million in the first quarter of 2025.

Now that we're almost a year into our restructuring you can see the various substantial cost reductions and improvements in profitability that we have executed when compared to the first quarter of 2024.

As a reminder, a full reconciliation between segment operating loss adjusted EBITDA and GAAP net loss can be found in the appendix.

Mark: Cell engineering, G&A expense decreased 53% from $38 million in the first quarter of 2000 $24 million to $18 million in the first quarter of 2025.

Mark Dmytruk: Cell Engineering G&A expense decreased 53% from $38 million in Q1 2024 to $18 million in Q1 2025. While smaller in amount, you can also see a decrease in biosecurity operating expenses by 33% year-over-year. All these decreases were driven by our restructuring efforts. 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. Because of these non-cash and other non-recurring items, we believe Adjusted EBITDA is a more indicative measure of our profitability. We are now showing you Adjusted EBITDA at the segment level so that you can more clearly see the relative profitability of Cell Engineering and biosecurity.

Starting with the more significant items in segment Opex in the first quarter of 2025 cell engineering R&D expense decreased 41% from $82 million in the first quarter of 2000 $24 million to $49 million in the first quarter of 2025.

Mark: And while smaller in amount you can also see a decrease in bio security operating expenses by 33% year over year.

Mark: All of these decreases were driven by our restructuring efforts.

Mark: 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.

Cell engineering, G&A expense decreased 53% from $38 million in the first quarter of 2000 $24 million to $18 million in the first quarter of 2025.

Mark: Are these non cash and other nonrecurring items, we believe adjusted EBITDA is a more indicative measure of our profitability.

And while smaller in amount you can also see a decrease in bio security operating expenses by 33% year over year.

Mark: And we are now showing you adjusted EBITDA at the segment level. So that you can more clearly see the relative profitability of cell engineering and Biosecurity.

All of these decreases were driven by our restructuring efforts.

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: The significant improvement in sell engineering segment operating loss in the first quarter of 2025 compared to the comparable.

Mark Dmytruk: The significant improvement in Cell Engineering segment operating loss in Q1 2025 compared to the comparable prior year period was due to the previously discussed drivers of improved revenue and reduced operating expenses, as well as the non-cash deferred revenue release within the quarter. Biosecurity segment operating loss also improved significantly due to the primarily cost reduction efforts. Moving further down the page, you'll note that total company Adjusted EBITDA in Q1 2025 was negative $47 million, which was up from negative $117 million in Q1 2024. The principal differences between segment operating loss and total company Adjusted EBITDA in the first quarter relate to the carrying cost of excess lease space, which you can see was $12 million in Q1 this year.

Mark Dmytruk: The significant improvement in Cell Engineering segment operating loss in Q1 2025 compared to the comparable prior year period was due to the previously discussed drivers of improved revenue and reduced operating expenses, as well as the non-cash deferred revenue release within the quarter. Biosecurity segment operating loss also improved significantly due to the primarily cost reduction efforts. Moving further down the page, you'll note that total company Adjusted EBITDA in Q1 2025 was negative $47 million, which was up from negative $117 million in Q1 2024. The principal differences between segment operating loss and total company Adjusted EBITDA in the Q1 relate to the carrying cost of excess lease space, which you can see was $12 million in Q1 this year.

Because of these noncash and other nonrecurring items, we believe adjusted EBITDA is a more indicative measure of our profitability.

Mark: Prior year period was due to the previously discussed <unk>.

Mark: <unk> of improved revenue and reduced operating expenses as well as the noncash deferred revenue release within the quarter.

And we are now showing you adjusted EBITDA at the segment level. So that you can more clearly see the relative profitability of cell engineering.

Mark: By our Securities segment operating loss also improved significantly due to the primarily cost reduction efforts.

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The significant improvement, it's all engineering segment operating loss for the first.

Mark: Moving further down the page you'll note that total company adjusted EBITDA in the first quarter of 2025 was negative $47 million, which was up from negative $117 million in the first quarter of 2020 for the principal differences between segment operating loss and total company.

First quarter of 2025 compared to the Carnival.

Prior year period was due to the previously discussed drivers of improved revenue and reduced operating expenses as well as the noncash deferred revenue release within the quarter.

Securities segment operating loss also improved significantly due to the primarily cost reduction efforts.

Mark: Adjusted EBITDA in the first quarter relates to the carrying cost.

Mark: Of excess lease space, which you can see was $12 million in Q1. This year. This cost represents the base rent and other charges relating to leased space.

Moving further down the page you'll note that total company adjusted EBITDA in the first quarter of 2025 was negative $47 million, which was up from negative $117 million in the first quarter of 2020 for the principal differences between segment operating loss and total.

Mark Dmytruk: This cost represents the base rent and other charges relating to leased space, which we are not occupying, net of sublease income. We'll continue to break that out for you going forward since that is a cash operating cost that is not related to driving revenue right now and can be potentially mitigated through subleasing. Finally, I'll just make one additional comment relating to cash burn in the quarter. Cash burn in Q1 2025 was $58 million, down from $104 million in Q1 2024. This significant decrease in cash burn was a result of the restructuring. We expect to further increase the cash burn run rate significantly from this level by Q4 2025, though we expect some lumpiness in the progression during the year due to timing of working capital.

Mark: We are not occupying net of sublease income.

Mark: We will continue to break that out for you going forward since that is the cash operating cost that is not related to driving revenue right now and it can be potentially mitigated through sub leasing.

Company adjusted EBITDA in the first quarter relates to the carrying cost of.

Mark: And finally, I will just make one additional comment relating to cash burn in the quarter cash burn in the first quarter of 2025 was $58 million down from $104 million in the first quarter of 2024.

Of excess lease space, which you can see was $12 million in Q1 this year.

This cost represents the base rent and other charges relating to leased space.

We are not occupying net of sublease income.

Mark: This significant decrease in cash burn was a result of the restructuring.

We will continue to break that out for you going forward since that is a cash operating cost that is not related to driving revenue right now and can be potentially mitigated through sub leasing.

Mark: We expect to further reduce our cash burn run rate, it's significantly from this level by the fourth quarter of 2025. So we expect some lumpiness in the progression during the year due to timing of working capital.

And finally, I will just make one additional comment relating to cash burn in the quarter cash burn in the first quarter of 2025 was $58 million.

Mark: Okay.

Mark: In terms of outlook for the full year, we previously issued guidance for total revenue of $160 million to $180 million.

Down from $104 million in the first quarter of 2024.

Mark Dmytruk: In terms of outlook for the full year, we previously issued guidance for total revenue of $160 to 180 million, cell engineering services revenue of $110 to 130 million, and biosecurity revenue of at least $50 million. We update this previously issued guidance solely to reflect the impact of the previously mentioned $7.5 million non-cash deferred revenue release in Q1. With this in mind, we now expect our total revenue to be $167 to 187 million, cell engineering revenue to be $117 to 137 million, and biosecurity to remain the same of at least $50 million. In conclusion, we're pleased with the substantial improvements in cash burn and profitability when looking back over the past year. In Q1, we continued to execute against our core objectives while navigating significant uncertainty in the macro environment. With that, I will hand it back over to you, Jason.

This significant decrease in cash burn was a result of the restructuring.

Mark: Sell engineering services revenue of $110 million to $130 million in bio security revenue of at least $50 million.

We expect to further reduce the cash burn run rate, it's significantly from this level by the fourth quarter of 2025. So we expect some lumpiness in the progression during the year due to timing of working capital.

Mark: We update this previously issued guidance solely to reflect the impact of the previously mentioned $7 5 million dollar noncash deferred revenue release in the first quarter.

Okay.

In terms of outlook for the full year, we previously issued guidance for total revenue of $160 million to $180 million.

Mark: With this in mind, we now expect our total revenue to be $167 million to $187 million.

Engineering services revenue of $110 million to $130 million in bio security revenue of at least $50 million.

Mark: Cell engineering revenues to be $117 million to $137 million and bio security to remain the same of at least $50 million.

We update this previously issued guidance solely to reflect the impact of the previously mentioned $7 5 million dollar noncash deferred revenue release in the first quarter.

In conclusion, we're pleased with the substantial improvements in cash burn in profitability when looking back over the past year.

With this in mind, we now expect our total revenue to be $167 million to $187 million cell engineering revenues to be $117 million to $137 million and bio security to remain the same of at least $50 million.

Mark: In the first quarter, we continued to execute against our core objectives, while navigating significant uncertainty in the macro environment.

And with that I will hand, it back over to you Jason.

Speaker Change: Thanks, Mark so in the strategic section, we're going to cover three topics today first I want to touch again on our continued restructuring efforts and how all that's going on there.

Jason Kelly: Thanks, Mark. So in the strategic section, we're going to cover three topics today. The first, I want to touch again on our continued restructuring efforts and how well that's going on the cash takeout side, and our path to sort of EBITDA break-even by the end of next year. Second, there's been a lot of changes in the administration and the US government here in terms of sort of approach to research spending and biosecurity and things like that. And I want to just highlight that I think biotech remains a critical emerging tech in the US and, again, goes well-positioned for it. And then third topic, I want to talk about our tools businesses, data points, and automation. This has been our big motion over the last year is expanding into the tool space, and that's going really well. And I want to give an update on that.

In conclusion, we're pleased with the substantial improvements in cash burn in profitability when looking back over the past year.

Mark: Cash take outside in our path to sort of EBITDA breakeven by the end of next year.

In the first quarter, we continued to execute against our core objectives, while navigating significant uncertainty in the macro environment.

Mark: Second there's been a lot of changes in the administration and the U S government here in terms of sort of approach to it.

And with that I will hand, it back over to you Jason.

Mark: Our research spending in bio security and things like that and I want to just highlight that I think biotech remains a critical emerging tech in the U S and that ginkgo is well positioned for it.

Thanks Mark.

In the strategic section, we're going to cover three topics today first I want to touch again on our continued restructuring efforts and how all that's going on there are cash take outside in our path to sort of EBITDA breakeven by the end of next year.

Mark: And then third topic I wanted to talk about our tools businesses are data points and automation. This is Ben are our big motion over the last year is expanding in the tool space and that's going really well I don't want to give an update on that.

There's been a lot of changes in the administration and the U S. Government here in terms of sort of approach that our research spending in bio security and things like that and I want to just highlight that I think biotech remains a critical emerging tech in the U S and I think is well positioned for it.

Mark: Okay. So first.

Jason Kelly: Okay. So first, I talked earlier. I'm really happy to have that highlighted in the middle, that $205 million of annualized run rate cost takeout that we've achieved in the year since we announced the restructuring. Our goal, of course, is to get to Adjusted EBITDA break-even in 2026. And so I really like this chart on the left. You can see back in Q1 2024 where we were on the cash expenses and total revenues. And what we want to do is just shrink that gray bar and grow the green bar and eventually get those to be the same size. And so we are pushing at that. That is sort of the relentless focus here on the team. Again, I'm really happy to see the progress. It's going the right direction.

Mark: I talked earlier I'm really happy to have that highlighted in the middle of that $205 million of annualized run rate cost takeout that we've achieved in the year.

Mark: Since we announced the restructuring.

Mark: Our goal of course is to get to adjusted EBITDA breakeven in 2026, I'm. So I really like this chart on the left you can see back in Q1 2024, where we were on the cash expenses and took revenues and when we want to do is just shrink that gray bar and grow the green bar and eventually get those to be the same size and so we are pushing it at that.

And then third topic I wanted to talk about our tools businesses data points in automation. This is Ben are our big motion over the last year is expanding in the tool space, that's going really well I don't want to give an update on that.

Okay. So first.

I talked earlier I'm really happy to have that highlighted in the middle of that $205 million of annualized run rate cost takeout that we've achieved in the year since.

Mark: That is sort of the relentless focus here on the team.

Since we announced the restructuring.

Mark: Again, I'm really happy to see the progress it's going the right direction. We already have made changes in the first quarter that you thought you'll see reflected in the <unk>.

Our goal of course is to get to adjusted EBITDA breakeven in 2026, I'm. So I really like this chart on the left you can see back in Q1 2024, where we were on the cash expenses and took revenues I mean, we wanted to do is just shrink that gray bar and grow the green bar and eventually get those to be the same size and so we are pushing out that.

Jason Kelly: We already have made changes in the first quarter that you'll see reflected in the coming quarters to continue to take costs out. And hopefully, our efforts in the tool space will keep growing sales as well. I will mention, if you look and see the segment breakout here in Biosecurity, again, Q1 2024 or sorry, Q4 2024 to Q1 2025, we're at $5 million on a run-rate burn. That's one where we're hoping to really get Biosecurity to break-even this year. And then Cell Engineering, you can see the enormous progress we've made since Q1 of 2024 last year. But I need to continue squeezing on that in order to reach Adjusted EBITDA break-even next year. So I think we've got a path to it. It will be a serious amount of work. But I've been extraordinarily impressed.

Jason Kelly: We already have made changes in the Q1 that you'll see reflected in the coming quarters to continue to take costs out. And hopefully, our efforts in the tool space will keep growing sales as well. I will mention, if you look and see the segment breakout here in Biosecurity, again, Q1 2024 or sorry, Q4 2024 to Q1 2025, we're at $5 million on a run-rate burn. That's one where we're hoping to really get Biosecurity to break-even this year. And then Cell Engineering, you can see the enormous progress we've made since Q1 of 2024 last year. But I need to continue squeezing on that in order to reach Adjusted EBITDA break-even next year. So I think we've got a path to it. It will be a serious amount of work. But I've been extraordinarily impressed.

Speaker Change: I'm in quarters.

Speaker Change: So continuing to take costs out and hopefully our efforts in the tool space will keep growing sales as well.

Speaker Change: I will mention if you look.

Speaker Change: And see the segment breakout here.

Speaker Change: And Biosecurity again, Q1, 'twenty 'twenty four.

That is sort of the relentless focus here on the team again, I'm really happy to see the progress it's going the right direction. We already have made changes in the first quarter that you'll see reflected in the coming quarters.

Speaker Change: Q4, 'twenty 'twenty four to Q1 2025.

At $5 million on a run rate burn that's that's one where we're hoping to really get bio security to breakeven. This year and then sell engineering you can see the enormous progress. We've made since Q1 of 'twenty 'twenty four over last year, but need to continue squeezing on on that nor would reach adjusted EBITDA breakeven next year. So I think we've got a path to it it will be a series of <unk>.

So continuing to take costs out and hopefully our efforts in the tool space will keep growing sales as well.

I will mention if you look.

See the segment breakout here.

And Biosecurity.

Again Q1 2024.

Speaker Change: Work, but I've been extraordinarily impressed and again kudos to the team here I can't go on all the work to date to get to the strong position we're in today.

Q4, 'twenty 'twenty four to Q1 2025.

Jason Kelly: And again, kudos to the team here at Ginkgo on all the work to date to get to the strong position we're in today. And again, I don't have it on these slides here, but over $0.5 billion in cash in the bank. This has been a tough market for biotechnology. The companies, I think, that make it out the other side of it will be in an especially strong position. And so the fact that we're so well shored up is thanks to the team's efforts over the last year. All right. Next, I want to talk about the new administration and what the US government is doing in biotechnology and biosecurity. There was actually a great speech. I really encourage you to either watch it or read it from the President's Science Advisor, Michael Kratsios.

At $5 million on a run rate burn that's that's one where we're hoping to really get biosecurity to breakeven. This year and then sell engineering you can see the enormous progress. We've made since Q1 of 'twenty 'twenty four over last year, but need to continue squeezing on on that in order to reach adjusted EBITDA breakeven next year. So I think we've got a path to it it will be a series of them.

Speaker Change: I don't have it on the slides here, but over half a billion dollars in cash in the bank. This has been a tough market for biotechnology.

Speaker Change: So I think that make it out the other side of it it'll be an especially strong position and so the fact that we're so well shored up thanks to the team's efforts over the last year alright.

Speaker Change: Alright.

Out of work, but I've been extraordinarily impressed again kudos.

Speaker Change: So I want to talk about the new administration and what the U S government is doing in biotechnology and Biosecurity.

So the team here I can't go on all the work to date to get to the strong position. We're in today and again I don't have it on the slides here about over half a billion dollars in cash in the bank. This has been a tough market for biotechnology companies I think that make it out the other side of it it'll be an especially strong position and so the fact that we're so well shored up his thanks to the team's efforts over the last year.

Speaker Change: Actually a great speech I really encourage you to watch it I read it.

Speaker Change: From the President Science advisor, Michael Krotz, Yost, it's a cabinet position as of the last administration was turned into a cabinet position on you had a great <unk>.

Jason Kelly: It's a cabinet position as of the last administration was turned into a cabinet position. He had a great speech where he talked about sort of how the administration was going to invest in technology and science. He said, "Whether in AI, quantum, biotech, or next-gen semiconductors, it's the duty of the government to enable scientists to create new theories and power engineers to put them into practice." What's important there is that's your short list of critical technologies for the US: AI, quantum, biotech, and chips. All right. It's good to see biotech on that list. It's been on the list for a while, certainly in the last administration as well. I'm happy to see it's still there from the President's Science Advisor. This is a report that came out. You might remember, I was actually chairing this commission.

Speaker Change: <unk>, we've talked about sort of how the administration was going to invest in technology and science and he said, whether it AI quantum biotech or Nextgen semiconductors.

Alright next I want to talk about the new administration and what the U S. Government is doing in biotechnology and bio security there was actually a great speech I really encourage you to either watch it or read it.

Speaker Change: The duty of government to enable scientists to create new theory, empower engineers to put them into practice and so what important there is that your short list of critical technologies for the U S. AI quantum biotech and chips alright. So it's good to see biotech on that list. It's been on the list for a while certainly in the last administration as well and so I'm happy to see it.

Michael Kratzke: From the President Science advisor, Michael Kratzke OS.

Michael Kratzke: <unk> position as of the last administration was turned into a cabinet position.

Michael Kratzke: Great speech, where you talked about sort of how the penetration we're going to invest in technology and science and he said whether it AI quantum biotech our next gen semiconductors, it's the duty of the government to enable scientists to create new theories empower engineers to put them into practice and so what's important there is that is your short list of critical technologies for the U S. AI.

Speaker Change: There.

Speaker Change: The President Science advisor.

Speaker Change: This is a report that came out of you might remember I was actually.

Speaker Change: During this commission I'm very thankful that our Senator young is now the chair Thats a load off my.

Jason Kelly: I'm very thankful that Senator Young is now the chair. That's a load off me. Michelle Rozo was vice chair. The final report from this National Security Commission on Emerging Biotechnology just came out a few weeks ago. I highly encourage folks to read it. Just a quote here. "We stand at the edge of a new industrial revolution, one that depends on our ability to engineer biology." This is a bipartisan commission. Obviously, Senator Young is a Republican. I see, again, a push here really coming on the legislative side for reduction in regulations, new sources of funding. I think you will see this administration fund things differently than the previous administration. I think you will still see funds continue to go out the door towards biotechnology. Importantly, our solutions business at Ginkgo is a trusted R&D service provider to the US government.

Michelle Rose as Vice chair of the final report from this National Security Commission on emerging biotech.

Michael Kratzke: Quantum biotech and chips alright, so it's good to see biotech on that list. It's been on the list for a while certainly in the last administration as well and so I'm happy to see it's still there.

Speaker Change: Came out a few weeks ago I highly encourage folks to read it just to quote here, we stand at the edge of a new industrial Revolution, one that depends on our ability to engineered biology. So there is a bipartisan commission, obviously senator Republican I see again, a push here really coming on the legislative side.

Speaker Change: From the President Science advisor.

Speaker Change: This is a report that came out you might remember I was actually sharing this commission I'm very thankful that our Senator young is now the chair that's a load off my.

Speaker Change: Or improved reduction in regulations, new sources of funding I think you will see this administration's fund.

Speaker Change: And Michelle Rose as Vice Chair of the final report from this national security commissioned on emerging biotech.

Speaker Change: Fun things differently.

Speaker Change: Just came out a few weeks ago I highly encourage folks to read it just to quote here, we stand at the edge of a new industrial Revolution, one that depends on our ability to engineered biology. So this is a bipartisan commission obviously senator Republican.

Speaker Change: Then the previous administration, but I think you will still see funds continue to go out the door towards biotechnology and importantly, our solutions business that ginkgo is a trusted R&D service provider to the U S. Government. So we have 28 government projects across both cell engineering, and Biosecurity about $180 million plus of contracted backlog.

Speaker Change: Again, a push here are really coming on the legislative side.

Jason Kelly: So we have 28 government projects across both cell engineering and biosecurity, about $180 million plus of contracted backlog or unfunded potential backlog. These are sort of like options on some of our contracts depending on how things go. And just to highlight a couple of wins since President Trump's election, we run a grant called ARPA-H REACT. This is in partnership with Carnegie Mellon, about a $9 million program sort of for bioelectronic devices in disease treatment. But then I really wanted to highlight a new program we just announced a few weeks ago called WEAT. It's a $29 million funded program. And if you go to the next slide, the applications here is really around how do we bring manufacturing of critical raw materials in the pharmaceutical industry back onshore. And I think there's a ton of work to do here.

Speaker Change: For improved reduction in regulations, new sources of funding.

Log or unfunded potential backlog, because it's sort of like options on some of our contracts pending on how things go and just to highlight a couple of wins since.

Speaker Change: You will see this administration's fund.

Speaker Change: Fun things differently.

Speaker Change: Then the previous administration, but I think you will still see funds continue to go out the door towards biotechnology and importantly, our solutions business that ginkgo is a trusted R&D service provider to the U S. Government. So we have 28 government projects across both cell engineering, and bio security about a $188 million plus of contracted backlog.

Speaker Change: President Trump's election.

Speaker Change: We wanted a brand called ARPA H react.

Speaker Change: In partnership with Carnegie Mellon and about $9 million program for bioelectronics devices in disease treatment.

Speaker Change: But then I really wanted to highlight a new program, we just announced a few weeks ago I called wheat us a $29 million funded program.

Speaker Change: <unk> or unfunded potential backlog is just sort of like options on some of our contracts depending on how things go and just to highlight a couple of wins since.

Speaker Change: And if you go to next slide the applications here is really around how do we bring.

Speaker Change: Trump's election.

Speaker Change: We wanted a brand called ARPA H react isn't.

Speaker Change: Manufacturing of critical raw materials in the pharmaceutical industry back onshore and I think there's a ton of work to do here youre already starting to see motions happened here pharmaceutical companies investing in manufacturing plants. That's usually around there are newer drugs. We also have a lot of critical drugs that are antibiotics a lot of our.

Speaker Change: This is in partnership with Carnegie Mellon and about $9 million program bioelectronics devices in disease treatment.

Jason Kelly: You're already starting to see motions happen here, pharmaceutical companies investing in manufacturing plants. That's usually around their newer drugs. We also have a lot of critical drugs that are antibiotics, a lot of our sort of frontline medications that have really been moved overseas over the last 20, 30 years. I think some of those we do want to bring back. So some of that's just going to be building manufacturing plants. But what this program is is actually to make use of wheat germ. So this is; it's an extract that comes as a byproduct of growing wheat. And what's cool about it is you are able to essentially take that wheat germ extract, which has all the components, like the low-level components of cells, right?

Speaker Change: But then I really wanted to highlight a new program, we just announced a few weeks ago I called wheat as of 'twenty.

Speaker Change: $29 million funded program.

Speaker Change: And if you go to next slide the applications here is really around how do we bring manufacturing of critical raw materials in the pharmaceutical industry back on onshore.

Speaker Change: Frontline medications that have really been moved overseas over the last 2030 years I think some of those we do want to bring back. So some of that is just going to be building manufacturing plants.

Speaker Change: But what this program is actually to make use of wheat germ. So this is a.

Speaker Change: Onshore and I think there's a ton of work to do here youre already starting to see motions happened here pharmaceutical companies investing in manufacturing.

Speaker Change: It's an extract that can that comes as a byproduct of growing wheat.

Speaker Change: Cream plants, that's usually around there are newer drugs. We also have a lot of critical drugs that are antibiotics, a lot of our frontline medications that have really been moved overseas over the last 2030 years.

Speaker Change: And what's cool about it is you are able to essentially take that we germ extract which has all the components like the low level components of cells right. So as part of the magic of biology are ourselves, we'd sell a insect cell bacterial cells at the lowest level of the DNA ribosomes there mrna that's all of this.

Jason Kelly: So this is part of the magic of biology, our cells, wheat cells, insect cells, bacterial cells, at the lowest level, the DNA, the ribosomes, the mRNA, that's all the same. And so you can actually reuse the material that comes from that wheat germ, add in a piece of DNA that, say, encodes for human insulin or another therapeutic, and then in that cell-free system, in that extract, actually produce that therapeutic drug. And this is not a technology that's coming out tomorrow, but this is a much lower-cost source for this sort of cell-free extract than what you can currently get on the market today if we're able to be successful in this research project for ARPA-H. And so this is the kind of stuff I think is obviously. I'm excited that we're being a part of this, but I'm just glad to see the government funding this.

Speaker Change: Some of those we do want to bring back. So some of that is just going to be building manufacturing plants.

Speaker Change: But what this program is actually to make use of wheat germ. So this is a it's an extract that can that comes as a byproduct of growing wheat and.

And so you could actually re use the material that comes from that we term AD in a piece of DNA thats, saying codes for a human insulin or another therapeutic and then in that cell free system in that extract actually produce.

Speaker Change: And what's cool about it is you are able to essentially take that we germ extract which has all the components like the low level components of cells right. So this is part of the magic of biology are ourselves, we'd sell a insect cell bacterial cells at the lowest level of the DNA ribosomes there mrna that's all this.

Therapeutic drug and this is not a technology, that's coming out tomorrow, but this is a much lower cost source for this sort of cell free extract than what you can currently get on the market today, if we're able to be successful in this our research projects.

Speaker Change: And so you could actually re use the material that comes from that we term AD in a piece of DNA thats, saying codes for human insulin or another therapeutic and then in that cell free system in that extract actually produce.

Speaker Change: For ARPA age and so this is the type of stuff I think is obviously I'm excited that we're being a part of that so I'm just glad to see the government funding. This.

Speaker Change: And this is the type of thing that Ginkgo solutions business, where we do these end to end projects and deliver a scientific results. This is an example of where we're doing that for the U S government.

Jason Kelly: And this is the type of thing that Ginkgo's solutions business, where we do these end-to-end projects and deliver a scientific result, this is an example of where we're doing that for the US government. And I expect we'll see more of those. Okay. So I want to talk a little bit now about Ginkgo Biosecurity, which is the other big area where we work with the US government. We really have two big product offerings here. The first, we call Canopy. And you might remember, we, I'm not going to go into great detail, but we collect wastewater from planes, inbound planes into international airports. We collect metadata, where did that plane come from? And then we look in the wastewater for a whole panel. I think we're up to like 60 now different infectious diseases.

Speaker Change: Therapeutic drug and this is not a technology, that's coming out tomorrow, but this is a much lower cost source for this sort of cell free extract than what you can currently get on the market today, if we're able to be successful in this our research projects for.

Speaker Change: And I expect we'll see more of those okay. So I want to talk a little bit now about ginkgo bio security.

Speaker Change: Which is the other big area, where we work with U S. Government, we really have two big offerings product offerings here. The first we call canopy and you might remember, we I'm not going to go into great detail, but we collect a wastewater from planes inbound planes into international airports, we collect metadata where did that plane come from and then we.

Speaker Change: Or ARPA age and so this is something I think is obviously I'm excited that we're being a part of this but I'm just glad to see the government funding. This.

Look in the wastewater for a whole panel I think we're up to like 60 now different infectious diseases. If we see them then like if we see a virus we can sequence it and get that variance genomes remember all the COVID-19 variance, we can get the variance sequence and then give that back to the government or whoever is having us do that.

Speaker Change: And I expect we'll see more of those okay. So I want to talk a little bit now about ginkgo bio security.

Jason Kelly: If we see them, then if we see a virus, we can sequence it and get that variant's genomes. Remember all the COVID variants? We can get the variant sequence and then give that back to the government or whoever is having us do that particular work. And so that's the actual physical collection of data. And then our Horizon platform is when we take all that data and we try to give actionable information back to decision makers. And you can imagine there's a lot of great opportunities for AI and sort of automated learning and data parsing there on the Horizon platform. We think of these almost like radar stations for monitoring for infectious disease. I mentioned airports, but absolutely, we should be doing this on ships. We should be doing this at mass gatherings, military installations, embassies, and BSL-3 and BSL-4 labs.

Speaker Change: Fuller work and so that's the actual physical collection of data and then our horizon platform is when we take all that data and we tried to give actionable information back to decision makers and you can imagine there's a lot of great opportunities for AI and.

Speaker Change: Look in the wastewater for a whole panel I think we're up to like 60 now different infectious diseases. If we see them then like if we see a virus we can sequence it and get that variance genomes remember all the COVID-19 variance, we can get the variance sequence and then give that back to the government or whoever is having us do that.

Speaker Change: Sort of automated learning and data parsing there on the horizon platform.

Speaker Change: These types of we think of these like almost like radar stations for monitoring for infectious disease, I mentioned airports, but absolutely we should be doing this on ships should be doing this at mass gatherings military installations and the embassies BSL three and four labs like this is a very obvious thing to me like we ought to be monitoring the effluent like what's coming out.

Speaker Change: <unk> work and so that's the actual physical collection of data and then our horizon platform is when we take all that data and we tried to give actionable information back to decision makers and you can imagine there's a lot of great opportunities for AI.

Jason Kelly: This is a very obvious thing to me. We ought to be monitoring the effluent, what's coming out of these labs and the surrounding area around these labs, just to keep an eye out if there's a leak or things like that. This type of, really, we consider it passive monitoring. You're just looking all the time. We think it's going to be actually critical in terms of having a strong biosecurity defense network here in the United States. And I think this is particularly salient coming up because, as you know, the United States has stepped out of the WHO. And if you look at how the WHO did its work, that was based on voluntary information sharing. So in other words, there'd be an outbreak in a country, and that country's equivalent of the CDC would share that information back with the WHO. WHO would disseminate information globally.

Speaker Change: Of these.

These labs in the surrounding area around these labs just.

Speaker Change: Sort of automated learning and data parsing there on the horizon platform.

Speaker Change: To keep an eye out if there's a leak or things like that this type of really what we consider a passive monitoring like youre just looking all the time.

Speaker Change: These types of we think of these like almost like radar stations for monitoring for infectious disease, I mentioned airports, but absolutely we should be doing this on ships that youre doing this at mass gatherings military installations and the embassies BSL three and four labs like this is a very obvious thing to me like we ought to be monitoring the effluent like what's coming out.

Speaker Change: He is going to be actually critical in terms of having a strong bio security.

Speaker Change: Defense network here in the United States.

Speaker Change: This is particularly salient coming up because as you know the United States has stepped out of the W. H O.

Speaker Change: And if you look at how the W. A Joe did its work that was based on voluntary information sharing so in other words.

Speaker Change: Of these.

Speaker Change: These labs in the surrounding area around these labs just.

Speaker Change: To keep an eye out if there's a leak or things like that this type of really we consider a passive monitoring like youre just looking all the time.

Speaker Change: There'd be an outbreak in the country and that country's equivalent of the CDC would share that information back with the W. H O W. H O disseminate information globally.

Speaker Change: He is going to be actually critical in terms of having a strong biosecurity.

Speaker Change: I think thats getting outdated in this era, one there's a lot less cooperation among countries at the moment number to post COVID-19, it's very clear the economic impact of these things. So once a country has an outbreak. They got is often a reticence to share that information, we even saw that with Covid itself and also the technology has just changed a lot.

Jason Kelly: I think that's getting outdated in this era. One, there's a lot less cooperation among countries at the moment. Number two, post-COVID, it's very clear the economic impact of these things. So once a country has an outbreak, there's often a reticence to share that information. We even saw that with COVID itself. And also, the technologies just changed a lot in the last 20 years. And passive monitoring, like I talked about on the last couple of slides, can turn a political problem where you have to ask people for things and have the politics to have them give it to you into a technological problem where we're just looking. And if something happens, we see it. And just to be clear, that's how we approach cybersecurity. That's how we approach missile defense.

Speaker Change: Defense network in the United States and I think this is particularly salient coming up because as you know the United States has stepped out of the W. H O.

Speaker Change: And if you look at how the W. H O did its work that was based on voluntary information sharing so in other words.

Speaker Change: There'd be an outbreak in a country and that country's equivalent of the CDC would share that information back with the W. H O W. H O disseminate information globally.

Speaker Change: In the last 20 years in passive monitoring like like I talked about in the last couple of slides can turn a political problem, where you have to ask people for things and have the politics to have them give it to you. It's a technological problem, where we're just looking and if something happens we see it and just to be clear that's how we approach cyber security that's how we approach Miss.

Speaker Change: I think thats getting outdated in this era, one there's a lot less cooperation among countries at the moment number to post COVID-19, it's very clear the economic impact of these things. So once the country has an outbreak. They got is often I'm reticent to share that information, we even saw that with Covid itself and also the technology has just changed a lot.

Speaker Change: Defense, We don't ask did you launch a missile a we have the satellites up there looking all the time for them and that's really how we should move to a platform like that for monitoring infectious disease, and I'm hopeful there'll be opportunities to do that as the U S considers how to build our infrastructure outside of the W. H O.

Jason Kelly: We don't ask, "Did you launch a missile?" We have the satellites up there looking all the time for them. And that's really how we should move to a platform like that for monitoring infectious disease. And I'm hopeful there'll be opportunities to do that as the US considers how to build our infrastructure outside of the WHO. Okay. I want to now talk about Ginkgo's data points and automation offerings where I see new deals and opportunities emerging. Okay. So about a year ago, I showed this slide for the first time. So Ginkgo's historical way we brought our platform to customers was through what we call solutions, where our customer is really the head of R&D. So this is the person who is in charge of, say, drug development at a company like Merck, Pfizer, and Novo Nordisk, some of our customers.

Speaker Change: And the last 20 years in passive monitoring like like I talked about in the last couple of slides can turn a political problem, where you have to ask people for things and have the politics to have them give it to you. It's a technological problem, where we're just looking and if something happens we see it and just to be clear that's how we approach cyber security that's how we.

Speaker Change: Okay.

Speaker Change: Now talk about getting those data points and automation offerings, where I see new deals and opportunities emerging.

Speaker Change: Okay. So.

Speaker Change: Missile Defense, we don't ask did you launch a missile we have the satellites up there looking all the time for them and that's really how we should.

Speaker Change: So about a year ago I showed the slide for the first time.

Speaker Change: So ginkgo as historical way, we brought our platform to customers was through what we call solutions, where our customers really the head of R&D. So this is the.

Speaker Change: Move to a platform like that for monitoring infectious disease, and I'm hopeful there'll be opportunities to do that as the U S considers how to build our infrastructure outside of the W. H L.

Speaker Change: Person, who is in charge of say drug development at a company like Merck or Pfizer and over in order to some of our customers and ginkgo is an outsourced.

Speaker Change: Okay I want to now talk about again goes data points and automation offerings, where I've seen new deals and opportunities emerging.

Jason Kelly: Ginkgo is an outsourced scientific team with access to a highly automated, unique platform here in the 200,000-sq-ft lab over here next to me in Boston. We would give that customer back a scientific result. So a good example is that WEAT program I just mentioned. The customer there is a program manager, sort of a head of R&D for the government at ARPA-H. Our job is to give them back a scientific result over a period of 1 to 2 years with milestones along the way, very similar to our commercial relationships. All right. About a year ago, we said, "Hey, we're going to keep doing that. We're going to do it in a more focused set of areas." That's a lot of how we took the cost down.

Speaker Change: Antefix team with access to a highly automated unique platform here in the 200000 square foot lab over here next to me in Boston, and we would give that customer back scientific result, So a good example is that week program I just mentioned the customer there is a program managers sort of our head of R&D for the government it.

Speaker Change: Okay. So.

Speaker Change: So about a year ago I showed this slide for the first time.

Speaker Change: So ginkgo as historical way.

Speaker Change: Way, we brought our platform to customers was through what we call solutions, where our customers really the head of R&D. So this is the.

Speaker Change: Person, who is in charge of say drug development at a company like Merck or Pfizer and over in order to some of our customers and ginkgo is an outsourced scientific team with access to a highly automated unique platform here in the 200000 square foot lab over here next to me in Boston, and we would give that.

Our bache and our job is to give them back a scientific result over a period of one to two years with milestones along the way very similar to our commercial relationships alright about a year ago, We said hey, we're going to keep doing that we're going to do it in a more focused set of areas that is a lot of how we took the cost down but we're also going to start offering that very same platform same robots.

Jason Kelly: But we're also going to start offering that very same platform, the same robotics, the same integrated systems directly to customer scientists, okay, to the many scientists that are at a Novo Nordisk or a Merck, and give them tools so that they could do the job of scientific discovery. And that was a new way to go to market. I really like this chart, this curve here. I've shown this before. But on the Y-axis, the idea here is as you go up the axis, you have increased customization and technical risk for the customer. And the reason I'm highlighting this is because there's sort of a business model shift in the middle of this chart. So at the extreme left end of this, I'm designing a custom drug. I'm taking all the risk on it.

Speaker Change: Customer back scientific result, so a good example is that week program I just mentioned the customer there is a program manager sort of a head of R&D for the government at our Bache and our job is to give them back a scientific result over a period of one to two years with milestones along the way very similar to our commercial relationships alright.

Speaker Change: X the same integrated systems directly to customers scientists, okay to the many scientists that are at an <unk> or a merck and give them tools. So that they could do the job of scientific discovery and that was a new way to go to market.

Speaker Change: I really like this chart. This curve here have shown this before but on the Y axis. The idea here is.

Speaker Change: About a year ago, we said hey, we're going to keep doing that we're going to do it in a more focused set of areas a lot of how we took the cost down but we're also going to start offering that very same platform same robotics. The same integrated systems directly to customers scientists. Okay too. Many scientists that are at an open artists are of Merck and give them tools, so that they could do that.

As you go up the Axis, you have increased customization and technical risk for the customer and the reason I'm highlighting this is because there is sort of a business model shift in the middle of this chart. So at the extreme left hand of this I'm designing accustomed drug I'm, taking all the risk on it and I'm, hoping that when I get great phase III results are phase III results.

Jason Kelly: I'm hoping that when I get great phase 2 results or phase 3 results, I can sell it to a large pharma company. I make an enormous amount of value, all right, but I take a lot of risk, and it's very custom. As you go down the chart, you have our research solutions business. So we are doing custom work. Every one of these customer projects is different. And it is technical risk. We get paid if we are successful and we hit certain technical milestones. And so as a result, we're able to get royalties and milestones. We're able to get a piece of the customer's product revenue, essentially, okay, in one form or another. That's sort of on the left-hand side of that dotted green line. On the right-hand side, you have our tools offerings. And here, we are not taking a royalty.

Speaker Change: Job of scientific discovery and that was a new way to go to market.

Speaker Change: Can sell it to a large pharma company I make an enormous amount of value alright, but I take a lot of risk and it's very custom as you go down. The chart you have our research solutions business. So we are doing custom work like every one of these customer projects is different.

Speaker Change: I really like this chart. This curve here I've shown this before but on the Y axis. The idea here is.

Speaker Change: As you go up the Axis, you have increased customization and technical risk for the customer and the reason I'm highlighting this is because theres sort of a business model shift in the middle of this chart. So at the extreme left hand of this I'm designing accustom drug I'm, taking all the risk on it and I'm, hoping that when I get great phase III results are phase III results.

Speaker Change: And it is it is.

Speaker Change: Technical risks like we get paid if we are successful and we had certain technical milestones and so as a result, we're able to get royalties and milestones were able to get a piece of the customers' product revenue essentially okay. In one form or another that's sort of on the left hand side of that dotted Green line on the right hand side you have our tools.

Speaker Change: I can sell it to a large pharma company I make an enormous amount of value alright, but it'd take a lot of risk and it's very custom as you go down. The chart you have our research solutions business. So we are doing custom work like every one of these customer projects is different.

Speaker Change: Offerings and here, we are not taking a royalty we're not taking any milestones from the customer and what we're really offering is sort of fee for service work for that customer.

Jason Kelly: We're not taking any milestones from the customer. What we're really offering is sort of fee-for-service work for that customer so that they can ultimately develop their own products. That's either going to market with sort of a traditional CRO-style business model with data points or via an equipment business model with automation. This really does change. If you go to the next slide, the solutions business is really based on sort of longer-term but bigger upside per project. We're getting a piece of that drug value, for example, in the long run. It just takes a long time. The advantage of our tools business is its near-term fees. It's a faster sales cycle. We have many, many more potential customers for that product in any organization.

Speaker Change: And it is it is.

Speaker Change: Technical risk like we get paid if we are successful and we hit certain technical milestones and so as a result, we were able to get royalties and milestones were able to get a piece of the customers' product revenue essentially okay in one form or another that sort of on the left hand side of that dotted Green line on the right hand side, you have our tools offerings.

They can ultimately develop their own products and that's either going to market with sort of attritional like C. R. O style business model of data points.

Speaker Change: Or by our equipment business model with automation.

Speaker Change: And this really.

Speaker Change: Does change if you go to the next slide.

Speaker Change: The solutions business is really based on sort of longer term, but bigger upside per project, we're getting a piece of that.

Speaker Change: And here, we are not taking a royalty.

Speaker Change: Not taking any milestones from the customer.

Speaker Change: And what we're really offering is sort of fee for service work for that customer.

Speaker Change: <unk> value for example in the long run it just takes a long time the advantage of our tools business is its near term fees. It's a faster sales cycle and we have many many more potential customers for that product in any organization.

Speaker Change: So that they can sell.

Speaker Change: It's really developed their own products and that's either going to market with sort of attritional like C. R. O style business model what data points.

Speaker Change: Or by our equipment business model with automation.

Speaker Change: And the reason I'm excited about this is ginkgo has worked out the hard challenges over the last 10 years.

Jason Kelly: And the reason I'm excited about this is Ginkgo has worked out the hard challenges over the last 10 years of building out our own automation and software stack. If you go to the next slide. This is not just hardware. It's also our code base, our operations, our data stack, and everything else. We've done this over 200 R&D projects in agricultural, industrial, and pharma biotechnology. So we have the scars of knowing sort of what works and what doesn't work when you're doing this work at a high throughput. If you go to the next slide, our interest from customers is really around sort of large data set generation for AI. This has been wind in our sales as we've opened our platform up. Companies like Genentech and Recursion have been showing that you can use these AI models in service of drug discovery.

Speaker Change: And this really does change if you go the next slide.

Speaker Change: The solutions business is really based on sort of longer term, but bigger upside per project and we're getting a piece of that that drug value. For example in the long run. It just takes a long time the advantage of our tools business is its near term fees. It's a faster sales cycle and we have many many more potential customers for that.

Speaker Change: Building out our own automation and software stack to go to the next slide.

Speaker Change: And this is not just hardware. It's also our code base, our operations, our data stack and everything else and we've done this over 200 R&D projects in agricultural industrial and pharma biotechnology. So we have the scars of knowing sort of what works and what doesn't work.

Speaker Change: In any organization.

And the reason I'm excited about this is ginkgo has worked out the hard challenges over the last 10 years.

Speaker Change: When youre doing this work at a high throughput.

Speaker Change: And if you go the next slide our interest.

Speaker Change: Customers is really around sort of large dataset generation for AI. This is Ben wind in our sales as we've opened our platform up companies like Genentech and <unk> have been showing that that you can use. These AI models in service of drug discovery, that's meaning a lot more companies are interested in sort of automated data.

Speaker Change: Building out our own automation and software stack to go to the next slide.

Jason Kelly: That's meaning a lot more companies are interested in sort of automated data generation. And that's exactly what we've built the reps doing over the last 10 years. And so that's been an excellent conversation to have with customers. Now, if you go to the next slide, Ginkgo's technology is shown on the right here. That's our facility in Boston with our automated racks. I will highlight the left-hand side of this chart. The lab bench with the Fisher catalog to order whatever reagents you need is actually a very effective way to go do drug discovery, right? It's a very effective way to go discover plant traits and things like that. It allows scientists to order what they need when they need it. It's very quick. You get turnaround in 24 hours, massively customizable. There's nothing wrong with the left-hand side.

Speaker Change: <unk> and that's exactly what we've built the reps doing over the last 10 years and so that's been <unk>.

Speaker Change: When youre doing this work at a high throughput.

Speaker Change: And if you go the next slide our interest.

Speaker Change: Excellent conversation to have with customers now.

Speaker Change: Customers is really around sort of large dataset generation for AI. This is Ben wind in our sales as we opened our platform up companies like Genentech and <unk> had been showing that that you can use. These AI models in service of drug discovery, that's meaning a lot more companies are interested in sort of automated data.

Speaker Change: On the next slide Kinko's technology as shown on the right here, that's our facility in Boston with our automated racks.

Speaker Change: I will highlight the left hand side of this chart the lab bench with the <unk>.

Speaker Change: Catalog to order whatever reagents, you need is actually a very effective way to go do drug discovery right years ago, a very effective way to go discover plant trades and things like that.

Speaker Change: Generation and that's exactly what we've built the reps doing over the last 10 years and so that's been <unk>.

Speaker Change: It allows scientists to order what they need when they need it it's very quick.

Speaker Change: Excellent conversation to have with customers now.

Speaker Change: The next slide Kinko's technology as shown on the right here, that's our facility in Boston with our automated racks.

Turnaround in 24 hours massively customizable, there's nothing wrong with the left hand side.

Speaker Change: <unk> is not great at generating low cost data points in other words, if you wanted to make a lot of data from an AI model or for hydro blood screening or things like that the bench is not your friend you do need to move on to something like robotics and.

Jason Kelly: It just is not great at generating low-cost data points. In other words, if you want to make a lot of data for an AI model or for high throughput screening or things like that, the bench is not your friend. You do need to move on to something like robotics. I highlight that on the next slide as well. These are just two different approaches that are quite complementary, right? It isn't like one has to replace the other. That's a lot of the conversations we have with customers.

Speaker Change: I will highlight the left hand side of this chart the lab bench with the.

Speaker Change: Fisher catalog to order whatever reagents, you need is actually a very effective way to go do drug discovery right and it's a very effective way to go discover plant trades and things like that.

Speaker Change: I like that on the next slide as well. These are just two different approaches that are quite complementary right. It isn't like one has to replace the other there's a lot of the conversations we have our customers, it's really that particularly as these AI models are gaining in prominence youre going to want to have what we call a foundry basically a generalized automated facility that can be quickly <unk>.

Speaker Change: It allows scientists to order what they need when they need it it's very quick.

Speaker Change: Turnaround in 24 hours massively customizable, there's nothing wrong with the left hand side. It just is not great at generating low cost data points in other words, if you want to make a lot of data from an AI model or for hydro, but screening or things like that the bench is not your friend you do need to move on to something like robotics.

Jason Kelly: It's really that, particularly as these AI models are gaining in prominence, you're going to want to have what we call a foundry, basically a generalized automated facility that can be quickly reprogrammed to make new large data sets to support your AI and ML teams alongside of the benches where your scientists are still doing small batch, very hypothesis-driven research. And by the way, what you learn over here from the foundry and the AI models is going to inform those scientists' hypotheses. Absolutely. That's exactly what we've seen with the Recursions and the Genentechs of the world, where you can use the foundry for, say, target discovery and then get in the lab at the bench and go test those targets out quickly by hand.

Speaker Change: Program to make new large datasets support your AI and ml teams alongside of the benches, where your scientists are still doing small batch very hypothesis, driven research and by the way what you learn over here from the foundry in the AI models is going to inform those scientists hypotheses absolutely that's exactly what we've seen.

Speaker Change: And I like that on the next slide as well.

Speaker Change: Or just two different approaches that are quite complementary right. It isn't like one has to replace the other that's a lot of the conversations we have with customers. It's really that particularly as these AI models are gaining in prominence youre going to want to have what we call a foundry basically a generalized automated facility that can be quickly reprogrammed to make new large datasets.

Speaker Change: With the recurrence and the genetics of the World, where you can use the foundry per se target discovery and then get in the lab at the bench in and go test those targets out quickly by hand, so that type of feedback loop I think every major pharma every large research Institute will ultimately need to have sort of a foundry type setup to complement their lab benches.

Speaker Change: Support your AI and ml teams alongside of the benches, where your scientists are still doing small batch very hypothesis, driven research and by the way what you learn over here from the foundry in the AI models is going to inform those scientists hypotheses absolutely that's exactly what we've seen.

Jason Kelly: So that type of feedback loop, I think every major pharma, every large research institute will ultimately need to have sort of a foundry-type setup to complement their lab benches. All right. So Ginkgo Datapoints is our first offering in this area. I'm not going to spend. I talked a lot about it at the last earnings call. Just a quick update on this. We launched actually just yesterday or, well, yeah, Monday, our GDP A1 dataset. And these data drops are very valuable for the community. And they showcase the output of our Datapoints services. So this is a really great one. There's a new preprint that came out. You can see on the right, there's a link at the bottom to go download the dataset. But 246 different therapeutic antibodies. And you can see these 10 different developability assays listed on the left.

Speaker Change: Alright, so ginkgo data points is our first offering in this area I'm not going to spend I talked a lot about at the last earnings call. Just a quick update on this we launched actually just yes.

Speaker Change: With the recurrence and the genentech's of the World, where you can use the foundry per se target discovery, and then getting the lab at the bench and go test those targets out quickly by hand, so that type of feedback loop I think every major pharma every large research Institute will ultimately need to have sort of a foundry type setup to complement their lab benches.

Speaker Change: Yeah Monday.

Our GDP a one dataset.

Speaker Change: And these data drops are very valuable.

Speaker Change: For the community and they showcase the output of our data point services. So this is a really great. One theres a theres a new pre rent that came out you can see on the right. There's a link at the bottom to go download the datasets, but 246 different therapeutic antibodies and you can see these 10 different develop ability assay is listed on the left and then importantly, all.

Speaker Change: That data is a really clean format for your AI or ml team to go play around with it and so we're going to keep doing that so you'll see us keep putting out datasets.

Jason Kelly: Then importantly, all that data is in a really clean format for your AI or ML team to go play around with it. So we're going to keep doing this. You'll see us keep putting out data sets. The data scientists love these. It creates new customer demand for us. And it showcases just what our platform can do. Okay. I want to spend a chunk of time real quick talking about Ginkgo Automation and some of the interests we've seen around, in particular, AI reasoning models and connecting those to automated platforms in the lab. First, I want to mention we had a big win. So we announced a week or two ago that we had partnered and sold a system to Aura Genetics. This is a diagnostics company building out a new facility.

Speaker Change: Monday or GDP, a one dataset.

These data drops are very valuable.

Speaker Change: For the community and they showcased the output of our data point services. So this is a really great. One theres a theres a new pre rent that came out you can see on the right. There's a link at the bottom to go download the datasets, but 246 different therapeutic antibodies and you can see these 10 different develop ability assay is listed on the left and then importantly, all.

Speaker Change: The data scientist love. These it creates new customer demand for us and it showcases just what our platform can do.

Speaker Change: Okay. So I want to spend a chunk of time real quick talking about gig automation and some of the interest we've seen around in particular, AI reasoning models and connecting those to automated platforms in our lab first I want to mention we had a big win so we announced about a week or two ago.

Speaker Change: That data is a really clean format for your AI or ml team to go play around with it and so we're going to keep doing that so you'll see us keep putting out datasets.

Speaker Change: That we are partnering solar system to our of genetics.

Speaker Change: Diagnostics company building out a new facility. This is really exciting to me because I'm on.

Speaker Change: The data scientist love. These it creates new customer demand for us and it showcases just what our platform can do.

Jason Kelly: This is really exciting to me because on the next slide, we've obviously had a lot of success with early customers like Octant in the drug discovery space, 7x throughput increase, 88% reduction in hands-on time. They've been using the system for two years. They were kind of our original drug discovery beta customer. A lot of conversations with high throughput screening. Pharma companies are definitely going to buy this. But diagnostics companies is really a new market for Ginkgo. So I'm really excited to see the automation going there. And I think this is one of the exciting things about Ginkgo's platform going out as tools, okay? When we were offering solutions, we had sort of a much more narrow window of where we could apply, say, our automation, right? It was ultimately going up through this kind of window of a research project associated with cell engineering.

On the next slide.

Speaker Change: Okay. So I want to spend a chunk of time real quick talking about Google automation and some of the interest we've seen around in particular.

Speaker Change: Obviously had a lot of success with early customers like octant in the drug discovery space seven X throughput increased 88% reduction in hands on time, they've been using the system for two years. They were kind of our original drug discovery beta customer.

Our reasoning models and connecting those to automated platforms in the lab.

Speaker Change: First I want to mentioned, we had a big win so we announced a week or two ago.

Speaker Change: A lot of conversations with high throughput screening pharma company is definitely gonna by this but diagnostics companies is really a new market for Ingo. So I'm really excited to see the automation going there I think this is one of the exciting things about kinko's platform going out as tools.

Speaker Change: We are partnering sold assistant to our of genetics.

Speaker Change: Diagnostics company building out a new facility.

Speaker Change: It's really exciting to me because I'm on.

Speaker Change: On the next slide.

Speaker Change: Obviously, you had a lot of success with early customers like Oct ins in the drug discovery space seven X throughput increased 88% reduction in hands on time, they've been using this system for two years, they were kind of our original drug discovery beta customer.

Speaker Change: Okay. When we are offering solutions, we had sort of like a much more narrow window of where we could apply say our automation right. It was ultimately going up through this kind of window of a research project associated with cell engineering now the automation could really go anywhere to any lab that would benefit from integrated automation and you can see that with our rack carts.

Speaker Change: A lot of conversations with high throughput screening pharma companies definitely gonna by this but diagnostics companies is really a new market for ginkgo. So I'm really excited to see the automation going there I think this is one of the exciting things about kinko's platform going out as tools.

Jason Kelly: Now, the automation could really go anywhere to any lab that would benefit from integrated automation. You can see that with our Rack Carts. If you go to the next slide, the idea behind the Ginkgo Automation is we're basically creating a standardized physical wrapper around a piece of laboratory, essentially benchtop hardware. So that's a centrifuge there, that orange thing inside the rack. Then we have a robotic arm. And then we have a piece of MagnaMotion track, which is kind of like a little railroad track that can move material along it and deliver a 96- or 384- or whatever well plate to that robotic arm. The arm picks it up and puts it onto the, in this case, centrifuge. All right. And so what you've done is you've taken a piece of lab equipment that today is very custom, right? It's coming from some particular vendor.

Speaker Change: On the next slide.

Speaker Change: The idea behind that Ginkgo automation is we're basically creating a standardized physical wrapper around a piece of laboratory essentially bench top hardware. So that's that's a centrifuge there that orange thing inside the rack then we have a robotic arm and then we have a piece of Magnum motion track, which is a.

Kind of like Little railroad track that can move material, along it and deliver a 96 or 384 or whatever well plates to that robotic arm the arm picks it up and puts it onto the in this case centrifuge.

Speaker Change: On the next slide.

Speaker Change: The idea behind that Ginkgo automation is we're basically creating a standardized physical wrapper around a piece of laboratory Sn.

Speaker Change: And so what you've done is you've taken a piece of lab equipment that today is very custom right like it's coming from some particular vendor. It's got its own software you got to walk up to it and interact with it and you put it inside this box and once you've done that if you go to the next slide you can stick that.

Speaker Change: Essentially bench top hardware. So that's that's a centrifuge there that orange thing inside the rack then we have a robotic arm and then we have a piece of Magnum Ocean track, which is a.

Jason Kelly: It's got its own software. You've got to walk up to it and interact with it. And you put it inside this box. And once you've done that, if you go to the next slide, you can stick that rack cart together with as many other ones as you want in a line. And let's say you had 10 pieces of equipment you wanted to integrate. We would send you the 10 carts with that equipment. You would stick them in a line. And then you would use our cloud software to control it. And suddenly, you don't need to be in the weeds in the software on all 10 pieces of lab equipment because our software has parameterized control of all of them.

Speaker Change: Like Little railroad track that can move material, along it and deliver a 96 or 384 or whatever well plates to that robotic arm the arm picks it up and puts it onto the in this case centrifuge alright, and so what you've done is you've taken a piece of lab equipment that today is very custom right.

Speaker Change: <unk> card together with as many other ones as you want and align and let's say you had 10 pieces of equipment you wanted to integrate we would send you. The 10 carts with that equipment you would stick them in line and then you would use our cloud software to control it and suddenly you don't need to be in the weeds in the software on all 10 pieces of lab equipment, because our software.

Speaker Change: Coming from some particular vendor it's got its own software you got to walk up to it and interact with it and you put it inside this box and once you've done that if you go to the next slide you can stick that that rack card together with as many other ones as you want in a line and let's say you had 10 pieces of equipment you wanted to integrate.

Speaker Change: He has parameterized control of all of them.

Speaker Change: And we didn't have to like a traditional integrated automation vendor would basically do a big custom design for you of custom engineering project that would take.

Jason Kelly: We didn't have to, like a traditional integrated automation vendor would basically do a big custom design for you, a custom engineering project that would take a year or something to ultimately design and build and get it shipped and installed for you. If we had these 10 racks available, we could send them over and put them together in a very short period of time, and so, a matter of weeks. So that is really exciting and a big change to how you build out integrated automation. The other big change, other than just speed to deploy, is it's expandable. So when you normally build a custom integrated setup for automation, it's built to do one thing, right? With these rack systems, for example, this is a system we have in Boston. We had five of these to start with, I think, or six doing NGS prep.

Speaker Change: A year or some things ultimately design and build and get it shipped and installed for you.

Speaker Change: We will send you the 10 carts with that equipment, you would stick them in line and then you would use our cloud software to control it and suddenly you don't need to be in the weeds in the software on all 10 pieces of lab equipment, because our software.

Speaker Change: If we add these 10 racks available we could send them over and put them together in a very short period of time and so on.

Speaker Change: Matter of weeks and so that that is really exciting and a big change to how you build out integrated automation. The other big change other than just speed to deploy is it is expandable.

Speaker Change: As parameterized control of all of them.

Speaker Change: And we didn't have to like a traditional integrated automation vendor would basically do a big custom design for you of custom engineering project that would take a.

Speaker Change: So when you normally build a custom integrated setup for automation.

Speaker Change: Built to do one thing right.

Speaker Change: With these rack systems. For example, this is a system we have in Boston, We had five of these to start with I think six doing mgs prep that was like the original application and then we were able to keep adding more racks. We now have 25 racks on this setup and and we have a whole range of different you can see it here our equipment that have been integrated into <unk>.

Speaker Change: A year or some things ultimately design and build and get it shipped and installed for you. If we add these 10 racks available we could send them over and put them together in a very short period of time and so it's a matter of weeks and so that that is really exciting and a big change to how you build out integrated automation the other big change.

Jason Kelly: That was the original application. Then we were able to keep adding more racks. We now have 25 racks on this setup. We have a whole range of different, you can see it here, equipment that have been integrated into these systems. We have three different sizes of racks so that we can integrate this equipment. This is out of date. We keep adding stuff. Whatever customers want in their setup, if there's a piece of equipment that we haven't yet integrated, we can get it integrated in a few weeks. So we're really excited about this kind of general concept. Customers are loving this as well. You can see our booth here at the SLAS show on the next slide. What I like about this, actually, the top right corner, there was a this is actually a J.P. Morgan Recursion Have a Party.

Speaker Change: Other than just speed to deploy is it's expandable.

These systems, we have three different sizes of <unk>. So that we can integrate this equipment. There's a lot of date, we keep adding stuff whatever customers want in their setup, where theres a piece of equipment that we havent yet integrated we can get it integrated in a few weeks.

Speaker Change: So when you normally build a custom integrated setup for automation.

Speaker Change: Its built to do one thing.

Speaker Change: Right with these rack systems. For example, this is a system we have in Boston, We had five of these to start with I think or six doing mgs prep that was like the original application and then we were able to keep adding more racks. We now have 25 racks on this setup and and we have a whole range of different you can see it here our equipment that have been integrated into.

Speaker Change: So really excited about this.

Speaker Change: Kind of general concepts and customers are loving this as well you can see our booth here.

Speaker Change: Here at the S O I S show on the next slide.

Speaker Change: No.

Speaker Change: What I like about this actually the top right corner there was actually.

Speaker Change: JP Morgan recur Jeanette Party, and we said how can we bring the racks and so we were able to set them up.

Speaker Change: These systems, we have three different sizes of rack. So that we can integrate this equipment has a lot of date, we keep adding stuff whatever customers want in their setup, if theres a piece of equipment that we havent yet integrated we can get it integrated in a few weeks.

Jason Kelly: And we said, "Hey, could we bring the racks?" And so we were able to set them up in a few hours in the afternoon before the cocktail party and have the moving plates around. So that's the kind of speed in terms of deploying an integrated automation setup that you just really don't see with other technology. This next slide is a picture of our facility in Boston. That's an older picture. But that's that 25-rack setup I was mentioning. And another thing that's unique about Ginkgo is that we actually run our own automation. This is in our BSL-2 lab here in Boston to do high throughput data generation for these research projects we're doing for customers. So we have a lot of experience understanding sort of biovalidation and moving these high throughput protocols onto integrated automation.

Speaker Change: In a few hours in the afternoon before the cocktail party and have them moving place around so that's the kind of speed in terms of deploying an integrated automation setup and you just really don't see with other technology.

Speaker Change: So really excited about this.

Speaker Change: Kind of general concepts and customers are loving this as well you can see our booth.

Speaker Change: Next slide the picture of our facility in Boston.

Speaker Change: Here at the SLA as show on the next slide.

Speaker Change: It is an older picture, but it's about 25 rack setup I was mentioning in another thing Thats unique about ginkgo is that we actually run our own automation. This is our BSL to lab here in Boston to do high throughput data generation for these research projects, we're doing for customers. So we have a lot of experience understanding sort of.

Speaker Change: And what I like about this is actually the top right corner. There's a this is actually J P. Morgan recursion out party and we said how can we bring the racks and so we were able to set them up.

In a few hours in the afternoon before the cocktail party and have them moving plates around so that's the kind of speed in terms of deploying an integrated automation setup and you just really don't see with other technology.

Speaker Change: Bio validation and moving these high throughput protocols.

Speaker Change: Onto onto integrated automation, so one of the things I'm really excited and when we have had customers reaching out to us about this system. If you go to the next slide is this application of.

Speaker Change: This next slide the picture of our facility in Boston.

Jason Kelly: So one of the things I'm really excited, and we have customers reaching out to us about this system, if you go to the next slide, is this application of what people are calling Lab in the Loop or sort of Physical AI in the lab. And so just to give you an example of this, if you were to go onto ChatGPT and click that little deep research button, and you ask it a question, instead of getting an answer in 5 seconds, it's going to give you an answer in like 5 minutes. And the reason for that, and you can even ask it if you want to see it doing this, you can say, "Hey, show your thinking." And you'll see what's called chain of thought reasoning. And so what the model does is it says, "Okay.

Speaker Change: It is an older picture that's about twenty-five rack setup I was mentioning and another thing thats unique about ginkgo is that we actually run our own automation. This is our BSL to lab here in Boston to do high throughput data generation for these research projects, we're doing for customers. So we have a lot of experience understanding sort of.

Speaker Change: But people are calling lab in the loop.

Speaker Change: Or sort of physical AI.

Speaker Change: In the lab and so just to give you example of this if you were to go onto chat GPT and click that little deep research button.

Speaker Change: And you're asking a question.

Speaker Change: Bio validation and moving these high throughput protocols.

Speaker Change: Instead of getting an answer in five seconds. It is going to give you an answer in like five minutes and the reason for that and you can even ask it if you want to see it doing this you can say hey show your thinking and Youll see what's called chain of thought reasoning and so what the model does is it says okay based on your what you've asked me to do I've broken this problem into pieces and for piece number one.

Speaker Change: But people are calling lab in the loop.

Speaker Change: Or sort of physical AI.

Jason Kelly: Based on what you've asked me to do, I've broken this problem into pieces. And for piece number 1, I'm going to go call up a web browser and do some research on the internet." And then based on that information I get back, there's a bunch of numeric data in there. So I'm going to write a Python script to analyze that data. And based on the results of the Python script, I'm going to do some more thinking and analysis. Then I'm going to write you a summary." And it goes and does all this. It's absolutely fabulous. You really should see it if you haven't. But what's gotten people excited is that type of reasoning and analysis, what if you were to then connect a reasoning model like that into the physical world?

Speaker Change: In the lab and so just to give you example of this if you were to go onto chat GBT and click that little deep research button.

I'm going to go call up a web browser and do some research on the Internet and then based on that information I get back there is a bunch of numeric data in there so I'm going to write a python scripts to analyze that data and based on the results of the Python script I'm going to do some more thinking and analysis I'm going to write you a summary, and it goes it does all of this it's absolutely fabulous.

Speaker Change: And you're asking a question.

Speaker Change: Instead of getting an answer in five seconds, it's going to give you an answer in like five minutes and the reason for that and you can even ask it if you want to see it doing this you can say hey show your thinking and Youll see what's called chain of thought reasoning and so what the model does is it says okay based on your what you've asked me to do I've broken this problem into pieces and for piece number one.

Speaker Change: You really should see and if you haven't but what's gotten people excited is that type of reasoning and analysis. What if you were to then connect or reasoning model like that into the physical world.

Speaker Change: I'm going to go call up a web browser and do some research on the Internet and then based on that information I get back there is a bunch of numeric data in there so I'm going to write a python script to analyze that data and based on the results of the Python script I'm going to do some more thinking and analysis I'm going to write you a summary, and it goes it does all of this it's absolutely fabulous.

Speaker Change: So theres a lot of activity right now a lot of startups getting funded to do like robotic hands like pick things up bold shirts or assemble electronics, but.

Jason Kelly: And so there's a lot of activity right now, a lot of startups getting funded to do robotic hands to pick things up and fold shirts or assemble electronics. But what I think is really exciting is, could we give that reasoning model hands in the lab? And that's how we see our racks. They're actually a perfect fit for this. We're able to integrate, I mean, you could integrate 100 pieces of equipment. We have one project where we're scoping that with racks. But in Boston, for example, we already have a setup with 25 pieces of lab equipment set up. And if you go to the next slide, a reasoning model could go ask that set of equipment to run some experiments and then get back really rich data, time series data, raw data files.

Speaker Change: But what I think is really exciting is could we give that reasoning model hands in the lab.

Speaker Change: And that's how we see our racks there actually like a perfect fit for this we're able to integrate <unk>.

Speaker Change: You really should see it if you haven't but what's gotten people excited is that type of reasoning and analysis. What if you were to then connect our reasoning model like that into the physical world.

Speaker Change: You could integrate 100 pieces of equipment, we have.

Speaker Change: One project, where we're scoping that with racks, but in Boston for example, we already have a setup with 25 pieces of lab equipment set up and.

Speaker Change: So theres a lot of activity right now a lot of startups getting funded to do like robotics hands like pick things up bold shirts, or assemble electronics, but what I think is really exciting is could we give that reasoning model hands in the lab.

Speaker Change: And if you go to the next slide our raising Mark ago asked that that set of equipment to run some experiments and then get back really rich data time series data raw data files of racks gave a whole bunch of event data limbs metadata.

Speaker Change: And that's how we see our racks, there actually like a perfect fit for this we're able to integrate.

Jason Kelly: The racks give a whole bunch of event data, LIMS metadata about exactly what's going on inside that experiment, a lot more data than you would get if you were doing the experiment by hand at the lab bench. These are just things that you wouldn't be collecting. You just wouldn't be collecting them because you're doing a lot of small things as you work at the bench that aren't really being recorded. But everything is being recorded when it's being run on automated setups. And if you go to the next slide, you can see we've already demonstrated this is a 24-hour protocol without any human intervention, 10,000 qPCR reactions. These are the types of things we can do. This is just one example of sort of just a large data set on a complex protocol being run over a long period of time.

Speaker Change: Exactly what's going on inside that experiment a lot more data than you would get if you were doing.

Speaker Change: And you could integrate 100 pieces of equipment.

Speaker Change: We have one project, where we're scoping that with racks, but in Boston for example, we already have a setup with 25 pieces of lab equipment set up.

Speaker Change: Driven by hand at the lab bench, you'll just things that you wouldn't be collecting.

Speaker Change: It just wouldn't be collecting them because youre doing a lot of small things as you work at the bench that arent really being recorded but everything is being recorded when it's being run an automated setups and if you go to the next slide you can see we've already demonstrated.

Speaker Change: And if you go to the next slide our reasoning monarch ago asked that that set of equipment to run some experiments and then get back really rich data time series data raw data files. The racks gave a whole bunch of event data limbs metadata.

Speaker Change: 24 hour protocol without any human intervention 10000, Q PCR reactions. These are the types of things. We can do this is just one example of searches a large data set on a complex.

Speaker Change: Exactly what's going on inside that experiment a lot more data than you would get if you were doing.

Speaker Change: Protocol being run over a long period of time. So these sort of like long continuous experiments ideally with a reasoning model controlling it talking.

Speaker Change: Driven by hand at the lab bench, you'll just things that you wouldn't be collecting.

Jason Kelly: So these sort of long, continuous experiments, ideally with a reasoning model controlling it and talking, being able to having those hands in the lab, is something we're really excited about, and we have a lot of customers excited about too. And so if you go to the next slide, I'll just say for customers tuning in, again, this is what's special about Ginkgo compared to a traditional automation vendor. Over the last 10 years, we have been building and running a highly automated lab. And that's not just having the automation set up and doing one thing over and over again. It's doing many things, collecting the data off that automation, getting it cleaned up, and back to the scientist. There's a whole software and data stack needed to really make the most out of these sort of automated data foundries.

Speaker Change: Being able to having those hands in the lab is something we're really excited about and we have a lot of customers excited about too and so.

If you go to the next slide I'll, just safer customers tuning in again. This is what's special about ginkgo compared to Attritional automation vendor over the last 10 years, we have been building and running a highly automated lab and that's not just having the automation setup in doing one thing over and over again, it's doing many things collecting the data off that automation getting it cleaned up and back to.

Speaker Change: Protocol being run over a long period of time. So these sort of like long continuous experiments ideally with a reasoning model controlling it talking.

Speaker Change: Scientists as a whole software and data stack needed to really make the most out of these sort of automated data foundries and so if your task to bring AI into your research department or deploy these sort of lab in a loop models, we're more than happy not just engage with you on the automation, but really on a consultative basis to help.

Speaker Change: Being able to having those hands in the lab is something we're really excited about and we have a lot of customers excited about too and so.

Speaker Change: If you go to the next slide I'll, just safer customers tuning in again. This is what's special about ginkgo compared to Attritional automation vendor over the last 10 years, we have been building and running a highly automated lab and that's not just having the automation setup in doing one thing over and over again, it's doing many things collecting the data off that automation getting it cleaned up and back to.

Jason Kelly: And so if you're tasked to bring AI into your research department or deploy these sort of lab in the loop models, we're more than happy not just to engage with you on the automation but really on a consultative basis to help you build out your whole technology stack internally. And we've actually started doing that for some large pharmas now as well. So these are, I think, just some of the things I wanted to update on. I think this whole push on the reasoning model on the AI side is really exciting. And again, I want to just highlight and thank the team for an enormous, enormous amount of work over the last year, for us to be in the position where we are today, where we have growing opportunities on the tool side. We have world-leading automation.

Speaker Change: You build out your whole technology stack internally and we are we've actually started doing that for some large farmers now as well. So so these are I think are just some of the things I want to update on I think this whole push on the reasoning model and AI side is really exciting and again I want to just highlight and thank the team for an enormous enormous amount of work over there.

Speaker Change: The scientists as a whole software and data stack needed to really make the most out of these sort of automated data foundries and so if your task to bring AI into your research department or deploy these sort of lab in a loop models, we're more than happy not just engage with you on the automation, but really on a consultative basis to <unk>.

Speaker Change: Last year for us to be in the position where are today, where we have growing opportunities on the tool side, we have world leading automation, we have over half a billion dollars in the bank and our spending is under control is a far cry from where we were a year ago.

Jason Kelly: We have over half a billion dollars in the bank. And our spending is under control, is a far cry from where we were a year ago. And so again, kudos to the team for pulling that off. And look forward to hearing your questions. Thank you so much.

Speaker Change: Again kudos to the team for pulling that off and look forward to hearing your questions. Thank you so much.

Speaker Change: Great. Thanks, Jason as usual I'll start with a question from the public and remind the analysts on the line that they'd like to ask a question. Please just raise your hand on zoom and I'll call on you and open up your line. Thanks, everyone.

Daniel Waid Marshall: 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, please just raise your hand on Zoom, and I'll call on you and open up your line. Thanks, everyone.

Speaker Change: Last year for us to be in a position where are today, where we have growing opportunities on the tool side, we have world leading automation, we have over half a billion dollars in the bank and our spending is under control is a far cry from where we were a year ago.

Speaker Change: Alright.

Speaker Change: Getting started.

Mark Dmytruk: All right. Getting started. So our first question is from X.com. And this question is from, that's, Brendan. Excuse me. The question is, "Does Jason think there's a possible opportunity for data points to evolve into a SaaS cloud computing product tool to compete with traditional companies in the space like Veeva Systems?

So our first question is from X Dot Com and this question is from that Brendan.

Speaker Change: Again kudos to the team for pulling that off and look forward to hearing your questions. Thank you so much.

Excuse me.

Speaker Change: The question is does Jason think there's a possible opportunity for data points to evolve into a SaaS cloud computing product tool to compete with traditional companies in the space like Veeva systems.

Speaker Change: Great. Thanks, Jason as usual I'll start with the question from the public and remind the analysts on the line that they'd like to ask a question. Please just raise your hand on zoom and I'll call on you and open up your line. Thanks, everyone.

Speaker Change: Yes, it's actually a good question.

Speaker Change: So I've mentioned this a little bit at the end, but we've been starting to do more of it was like Wow.

Jason Kelly: Yeah, it's actually a good question. So I mentioned this a little bit at the end, but we've been starting to do more of these, at least kind of I'll call it consultative, almost like tech-enabled consulting for a large pharma company where we're actually coming in and helping them think about their data architecture and how you should if you're going to run a big automated lab, what does it look like? What software do you need to have in place to do that? What kind of data systems do you need to have in place to do that? And so forth. And I think this is something that Ginkgo has a lot of very uniquely specialized expertise in. There's a question of how to go to market with that. Do you actually want to go all the way to offering SaaS software?

Speaker Change: Alright.

Speaker Change: Kind of I'll call. It a consultative almost like tech enabled consulting for a large pharma company, where we're actually coming in and helping them think about their data architecture and like how you should if youre going to run a big automated lab.

Speaker Change: Getting started.

Speaker Change: So our first question is from X Dot Com and this question is from that Brendan.

Speaker Change: Excuse me.

Speaker Change: Or does it look like what what software do you need to have in place to do that what kind of data systems, you need to have in place to do that.

Speaker Change: And so forth and I think this is something that ginkgo has a lot of.

Speaker Change: Yes, it's actually a good question.

Very uniquely specialized expertise in it.

Speaker Change: So I've mentioned this a little bit at the end, but we've been starting to do more of it.

Speaker Change: It's a question of like kind of go to market with that like do you actually want to go all the way to offering like SaaS software do you want to just do consultative work and then be able to bring in things like our automation technology alongside that and so on we're still figuring that stuff out, but certainly companies do make plenty of money in this sort of cloud and SaaS based so we saw an opening there I would say the.

Kind of I'll call. It consultative almost like tech enabled consulting for a large pharma company, where we're actually coming in and helping them think about their data architecture and like how you should if youre going to run a big automated lab, what does it look like what what software do you need to have in place to do that what kind of data systems, you need to have in place to do that.

Jason Kelly: Do you want to just do consultative work and then be able to bring in things like our automation technology alongside that and so on? We're sort of figuring that stuff out. But certainly, companies do make plenty of money in the sort of cloud and SaaS space. So if we saw an opening there, I would say the research side of the house, this is a little different when it comes to commercial, where I think you already have a lot of these tools in pharma sales and things like that. But when it comes to the research side of the house, many companies don't already have in place large sort of data infrastructure. And so again, most of the work is done at the bench. Most of it is not large data sets, with the exception of things like high throughput screening.

Speaker Change: The research side of the house is a little different when it comes to commercial where I think you already have a lot of these tools and like pharma sales and things like that but when it comes to the research side of the house. Many many companies are not.

Speaker Change: And so forth and I think this is something that ginkgo has a lot of.

Speaker Change: Very uniquely specialized expertise in.

Speaker Change: There's a question of like how to go to market with that like do you actually want to go all the way to offering like SaaS software or do you want to just do consultative work and then be able to bring in things like our automation technology alongside that and so on we're start figuring that stuff out, but certainly companies do make plenty of money and that sort of cloud and SaaS space. So we saw an opening there I would say.

Speaker Change: Don't already have in place large sort of data infrastructure and so again most of the work is done at the bench most of it is not large datasets with the exception of things like either but screening so as they build out more of that I do think there's an opening we've got to see if if.

Jason Kelly: So as they build out more of that, I do think there's an opening. We'll have to see if it's a business for us. But definitely, it's a place we can help, I would say.

Speaker Change: If it's a business for us, but I definitely its a place we can help I would say.

Speaker Change: Okay.

Speaker Change: Alright, now for some questions from our analysts.

Mark Dmytruk: All right. Now for some questions from our analysts. The first question is from Michael Riskin from Bank of America. Michael, your line is open.

Speaker Change: First question is from Michael Riskin from Bank of America.

Speaker Change: Many companies are not.

Speaker Change: Michael you are your line is open.

Speaker Change: Don't already have in place large sort of data infrastructure and so again most of the work is done at the bench most of it is not large datasets with the exception of things like high throughput screening so as they build out more of that I do think there is an opening we've got to see if.

Great can you guys hear me, Yeah, Hey, Michael.

Michael Ryskin: Great. Can you guys hear me?

Speaker Change: Are.

Jason Kelly: Yeah. Hey, Michael.

Speaker Change: Thanks for taking the question I wanted to ask.

Michael Ryskin: Hey. How are you? Thanks for taking the question. I wanted to ask kind of a two-parter but on the same topic. One is on the ARPA-H news you provided, just sort of wondering if you could provide a little bit more details on some of the economics beyond that. We have the headline number in terms of the $29 million contract, but just thoughts on how and when that'll be recognized, how that contributes to revenues. And then related to that, you had a couple of slides where you talked about government contracts, government relationship, things like that. Just wondering what the latest on those is, given the current environment with DOGE cutting back a lot of that funding. Have they been reviewed already? Are those sort of how safe are those? And if you could talk about any take-or-pay considerations there, that'd be helpful.

Speaker Change: Kind of a two parter, but on the same topic.

Speaker Change: One is on the ARPA H.

Speaker Change: If it's a business for us, but I definitely its a place we can help I would say.

Speaker Change: As you provided just sort of wondering if you could provide a little bit more details on.

Speaker Change: Okay.

Speaker Change: Some of the economics beyond that we have the headline number in terms of the the $29 million contract, but just thoughts on how and when that will be recognized how that contributes to revenues and then related to that you had a couple of slides, but you talked about Gov.

Speaker Change: Alright, now for some questions from our analysts.

Speaker Change: First question is from Michael Riskin from Bank of America.

Speaker Change: Michael you are your line is open.

Speaker Change: Great can you guys, sorry, Yeah, Hey, Mike Hey, how are you.

Speaker Change: Government contracts government relationship things of that just wondering what the latest on.

Speaker Change: Taking the question I wanted to ask a.

Speaker Change: Kind of a two parter, but on the same topic.

Speaker Change: One is on the ARPA H news you provided just sort of wondering if you could provide a little bit more details on.

Speaker Change: On those is given the current environment with Doge cutting back a lot of that funding.

Speaker Change: Have they been reviewed already are those sort of how safe are those and if you could talk about any take or pay considerations there that'd be helpful.

Speaker Change: So Jason I'd be happy to take the first part of that so the ARPA is just in terms of kind of economics out of the revenue flows.

Mark Dmytruk: So Jason, I'd be happy to take the first part of that. So the ARPA-H, just in terms of kind of economics, how the revenue flows. So it's a $29 million two-year contract. So you can sort of expect sort of generally revenue to be recognized over two years. And then I guess the second point I would just make is that from our perspective, that really significantly de-risks the guide for the year. And so yeah. So I think it was very good news to be getting that from the perspective of this year.

Speaker Change: Government contracts government relationship things like that just wondering what the latest on those is given the current environment with Doge cutting back a lot of that funding.

Speaker Change: So it's a $29 million two year contract. So you can sort of expect sort of generally revenue to be recognized.

Speaker Change: Over two years, and then I guess, the second point I would just make.

Speaker Change: They've been reviewed already are those sort of how safe are those and if you could talk about any take or pay considerations there that'd be helpful.

Speaker Change: Is that from our perspective that really significantly de risks the guide for the year.

Speaker Change: And so.

Speaker Change: Yeah. So.

Speaker Change: So Jason I'd be happy to take the first part of that so the ARPA is just in terms of kind of economics out of the revenue flows. So it's a $29 million two year contract. So you can sort of expect sort of generally revenue to be recognized.

Speaker Change: I think it was very good news to be getting that from the perspective of this year.

Speaker Change: Yes, certainly.

Speaker Change: The second part, yes that was one of the ones that you're keeping an eye on that we had sort of gotten awarded.

Jason Kelly: Yeah. To sort of speak to the second part, yeah, that was one of the ones we were keeping an eye on that we had sort of gotten awarded, knew we were going to get it, but we hadn't closed on contracting. So I do think in general, like I mentioned, I think biotechnology is still on the short list of critical emerging technologies. So I'm generally hopeful that any additional programs that we have that aren't quite contracted yet will move through, but importantly, that they'll still continue to be funding. Like Mark said, the WEAT was sort of the big bogey on that for us for this year. But in general, what's more important is, do we keep seeing the funding of advanced research in this area? We think so.

Knew we were going to get it but we haven't closed on contracting. So I do think in general like I mentioned I think biotechnology is still on the shortlist of critical emerging technologies on generally hopeful that.

Speaker Change: Over two years, and then I guess, the second point I would just make.

Speaker Change: Is that from our perspective that really significantly de risks the guide for the year.

Speaker Change: So.

Speaker Change: Any additional programs that we have that arent quite contracted yet we'll move through but importantly that they'll still continue to be funding like like Mark said that we were sort of the big bogey on that for us for this year, but in general what's more important is like do we keep seeing the funding of advanced research in this area. We think so and then.

Speaker Change: Yeah. So.

Speaker Change: I think it was very good news to be getting that from the perspective of this year.

Speaker Change: Yes.

Speaker Change: The second part, yes that was one of the ones. We're keeping an eye on that we had sort of gotten awarded knew we were going to get it but we haven't closed on contracting so I do think in general.

Speaker Change: Certainly on the.

Speaker Change: I mentioned I think biotechnology is still on the shortlist of critical emerging technologies on generally hopeful of that.

Jason Kelly: And then certainly, on the biosecurity side, there was a couple of executive orders just today related to bio. I don't know if you saw that. But there was one on regulatory relief to promote domestic production of critical medicines. So that's right in line with sort of the WEAT project and generally onshoring. It's basically reducing regulation for people building out manufacturing for pharma, not something we do, but just to speak to this being a critical priority. And then second was improving safety and security of biological research. This is around not funding gain-of-function work, but again, speaks to, I'd say, biosecurity being on the list of things that are not being written off as not important. So cautiously optimistic, but of course, you never know.

Speaker Change: Bio security side, there is a couple of executive orders just today arent related to bio I don't know if you saw that but there's there was one on.

Speaker Change: Any additional programs that we have that arent quite contracted yet we'll move through but importantly that they will still continue to be funding like like Mark said that we were sort of the big bogey on that for us for this year, but in general what's more important is like do we keep seeing the funding of advanced research in this area. We think so and then certainly.

Regulatory relief to promote domestic production of critical medicines. So that's right in line.

Speaker Change: What sort of the wheat project and generally onshoring is basically in reducing regulation for people building out manufacturing for pharma and not something we do but just to speak to this being a critical priority and then <unk>.

Speaker Change: One is improving safety and security of biological research. This is around like not funding gain of function.

Speaker Change: On the bio security side. There is a couple of executive orders just today aren't related to bio I don't know if you saw that but there's there was one on.

Speaker Change: Work, but again speaks to I'd say bio security being on the list of things that are not being written off is not important so I'm cautiously optimistic but of course, you never know.

Speaker Change: Regulatory relief to promote domestic production of critical medicines. So that's right in line.

Speaker Change: What sort of the weed project and generally onshoring, it's basically reducing regulation for people building out manufacturing for pharma and not something we do but just to speak to this being a critical priority and then.

Speaker Change: If I could.

Speaker Change: A follow up Mark on the first part on the operation just clarify Theres multiple partners in that right. So is there any clarity on how the $29 million gets split up or yes. So we're the prime which means we will recognize all the revenue on that and you would then see.

Michael Ryskin: If I could squeeze in just a follow-up, Mark, on the first point on the ARPA-H, just clarify, there's multiple partners in that, right? So is there any clarity ahead of time how that $29 million gets split up, or?

Speaker Change: Second one is improving safety and security of biological research. This is around like not funding gain of function.

Mark Dmytruk: Yeah. So we're the prime, which means we will recognize all the revenue on that. And you would then see sort of in the cost of sales or in the R&D expense line, the effect of the subcontractor costs on that. But we would be recognizing the full amount of revenue.

Speaker Change: Work, but again speaks to I'd say bio security being on the list of things that are not being written off is not important so.

Speaker Change: Sort of in the cost of sales or in the R&D expense line the effect of the subcontractor costs on that but we would be recognizing the full amount of revenue.

Cautiously optimistic but of course, you never know.

Speaker Change: If I could.

Speaker Change: I guess, just a follow up mark on the first part on the operation just clarify theres multiple partners in that right.

Speaker Change: Okay alright. Thanks.

Michael Ryskin: Okay. All right. Thanks.

Speaker Change: Alright. Our next question is from Mark Massaro, because from BTG Mark your life.

Mark Dmytruk: All right. Our next question is from Mark Massaro, who's from BTIG. Mark, you're live.

Speaker Change: Are there any clarity on how the $29 million gets split up or so so we're the prime which means we will recognize all the revenue on that and you would then see.

Speaker Change: Hey, Mark you're muted.

Jason Kelly: Hey, Mark. You're muted.

Michael Ryskin: Sure.

Speaker Change: Sort of in the cost of sales or in the R&D expense line the effect of the subcontractor costs on that but we would be recognizing the full amount of revenue.

Speaker Change: All right, maybe we can we got you Mark now you've got it okay cool.

Mark Dmytruk: All right. Maybe we can.

Jason Kelly: Yeah. We got you, Mark. Now you're.

Speaker Change: You got me now.

Mark Dmytruk: We got him. Okay. Cool.

Jason Kelly: Yeah. All right.

Austin: Yeah, you can Austin.

Mark Dmytruk: Sorry. You got me now?

Jason Kelly: Yep. Yeah. Yeah. Yeah. You got me.

Speaker Change: Thank you for the question. So I wanted to just ask a question about the revenue generating program metric maybe.

Mark Dmytruk: Awesome. Thank you for the question. So I wanted to just ask a question about the revenue-generating program metric. Maybe this could be for you, Mark. Just help us think about how we should be tracking the economics per program. So if I'm doing the math right, it looks like the revenue per program might be down in the quarter. Can you just give us a sense for how we should think about that? Is that something that should grow, or is it because you're onboarding newer programs that are just starting to generate revenue, it takes some time to move up?

Speaker Change: Okay alright. Thanks.

Mark Massaro: Alright. Our next question is from Mark Massaro, because from BTG Mark your life.

Maybe this could be for you Mark just help us think about how we should be tracking the economics per program.

Speaker Change: Hey, Mark you're muted.

Speaker Change: If I'm doing the math right. It looks like the revenue per program might be down in the quarter can you just give us a sense for how we should think about that is that something that should grow.

Speaker Change: All right, maybe we can we got you Mark now you've got it okay cool.

Speaker Change: You got me now.

Speaker Change: Yeah, you can awesome.

Speaker Change: Or is it because you're onboarding newer programs that are just starting to generate revenue. It takes some time to move up.

Speaker Change: Thank you for the question. So I wanted to just ask a question about the revenue generating program metric maybe.

Speaker Change: Maybe this could be for you Mark just help us think about how we should be tracking the economics per program.

Speaker Change: It's actually a little bit of a mix shift.

Jason Kelly: It's actually a little bit of a mix shift from sort of the new data points. So the number of data points, you may see some, but it's still too early days to kind of predict.

Speaker Change: From sort of the two data points. So the number of data point you may see some but it's still too early days to kind of predict okay. And then the other one is just.

Mark Massaro: If I'm doing the math right. It looks like the revenue per program might be down in the quarter can you just give us a sense for how we should think about that is that something that should grow.

Mark Dmytruk: Okay. And then the other one is just, and I recognize the new reporting structure is early days. But if I have this right, it looks like your revenue-generating programs increased by 21. Do you think about them addressing throughout the year? And then I would just be curious if you could just give us any color as to sort of the flavor of some of these programs and what might have surprised you in the quarter.

Speaker Change: I recognize the new reporting structures is early days, but if I have this right. It looks like your revenue generating programs increased by 21.

Speaker Change: Or is it because you're onboarding newer programs that are just starting to generate revenue. It takes some time to move up.

Speaker Change: You think about that throughout the year and then it would just be curious if you could just give us any color as to.

Speaker Change: It's actually a little bit of a mix shift.

Speaker Change: From sort of the bigger solutions deals.

Speaker Change: Sort of like the flavor of some of these programs and what.

Speaker Change: Two data points deals so the number of data points deals when in the metric went from about 10 to 20, when you compare Q4 to.

Speaker Change: What might have surprised you in the quarter.

Speaker Change: So it's so youre going to have programs complete and programs that onboard and so the net impact of that means you probably are not going to see.

Jason Kelly: So you're going to have programs that complete and programs that onboard. And so the kind of net impact of that means you probably are not going to see a net plus 20 sort of quarter after quarter after quarter after quarter. You're going to have some quarters where we finish a bunch of programs. And so again, still early days, Mark, with the metric. But I think we're all sort of keeping our eye on that trend line. The flavor in terms of what's in there, so I would say, generally speaking, the solutions deals, of course, are bigger. The data points deals are smaller. There are just a few automation deals in the mix right now because that's really the newest of the tools' offerings. We did sign a bunch of ag solutions deals in Q1, which is new.

Speaker Change: Net plus 'twenty sort of quarter after quarter after quarter after quarter that youre going to have some quarters, where we are.

Speaker Change: Where we finish a bunch of programs and so again still early days mark with the metric but.

Speaker Change: But I think we're all sort of keeping our eye on that trend line.

Speaker Change: The <unk>.

Speaker Change: Flavor in terms of.

Speaker Change: What's in there. So there is still I would say like generally speaking the solutions deals of course are bigger the data points deals are smaller.

Speaker Change: There are just a few automation deals in the mix right now because that's really the newest of the tools offerings. We did sign a bunch of AG solutions deals in Q1, which is new I think it might have been the most new programs that I remember in that sort of part of the business.

Jason Kelly: I think it might have been the most new programs that I remember in that sort of part of the business in a single quarter. That said, they're all relatively small in size. And so you could think of those as almost pilot in terms of scale relative to the solution side of the business. So yeah, I would just say probably the flavor is good diversity in terms of what we're seeing with big programs, small programs across ag, biopharma, etc., data points, solutions.

Speaker Change: In a single quarter that said, they're all relatively small in size and so you can think of those as almost.

Speaker Change: And I.

Speaker Change: I recognize the the new reporting structures is early days, but if I have this right. It looks like your revenue J D J.

Speaker Change: Pilot in terms of scale relative to the solution side of the business. So yeah, I would just say probably like the flavors. Good diversity in terms of what we're seeing with big programs small programs across.

Speaker Change: To think about them.

Speaker Change: Progressing throughout the year and then it would just be curious if you could just give us any color as to.

Speaker Change: Biopharma etcetera data points solutions.

Speaker Change: Great. Thank you.

Speaker Change: Sort of like the flavor of some of these.

Mark Dmytruk: Great. Thank you.

Speaker Change: Thanks Mark.

Michael Ryskin: Thanks, Mark.

Speaker Change: Prized you in the quarter.

Speaker Change: Alright next question from Te Josh Who's coming from Morgan Stanley. Your line is open.

Mark Dmytruk: All right. Next question from Tejas, who's coming from Morgan Stanley. Your line is open.

Speaker Change: Hey, guys good evening and thanks for the time here.

Tejas Savant: Hey, guys. Good evening. Thanks for the time here. So maybe a sort of predictable question for you, Jason, just on the continued pressure on pharma and biotech here. The commentary from service providers through the earnings season has gotten incrementally more cautious, I guess. And I guess a lot of sort of nebulous concerns out there, things like tariffs and reference pricing. This afternoon, we heard of the appointment of a new head of CBER today with pretty vocal stance and accelerated approvals and surrogate endpoints and whatnot. So I'm just curious as to what you're hearing from your customers, especially over the last 6 to 8 weeks when things seem to have sort of ratcheted up a little bit, if you will.

Speaker Change: So it's so youre going to have programs are complete and programs that onboard and so that kind of net impact of that means you probably are not going to see a net plus.

Speaker Change: So maybe.

Speaker Change: Sure predictable question for you just on the.

Speaker Change: The continued pressure on pharma and biotech hear the commentary from the service providers.

Speaker Change: 'twenty sort of quarter after quarter after quarter after quarter that youre going to have some quarters, where we are.

Speaker Change: The starting season has gotten incrementally more cautious I guess yeah.

Speaker Change: Where we finish a bunch of programs and so.

Mark Massaro: Again, it's still early days, mark with the metric but.

And I guess.

Speaker Change: A lot of sort of nebulous concerns out there you know things like Paris reference pricing. This afternoon Reorders the appointment of a new head of seaborne today.

Mark Massaro: But I think we're all sort of keeping our eye on that trend line.

Mark Massaro: The.

Mark Massaro: Flavor in terms of.

Speaker Change: Many local stands at accelerated approvals and surrogate endpoints and whatnot. So.

Mark Massaro: What's in there so there's still I would say like generally speaking the solutions deals of course are bigger the datapoints deals are smaller.

Speaker Change: I'm, just curious as to what Youre hearing from your customers, especially or.

Speaker Change: The last like six to eight weeks when things seem to ratchet it up a little bit if you will.

Mark Massaro: There are just a few automation deals in the mix right now because that's really the newest of the tools offerings. We did sign a bunch of AG solutions deals in Q1, which is new and I think it might have been the most new programs that I remember in that sort of part of the business.

Speaker Change: Yeah.

Speaker Change: I would say overall it is like there is a lot of sort of hesitancy in general around R&D.

Jason Kelly: Yeah. I mean, I would say overall, there is a lot of sort of hesitancy in general around R&D services. So I think you're just seeing, a, less outsourcing of stuff. People are more protective of their internal teams. So that's been headwinds for us on the solution side. I think if you look across the industry broadly, there's less demand going to basically all CRO, equipment, and tools vendors. And you've seen that reflected in the pressure on all of them. I mentioned this before. Ginkgo's new in the tools industry. So unlike, say, WuXi or somebody that's highly penetrated across the whole industry and sort of moves with the total demand, we're more winning pie from others. And so I think there's a lot of opportunity for us still uniquely in tools. But I would say the whole sector is definitely under pressure.

Speaker Change: Services like I think youre seeing a less outsourcing staff people are like more protective of their internal teams. So that's like that headwinds for us on the solution side.

Mark Massaro: In a single quarter that said, they're all relatively small in size and so you can think of those as almost.

Speaker Change: I think if you look across the industry broadly.

Mark Massaro: Pilot in terms of scale relative to the solution side of the business.

Speaker Change: Like there is less demand going to like basically all CRO and equipment and tools vendors I think that's then you've seen that reflected in the pressure on all of them.

Speaker Change: Yeah, I would just say probably like the flavors good diversity in terms of what we're seeing with big programs small programs across AG biopharma etcetera data points solutions.

Speaker Change: I've mentioned this before ginkgo is new in the tools industry. So so unlike.

Speaker Change: Saying wuxi or somebody that's like highly penetrated across the whole industry and sort of moves with the total demand we're more winning pie.

Thank you.

Mark Massaro: Thanks Mark.

Speaker Change: Our next question from Cage Us Who's coming from Morgan Stanley. Your line is open.

Speaker Change: From others, and so I think Theres I think theres a lot of opportunity for us still uniquely in tools, but I would say the whole sector is definitely under pressure.

Speaker Change: Hey, guys good evening and thanks for the time here.

Speaker Change: You know I think that probably means places invest less in new advanced technologies and outright like I think you are less likely to see a lot of the current players like doing some big project to expand in the new area right. Now. So that's may be good for us because we're sort of an innovative new entrants and so.

Jason Kelly: I think that probably means places invest less in new advanced technologies, right? I think you're less likely to see a lot of the current players doing some big project to expand in a new area right now. So that's maybe good for us because we're sort of an innovative new entrant. But I would say across the industry, I'm hearing from people what you're hearing, which is pullback on things. But I don't know that Ginkgo maybe gets affected a little less on that when it comes to our tools business. I do think on solutions, it makes it tougher for us.

Speaker Change: So many of you know.

Speaker Change: Sure predictable question for Hagen said just on the the continued pressure on on on pharma and biotech here you know the commentary from the service providers.

Speaker Change: This earning season has gotten.

Speaker Change: So, but I would say across the industry.

Speaker Change: Incrementally more cautious I guess yeah.

Speaker Change: Hearing from people what you are hearing which is pull back on things, but I don't know whether that ginkgo, maybe gets affected a little less on that when it comes to our tools business I do think on solutions that makes it tougher for us.

Speaker Change: And I guess you know.

Speaker Change: A lot of sort of nebulous concerns out there you know on things like Paris, and reference pricing itself known Reorders the appointment of a new head of seaborne today.

Speaker Change: Got it that's helpful.

Tejas Savant: Got it. That's helpful. A couple of quick cleanups for Mark. Mark, can you just share some color or just ballpark numbers to help us bridge from your old program ad metrics, the new revenue-generating programs? And then I think on the last call, you guys had talked about a little bit of potential upside from the tools offering and a number of pharma deals that closed in Q4. So just curious as to how those opportunities have evolved since. And then on this sort of pharma reshoring point, Jason, which you alluded to a little bit earlier, is there an opportunity beyond sort of the work you're doing with ARPA-H here, in your mind, for Ginkgo to participate in?

Speaker Change: It's a very local stands at accelerated approvals and surrogate endpoints and whatnot. So.

Speaker Change: Real quick cleanups of Mark.

Speaker Change: Can you just share some color just ballpark numbers to help US bridge from your old program add metrics of new revenue generating programs.

Speaker Change: I'm, just curious as to what Youre hearing from your customers, especially over.

Speaker Change: The last like six to eight weeks when things seem to ratchet it up a little bit if you will.

Speaker Change: And then I think on the last call you guys had talked about a little bit of potential upside from the tools offering in a number of pharma deals that closed in the fourth quarter. So just curious as to how those those opportunities that evolved since.

Speaker Change: Yeah, I mean, I would say overall it is likely there is a lot of sort of hesitancy in general around R&D services like energy are you seeing a less outsourcing of staff people are like more protective of their internal teams. So that's like that headwinds for us on the solution side.

Speaker Change: Then on this sort of pharma reassuring point, Jason that you alluded to a little bit earlier.

Speaker Change: Is that an opportunity beyond sort of the work you're doing with our by age you are in your mind for ginkgo to participate in.

Speaker Change: I think if you look across the industry broadly.

Speaker Change: There like there's less demand going to like basically all cero and equipment and tools vendors I think that's then you've seen that reflected in the pressure on all of them.

Yeah.

Speaker Change: Alright, so why don't I start there so in terms of bridging the old metric to the new so the new metric.

Mark Dmytruk: All right. So why don't I start there? So in terms of bridging the old metric to the new, so the new metric, very importantly, excludes programs with de minimis revenue in the quarter. So that would typically be a program that is either just starting or is in the final stages of completion. And we really, in any particular quarter in the past, had quite a lot of those. We might have had, just rough numbers, 20 to 30 programs that were in kind of a start mode and a maybe similar number that were in a final stage of completion mode. And so those would be kind of out of the mix right now completely.

Speaker Change: Very importantly excludes programs with de Minimis revenue in the quarter. So that would typically be a program that is either just starting or.

Speaker Change: I mentioned this before Giga is new in the tools industry. So so on unlike you know say in wuxi or somebody that's like highly penetrated across the whole industry and sort of moves with the total demand where more winning pie.

Speaker Change: Or is in the final stages of completion.

Speaker Change: And we really in any particular quarter in the past had quite a lot of those like like we might have had.

Speaker Change: From others, and so I think there's I think there's a lot of opportunity for us still uniquely in tools, but I would say the whole sector is definitely under pressure.

Speaker Change: Just like rough numbers 20 to 30 programs that were in kind of a start up mode and are maybe similar number that were in a final stage of completion mode and so those would be kind of out of the mix right now completely.

Speaker Change: You know I think that probably means places invest less in new advanced technologies in outright like anger, you're less likely to see a lot of the current players like doing some big project to expand in a new area right. Now. So that's may be good for us because we're sort of an innovative new entrants and so but I would say across the industry honestly.

Speaker Change: However, it's not a straight subtract because we're now including programs that wouldn't have been included in the past because it didn't meet the sort of definition of what we thought of as a major program and so a lot of the sort of smaller data points programs or even small solutions programs.

Mark Dmytruk: However, it's not a straight subtract because we're now including programs that wouldn't have been included in the past because they didn't meet the sort of definition of what we thought of as a major program. And so a lot of the sort of smaller data points programs or even small solutions programs wouldn't necessarily have been included in the past at all under the definition. And so those are now kind of in the mix. So that's sort of the rough bridge here. Now, if you look in the appendix to the presentation, we have included a restatement of the, or I would just say, the historical comparables that you need on the current metric so that you can see what it was in each quarter of last year. So that'll help you kind of bridge the old to the new.

Speaker Change: Hearing from people what you are hearing witches pullback on things, but I don't know whether that king of maybe against the fact that a little less on that when it comes to our tools business I do think on solutions that makes it tougher for us.

Speaker Change: Wouldn't necessarily have been included in the past it all under the definition.

Speaker Change: And so those are now kind of in the mix. So that's sort of like the rough bridge here now if you look in the appendix to the presentation.

Speaker Change: Got it that's helpful.

Speaker Change: Real quick cleanups of Marta, but can you just share some color just ballpark numbers to help US bridge from your old program add metrics of new revenue generating programs.

Speaker Change: We have included a.

Speaker Change: <unk>.

Speaker Change: A restatement of our I would just say the historical Comparables that you need on the current metric. So that you can see what it was in each quarter of last year. So that'll help you kind of bridge the old to the new.

Speaker Change: On your second question.

Mark Dmytruk: On your second question, upside on tools and pharma. So I think probably the best way to put it is in terms of the revenue guide. Yes, the guide is still being, I would say, relatively conservative in terms of what we're expecting from tools this year. So still kind of in that low double-digit $ million contribution on a full-year basis. And just to put that in context, in the first quarter, tools contributed sort of low single-digit $ millions in terms of revenue. So less than 10% of the Cell Engineering revenue in Q1 came from the tools offering. And then we would expect that number to increase as we get sort of through the year. But it's still early days, so we're being conservative there. But I would say there's upside potential on the tools side of the business, particularly on data points.

Mark Dmytruk: On your second question, upside on tools and pharma. So I think probably the best way to put it is in terms of the revenue guide. Yes, the guide is still being, I would say, relatively conservative in terms of what we're expecting from tools this year. So still kind of in that low double-digit $ million contribution on a full-year basis. And just to put that in context, in the Q1, tools contributed sort of low single-digit $ millions in terms of revenue. So less than 10% of the Cell Engineering revenue in Q1 came from the tools offering. And then we would expect that number to increase as we get sort of through the year. But it's still early days, so we're being conservative there. But I would say there's upside potential on the tools side of the business, particularly on data points.

Speaker Change: And then you know on this sort of pharma reassuring point, Jason that you alluded to a little bit earlier is that an opportunity beyond sort of the work you're doing with our by age you are in your mind for ginkgo to participate in.

Speaker Change: Upside on tools and pharma so.

Speaker Change: Probably the best way to put it is.

Speaker Change: In terms of the revenue guide yes.

Speaker Change: The guide is still being I would say relatively conservative in terms of what we're expecting from tools. This year, so still kind of in that low.

Speaker Change: Alright, so why don't I start there so in terms of bridging the old metric to the news so the new metric.

Speaker Change: Very importantly excludes programs with de Minimis revenue in the quarter. So that would typically be a program that is either just starting.

Speaker Change: A low double digit million dollar contribution on a full year basis, and just to put that in context in the first quarter tools contributed sort.

Speaker Change: Or is in the final stages of completion, and we really in any particular quarter in the past had quite a lot of those like like we might have had you know just like rough numbers 20 to 30 programs that were in kind of a startup mode and are maybe similar number that were in a final stage of completion mode and so those would be.

Speaker Change: Sort of low single digit millions in terms of revenue so less than 10% of the cell engineering revenue in Q1 came from the tools offering and then we would expect that number to increase.

Speaker Change: As we get sort of through the year, but.

Speaker Change: It's still early days, so we're being conservative there, but I would say there is upside potential on the tool side of the business.

Speaker Change: He kind of out of the mix right now completely.

Speaker Change: Particularly on data points I think what we're learning on automation is that is a longer sales cycle.

However, it's not a straight subtract because we're now including programs that wouldn't have been included in the past because it didn't meet the sort of definition of what we thought of as a major program and so a lot of the sort of smaller data points programs or even small solutions programs wouldn't necessarily have been included in the past it all under the definition.

Mark Dmytruk: I think what we're learning on automation is that a longer sell cycle. With respect to some of the bigger, your point on biopharma, yes, I mean, I think we're happy with how we're executing on those deals right now. And I think we'll be looking to see whether or not we can kind of expand the relationships with some of those biopharma as we execute on some of the first projects that we have with them in Datapoints.

Speaker Change: With respect to some of the bigger like the by your point on Biopharma.

Yes, I mean, I think we're happy with how we're executing on those deals right now.

Speaker Change: And I think we'll be looking to.

Speaker Change: See whether or not we can kind of expand the relationships with some of those biopharma as we execute on some of the first projects that we have with them and data points.

Speaker Change: And so those are now kind of in the mix so that sort of like the rough bridge here now if you look in the appendix to the presentation. We have included.

Yes, I would say I think one of the things of the Biopharma as we can get in with a proof of concept, we were adding and continue to add like new logos, there, which is always exciting forgetting go because we have a variety of things, we can sell to people and so getting and improving ourselves and getting set up with the procurement system. At these places is all just like wins for us so that.

Jason Kelly: Yeah. I would say I think one of the things with the biopharmas is we can get in with a proof of concept. We're adding and continue to add new logos there, which is always exciting for Ginkgo because we have a variety of things we can sell to people. And so getting in and proving ourselves and getting set up with the procurement system at these places is all just wins for us. So that continues to work, the proof of concept deals. The hope is that those then grow into larger programs in data points or maybe an automation purchase. And then when it comes to the onshoring that you asked about, Tejas, I think one application there for us would be using the automation for some of the QC.

Speaker Change: E.

Speaker Change: On your second question.

Speaker Change: Continues to work like the proof of concept deals that the hope is that those then grow into larger programs and data points or maybe an automation purchase and then when it comes to the onshoring of you asked about the.

Speaker Change: Upside on tools and pharma so.

I think probably the best way to put it is in.

Speaker Change: I think one application there for us would be using the automation for some of the QC.

Speaker Change: In terms of the revenue guide yes.

Speaker Change: The guide is still being I would say relatively conservative in terms of what we're expecting from tools. This year, so still kind of in that low.

Speaker Change: So there's usually a variety of different assays that are being included in the quality control for therapeutics coming off the manufacturing those are often like can be pretty complicated experiments.

Jason Kelly: So there's usually a variety of different assays that are being included in the quality control for therapeutics coming off the manufacturing. Those often can be pretty complicated experiments and can be a good fit, depending on the drug, for some of our automation. So that's one place I think we could play. We obviously don't do. We're not a manufacturer. So you won't see us building a new site. We're not like Lonza or something. But I do think on the automation side, we could play.

Speaker Change: Low double digit million dollar contribution on a full year basis, and just to put that in context in the first quarter tools contributed sort.

Speaker Change: And I are can be a good debt depending on the drug for some of our automation. So that's one place I think we could play we obviously don't do we're not a manufacturer. So you won't see us like building a new site, we're not like alonza or something but I do think on the automation side, we could play.

Speaker Change: Sort of low single digit millions in terms of revenue so less than 10% of the sole engineering revenue in Q1 came from the tools offering and then we would expect that number to increase.

Speaker Change: As we get sort of through the year, but.

Speaker Change: Got it Super helpful. Thanks, guys appreciate the time.

Tejas Savant: Got it. Super helpful. Thanks, guys. Appreciate the time.

Still early days, so we're being conservative there, but I would say there's upside potential on the tools side of the business.

Jason Kelly: Yep.

Matt: Alright next up we have Matt <unk> from Goldman Sachs. Matt Your line is open.

Mark Dmytruk: All right. Next up, we have Matt Sykes from Goldman Sachs. Matt, your line is open.

Particularly on data points I think what we're learning on automation is that as a longer sell cycle.

Matt: Hi, this is <unk>.

Evie Koslosky: Hi. This is Evie for Matt. Thanks for taking my questions. So the first one, great to see the deal with Aura. How do you view the longer-term opportunity within the diagnostics for RACs? And then are you seeing any interest from customers in this space on a broader scale, especially given the durability of that end market versus earlier-stage R&D spending?

Matt: Taking my questions. So the first one great to see the deal with <unk>, how do you view the longer term opportunity within the diagnostics for Iraq, and then are you seeing any interest from customers in this space on the on a broader scale, especially given the durability of that end market versus earlier stage R&D spending.

Speaker Change: With respect to some of the bigger like the your point on Biopharma.

Speaker Change: Yes, I mean, I think we're happy with how we're executing on those deals right now.

Speaker Change: And I think we'll be looking to.

Speaker Change: See whether or not we can kind of expand the relationships with some of those biopharma as we execute on some of the first projects that we have with them and data points.

Matt: Yeah, we think it's a great great Pepper diagnostics I mean, what makes the racks unique compared to like a traditional integrated setup is that it is expandable.

Jason Kelly: Yeah. We think it's a great fit for diagnostics. I mean, what makes the RAX unique compared to a traditional integrated setup is that it is expandable. So when you're getting a work cell set up to do whatever your particular diagnostic reaction, you're trying to predict how much demand you have. That work cell has a certain capacity. If you start to exceed that, the current industry standard is basically build a whole nother work cell. Whereas with the RAX, you could take whatever piece of equipment it is that's your current bottleneck on your diagnostic process and just add a second one to the setup and potentially alleviate that bottleneck. So that's really exciting. It's also not something that sunsets in the event that your mix of diagnostic demand changes in the future, right?

Speaker Change: Yeah, I remember that I was hearing one of the things of the Biopharma as we can get in with a proof of concept, we were adding and continue to add like new logos, there, which is always exciting frigging go because we have a variety of things we can sell to people and so getting an improving ourselves and getting set up with the procurement system. At these places is all just like wins for us so that.

Matt: So when you are getting a workstyle set out to do whatever your particular diagnostic.

Matt: Yeah.

Matt: <unk> like you were trying to predict how much demand you have that works all has a certain capacity if you start to exceed that the current industry standard is basically built a whole another works out.

Speaker Change: It continues to work like a proof of concept deals that the hope is that those then grow into larger programs and data points or maybe an automation purchase and then when it comes to the onshoring of you asked about I ask the apps I think one application there for us and would be using the automation for some of the QC on each there's usually a variety of different.

Matt: Whereas with the racks you could take whatever piece of equipment is that your current bottleneck on your on your diagnostic process. It just add a second one.

Matt: So the setup and potentially alleviate that bottleneck. So that's really exciting. It's also not something that sunsets in the event that your mix of diagnostic demand changes in the future right. So what's great about the racks as some of the equipment is likely to be common across different protocols youre running.

Speaker Change: Assays that are being included in the in our quality control for therapeutics coming off the manufacturing those are often like can be pretty complicated experiments and I are can be a good debt depending on the drug for awesome or automation. So that's one place I think we can play we obviously don't do we're not a manufacturers or you don't you won't see us like building a.

Jason Kelly: So what's great about the RAC is some of the equipment is likely to be common across different protocols you're running. And if you had, say, a new protocol you brought online, let's say you wanted to add some sort of NGS diagnostic to your current setup, you could then add a few pieces of equipment to the very same RAC setup you had running your first protocol and add a second one. So this is, I mean, we're obviously biased, but we really think of it like you're building an automation core that can be used for lots of different things rather than a work cell that's meant to do one thing. And that's really compelling. It totally changes the ROI calculation for people building out integrated automation. So we think we should be on the RFP and the look for anybody building a new automation facility.

Matt: And you could if you had say a new protocol you brought online, let's say you wanted to add some sort of like NGF diagnostic youre current setup.

Matt: You could then add a few pieces of equipment to the very same rack setup you had running your first protocol and add a second one so this is a.

Speaker Change: Our new site, we're not like Alonza or something but I do think on the automation side, we could play.

Matt: No.

Matt: I mean look we're obviously biased, but like we really think of it like you're building in automation core that can be used for lots of different things rather than at work cell. That's meant to do one thing and that's really compelling and totally changes the ROI calculation for people building out integrated automation. So we think we should be on the RFP and the look for anybody building a new automation facility, we had to get the word out and.

Speaker Change: Got it Super helpful. Thanks, guys appreciate that Dan.

Speaker Change: Alright next up we have Mac Sykes from Goldman Sachs. Matt Your line is open.

Eliana: Hi, This is eliana format.

Eliana: Questions. So the first one great to see the deal with our how do you view the longer term opportunity within the diagnostics for Iraq, and then are you seeing any interest from customers in this space on them on a broader scale, especially given the durability of that end market versus earlier stage R&D spending.

Jason Kelly: We got to get the word out in the market. But it's really exciting to me to see us getting this first diagnostics deal. We really see ourselves able to play in that space.

Matt: The market, but it's really exciting to me to see us getting this first.

Matt: Diagnostics deal like that we really see ourselves able to play in that space.

Okay, Great and then on the EBITDA breakeven target for the end of 2026.

Evie Koslosky: Okay. Great. And then on the EBITDA breakeven target for the end of 2026, what are the areas that have you uncovered any areas of upside as you work through the cost-cutting exercises? And then on the flip side, how are you able to balance the spending to make sure that the new offerings get good initial traction commercially while also meeting the profitability goals?

Eliana: Yeah, we think it's a great great Pepper diagnostics, I mean, I mean that what makes the racks unique compared to like a traditional integrated setup is that it is expandable.

Matt: What are the areas have you uncovered any areas of upside as you work through the cost cutting exercises and then on the flip side. How are you able to balance the spending to make sure that the new offerings get good initial traction commercially while also meeting the profitability goals.

Eliana: So you know when you're getting a work cell setup to do you know whenever your particular diagnostic racks.

Eliana: Reaction like Youre trying to predict how much demand you have that works all has a certain capacity. If you start to exceed that of current industry standard is basically built a whole another works out.

Speaker Change: Jason I'd be happy to take the first part and maybe the second part over to you. So.

Mark Dmytruk: So Jason, I'd be happy to take the first part and maybe hand the second part over to you. So we do still have room to go on cost. And that's why we upped the target to $250 million. I would say, Evie, yeah, there's probably still some room after we get to that level. We largely, at this point, have taken the actions that we need to take in order to get to the $250. There's still a little bit of work to do there. So you'll start to see the impact of that part of the cost reduction roll through the kind of Q2, Q3 numbers. But we are, I think, sort of being careful at this point. And I'll let Jason just talk about the kind of new opportunities.

Speaker Change: So we do still have room to go on cost and that's why we.

Eliana: Whereas with the racks you could take whatever piece of equipment. It is that your current bottleneck honored on your diagnostic process. It just add a second one.

Speaker Change: <unk>.

Speaker Change: The target to $250 million.

To the setup in and potentially alleviate that bottleneck as natural exciting. It's also like not something that sunsets in the event that your mix of diagnostic demand changes in the future right. So what's what's great about the racks as some of the equipment is likely to be common across different protocols youre running at.

Speaker Change: I would say EV, yes, theres probably.

Speaker Change: Still some room after we get to that level, we largely at this point have taken the actions that we need to take in order to get to the $2 50, there is still a little bit of work to do there. So you'll start to see the impact of.

Speaker Change: That part of the cost reduction roll through the kind of Q2 Q3 numbers.

Eliana: And you could if you had say a new protocol you brought online, let's say you wanted to add some sort of like Engie S diagnostic to your current setup.

Speaker Change: But we are I think sort of being careful at this point, the and I'll, let Jason just talk about the kind of new opportunities I Wouldnt say, though even though there is some like very large.

Eliana: You can then add a few pieces of equipment to the very same rack setup you had running your first protocol and add a second one. So this is a you know.

Mark Dmytruk: I wouldn't say, though, Evie, there's some very large sort of silver bullet kind of upside cost reduction opportunity other than, of course, subleasing the excess space, which we all know is a challenge in this market. Other than that, we're much more into the weeds on looking at sort of small-dollar kind of line items. And that's sort of where we're at right now. There aren't these big chunks of upside anymore.

Speaker Change: I mean look we're obviously biased spotlight, we really think of it like you're building in automation core that can be used for lots of different things rather than at work cell. That's meant to do one thing and that's really compelling and totally changes the ROI calculation for people building out integrated automation. So we think we should be on the RFP and the look for anybody building and a new automation facility, we got to get the word out.

Sort of sort of silver bullet kind of upside cost reduction opportunity other than of course sub leasing the excess space, which we all know is a challenge in this market and other than that we're more we're much more into the weeds on looking at sort of small dollar kind of line items and.

Speaker Change: In the market, but it's really exciting to me to see us getting this first.

Speaker Change: That's sort of where we're at right now there aren't like these big chunks of upside anymore.

Speaker Change: <unk> diagnostics deal like that we'd be really see ourselves able to play in that space.

Speaker Change: Yeah, and just to comment on the tool side I mean, you won't see us do anything pathological and if that's the question right.

Jason Kelly: Yeah. And just a comment on the tool side. I mean, you won't see us do anything pathological if that's the question, right? So if we see opportunity where by investing in, for example, just today, we put out another sort of data drop from Datapoints for cell paintings. This is like an imaging-based dataset. So you can have bright field. You can do the cell painting. These are becoming common high-content data sources for people doing AI/ML or drug discovery, right? That's the first time we've put out a dataset like that. We love to do stuff like that. We already have a ton of interest in that, a lot of people downloading it. You'll see us keep doing that, investing in new areas for Datapoints. No-brainer.

Speaker Change: Okay, Great and then on the EBITDA breakeven target for the end of 2026.

Speaker Change: If we see opportunity where by investing in you know for example, just today, we put out another sort.

What are the areas that are you have you uncovered any areas of upside as you work through the cost cutting exercises and then on the flip side. How are you able to balance the spending to make sure that the new offerings get good initial traction correctly, while also meeting the profitability goals.

Speaker Change: Data drop from data points for sell paintings like imaging based.

Speaker Change: Datasets, you feel you can do to sell painting, either becoming like com and high content.

Speaker Change: Data sources for people doing like AI ml for drug discovery.

Speaker Change: So Jason I'll be happy to take the first part and maybe hang the second part over to you Sir.

Speaker Change: Right like that that's that's it.

Speaker Change: First time, we put out a data set like that we'd love to do stuff like that we already have a China like interest in that lot of people downloading. It youll see us keep doing that investing in new areas, where data points no brainer as long as we when we put out a new one we see new customers you won't see me stop investing and that sort of thing.

Speaker Change: So we do still have room to go on cost and that's why we.

Speaker Change: Ups the target to $250 million.

Speaker Change: I would say EV, yeah, there's probably still some room after we get to that level are we largely at this point have taken the actions that we need to take in order to get to the 250, there's still a little bit of work to do there. So you'll start to see the impact of.

Jason Kelly: As long as when we put out a new one, we see new customers, you won't see me stop investing in that sort of thing. Same with on the automation side. We see opportunities to demonstrate particular workflows and show people we put out these sort of white papers and demonstrations of what you can do on the RAC. I see a lot of upside in all those things. You won't see us slow down there just to meet an EBITDA target. But all things equal, we do see a good line of sight to getting to it by the end of 2026. So it is a focus. But a lot of it is really just tightening up on the solution side so that we have room to invest in tools. That's really the big motion.

Speaker Change: On the automation side, we see opportunities to demonstrate particular workflows and show people, we put out these sort.

Speaker Change: Sort of like White papers and demonstrations of what you can do on the racks.

Speaker Change: I see a lot of upside in all of those things are you won't see a slowdown there.

Speaker Change: That part of the cost reduction roll through the kind of Q2 Q3 numbers.

Speaker Change: Just to just to meet an EBIT target.

Speaker Change:

Speaker Change: Yes, all things equal we do see a good line of sight to getting to it and by the end of 'twenty six though it is a focus but a lot of it is really just tightening up on the solution side. So that we have a room to invest in tools that that's really the big motion.

Speaker Change: But we are I think sort of being careful at this point, the and I'll, let Jason just talk about the kind of new opportunities I Wouldnt say, though EV, there's some like very large.

Speaker Change: Sort of sort of silver bullet kind of upside cost reduction opportunity other than of course sub leasing the access space, which we all know is a challenge in this markets and other than that we're more we're much more into the weeds on looking at sort of small dollar kind of line items and that's all.

Speaker Change: Okay. Thank you so much.

Evie Koslosky: Great. Thank you so much.

Speaker Change: Yes. Thank you.

Mark Dmytruk: Yeah. Thank you. I think we have one last question. I saw another pop up. I think we probably just have time for one more from Matt Larew, who's coming to us from William Blair.

Speaker Change: I think we have one last question I saw another pop up but I think we probably just have time for one more from Matt Larew.

Speaker Change: Coming to us from William Blair.

Speaker Change: Hey, Matt.

Jason Kelly: Hey, Matt.

Speaker Change: Hey, good afternoon. Thanks second question, just if I think back to <unk>.

Tejas Savant: Hey. Good afternoon. Thanks for taking the question. Jason, if I think back to 2023, 2024, when there were perhaps different but in some way similar macro constraints with respect to biotech funding, you really were selling more.

Speaker Change: Where we're at right now there aren't like these big chunks of upside anymore.

Speaker Change: 'twenty three 'twenty four when they were perhaps different but somewhat similar macro constraints with respect of biotech funding.

Speaker Change: And just a comment on the tool side I mean, you won't see us do anything pathological and if that's the question right likes it so that if we see opportunity where by investing in you know for example, just you know today, we have we put out another sort of data drop from data points for sell painting Zaikai imaging based.

Speaker Change: You really.

Speaker Change: And sometime you know well we have about three.

Jason Kelly: You're just dead sometime.

Speaker Change: Three weeks of positivity at the beginning of this year.

Tejas Savant: Well, we have like 3 weeks of positivity at the beginning of this year. You were really selling 1 or at least just a couple of solutions. The contract structure was perhaps more onerous to get deals done in terms of longer lead times. And there was maybe more of a focus on biopharma. So I know that remains today. If I then fast-forward to today and maybe we're entering more macro uncertainty from a variety of different angles, you now have a number of different product offerings that span content, tools, automation, etc. You've opened up the way you're thinking about doing deals and different sizes and structures. But you also alluded to in your earlier comments this sort of inherent push-pull between the willingness to outsource.

Speaker Change: You were really selling one or at least a couple of solutions.

Contract structure was perhaps more onerous to get deals done in terms of longer lead times.

Speaker Change: Data Sachi bright field, you can do to sell painting, either becoming like com and high content.

Speaker Change: And there was maybe more of a focus on biopharma.

Speaker Change: Data sources for people doing like AI ml for drug discovery.

Speaker Change: All that remains today, if I then fast forward to today and maybe what we're entering.

Speaker Change: More macro uncertainty from a variety of different angles.

Speaker Change: Like that's it that's the first time, we put out a data set like that we'd love to do stuff like that we already have a ton of my interest and that a lot of people downloading edge, you'll see us keep doing that investing in new areas or data points no brainer as long as we when we put out a new one we see new customers you won't see me stop investing and that sort of thing.

Speaker Change: A number of different product offerings that span content tools automation et cetera is opened up the way youre thinking about doing deals.

Speaker Change: And different sizes structures, but you.

Speaker Change: You also alluded to in your earlier comments this sort of inherent push pull between the willingness to outsource.

Speaker Change: Same with like on the automation side, we see opportunities to demonstrate particular workflows and show people. We put out these sort of like white papers and demonstrations of what you can do on the racks.

Speaker Change: It does the same dollar amount means less work gets done or does it push people taking more work the work more efficiently right. So some of these pension because I'd just be curious.

Tejas Savant: Does the same dollar amount mean that less work gets done, or does it push people to do more work more efficiently, right? So some of these tensions. So I'd just be curious, either in the first couple of months of the year or what you're seeing and hearing from customers, how you think Ginkgo can fit into if this macro situation deteriorates or remains uncertain, how you fit into the picture differently this time than perhaps a couple of years ago.

Speaker Change: You know I see a lot of upside in all of those things are you won't see a slowdown there.

Speaker Change: Either in the first couple of months of the year or what youre seeing and hearing from customers.

Speaker Change: Just a just a meet an EBIT target, but yeah. All things equal are we do see a good line of sight to getting to it and by the end of 'twenty six though it is a focus but a lot of it is really just tightening up on the solution side. So that we have a room to invest in tools that that's really the big motion.

Speaker Change: Do you think that can fit into if this macro situation deteriorates remains uncertain, how you fit into the picture differently. This time than perhaps a couple of years ago.

Speaker Change: Yeah, I mean, I think the biggest thing is with the tools offering like you can you can like take smaller bites and engage with US right like the what I would have had 23 24, where there was really only way to deal with ginkgo is the sort of big R&D projects.

Jason Kelly: Yeah. I mean, I think the biggest thing is with the tools offering, you can take smaller bites and engage with us, right? What I would have had 2023, 2024 was the really only way to deal with Ginkgo was these sort of big R&D projects, that type of big outsourced R&D work across the industry. Pick your favorite small biotech in Cambridge. It's not getting a large research partnership right now with major pharmas or midsize pharmas. So that's just the reality, right? So I think the thing we've done well in the last year, and again, I think this continues to speak to A, the flexibility of the platform we built at Ginkgo, where really the core heart of it is sort of a lot of this automation and software infrastructure and approaching a biolab like a factory.

Speaker Change: Okay. Thank you so much.

Speaker Change: Yeah. Thank you.

Speaker Change: I think we have one last question I saw another pop up but I think we probably just have time for one more from Matt Larew is.

Speaker Change: He's coming to us from William Blair.

Speaker Change: That type of big outsourced R&D work across the industry like pick your favorite small biotech in Cambridge, it's not getting like a large research partnership right now with like major farmers or midsize farmers. So that that's just the that's just the reality right. So I think the thing we've done well in the last year and again I think this continues to speak to a the flexibility.

Speaker Change: Hey, Matt.

Speaker Change: Hey, good afternoon. Thanks second question, just if I think back to <unk>.

Speaker Change: 'twenty three 'twenty four when they were perhaps different but somewhat similar macro constraints with respect of biotech funding.

Speaker Change: You really where he'd like to add in some time.

Speaker Change: We have three weeks of positivity of the beginning of this year.

Speaker Change: <unk> of the platform, we built that ginkgo, we're really like the core heart of it is sort of a lot of this automation and software infrastructure and approaching our biolab like a factory that's brewing like very durable to be undertaken different directions, all the way from industrial biotech.

Speaker Change: You were really selling one or at least I have just a couple of solutions. The the contract structure was perhaps more onerous to get deals done in terms of longer lead times.

Jason Kelly: That's proving very durable to be able to take in different directions all the way from industrial biotech, when we first would have been talking to you, through ag to pharma to now different styles, whether you're selling it as solutions and tools. I think we're tough to kill, right? I think that's sort of what's been proven over the last couple of years here at Ginkgo. So I think that speaks to the strength of the platform. I do think there is some looking for silver linings whenever there's churn, right? Right now, for example, with the FDA, you're seeing a lot of interest around changing how we approach things like toxicology with the government in general, a lot of issues around how we're approaching other countries, particularly China, doing our work. I mean, look, if WuXi gets nuked, that's a huge opening for us, right?

Speaker Change: And there was maybe more of a focus on biopharma.

Speaker Change: When we were first would've been talking to you through ads of pharma to now different styles, whether youre selling in our solutions and tools.

Speaker Change: That remains today, if I then fast forward to today and maybe we're entering a more macro uncertainty from a variety of different angles. You now have a number of different product offerings that span content tools automation et cetera is opened up the way you're thinking about doing deals.

Speaker Change: I think like.

Speaker Change: We're we're tough to kill right I think that that's sort of what's been proven over the last couple of years here. He can go and so I think that.

Speaker Change: That speaks to the strength of the platform I would I do think there is some.

Speaker Change: And different sizes structures.

Speaker Change: But you also.

Speaker Change: Looking for silver linings like whenever there is churn right like right now like for example, with the FDA Youre seeing a lot of interest around changing how we approach things like toxicology.

Speaker Change: That puts people taking more work the work more efficiently right. So some of these pension so I'd just be curious either in the first couple of months of the year or what youre seeing and hearing from customers.

Speaker Change: Do you think that can fit into if this macro situation deteriorates remains uncertain, how you fit into the picture differently. This time than perhaps a couple of years ago.

Speaker Change: With the government in general a lot of issues around how we're approaching other countries, particularly China doing our work I mean look if wuxi gets nuked, that's like that's a huge opening for us right.

Speaker Change: If it's like Hey, you can't use them.

Jason Kelly: If it's like, "Hey, you can't use them," then there's a lot of new CRO business to be had, right? So there are things there that could change the macro for Ginkgo specifically. We'll see, right? But I think what we've shown is Ginkgo's resilient. Ginkgo will change as the market changes around us. And we're not going to die, right? So that, I think, remains the case 2023 to now. But certainly, I'd say the biggest change is us going to market with tools, which is much more favorable for this current environment in terms of what customers are up for buying. Smaller chunks, more arm's length is what the market demands right now.

Speaker Change: There's a lot of new zero business to be at right. So there are things there that could change the macro.

Speaker Change: Specifically, we will see right, but I think what we've shown is getting us Brazilians ginkgo will change as the market changes around us and we're not going to die right. So so that that I think it remains the case 23 to now and then certainly the I'd say the biggest change is that is going to market with tools.

Speaker Change: That type of big outsource R&D work across the industry like you know pick your favorite small biotech and Cambridge is not getting like a large research partnership right now wed like major farmers or midsize farmers. So that that that's just the that's just the reality right. So I think the thing we've done well in the last year and again I think this continues to speak to a the flexibility.

Speaker Change: Which is much more favorable for this current environment in terms of what customers are up for buying smaller chunks.

Speaker Change: More arm's length.

Speaker Change: What the market demands right now.

Speaker Change: <unk> on the platform, we built at Ginkgo, we're really like the core heart of it is sort of a lot of this automation and software infrastructure and approaching our biolab like a factory that that crew aiming like very durable to be undertaken different directions. All the way from industrial biotech you know when we reverse would've been talking to your through Agger pharma to now different styles, whether you.

Speaker Change: Got it and then maybe.

Tejas Savant: Got it. And then, maybe as a follow-up to that, curious, the lead generation and closes for the newer programs, data points, tools, the tools offerings, are most of those internal in the sense that perhaps you were actively engaging with the customer, maybe on a broader or different project? And then that didn't work, but, "Hey, something else popped up you can do," or are most of those external at this point as people get more awareness about them?

Speaker Change: After that serious.

Speaker Change: The.

Speaker Change: Lead generation and closer for the newer programs.

Speaker Change: No data point tool that draws offerings.

Most of those internal in the sense that perhaps you were actively engaging with the customer moving on a broader different project and then that didn't work, but hey, something else that popped up you can do or are most of those external at this point as people get more awareness about them.

Speaker Change: Selling and our solutions and tools.

Speaker Change: I think like you know where were were taught to kill right I think that that sort of what's been proven over the last couple of years here again go and so I think that.

Speaker Change: It's a lot more stuff coming externally now that's what they are doing that.

Jason Kelly: It's a lot more stuff coming externally now. That's the other thing that's great about the tools business. We put these data drops up like the one we did today. And people just download it and give us the emails. We follow up. And we've gotten chunks of business that way. It's pretty neat. So that's exciting. Within our close accounts, we certainly are able to expand, right? So there's RFPs out right now for automation systems with customers that we've had multi-year engagements with on the solution side. That's obviously puts us in a really nice spot. So we do see some of that. But it's not the only source of leads. We are, again, with the tools business. And ideally, I'd actually like the tools business to keep enabling smaller and smaller bite-sized chunks, right? And so watch us over the course of the year.

Speaker Change: Great about the tools business like we put these data drops off like the one we did today and people just download it and get the E. Mails, we follow up and we've gotten chunks of business that way, it's pretty neat.

Speaker Change: That speaks to the strength of the platform I would I do think there is some you know looking for silver linings like whenever there is churn yeah right like right now like it for example at the FDA Youre seeing a lot of interest around changing how we approach things like toxicology I with you know with.

Speaker Change: So thats exciting within our closed accounts, we certainly are able to.

Speaker Change: Expand right. So like you know, there's rfps out right now for automation systems with customers that we've had multiyear engagements with on the solution side. That's obviously puts us in a really nice thoughts. So so we do see some of that but it's not the only source of Lee as we are again with the tools business and ideally I'd actually like the tools business.

Speaker Change: The government in general a lot of issues around how are approaching other countries, particularly China doing our work I mean logging if wuxi gets nuked, that's like that's a huge opening for us right like at Allergan.

It's like Hey, you can't use them.

Speaker Change: And there's a lot of new zero business to be add rides at so there are things there that could change the macro for ginkgo, specifically, we'll see right, but I think what we've shown is giggles resilient giggle will change as the market changes around us and we're not gonna die rights. So so that that I think it remains the case 23 to now but certainly.

Speaker Change: Keep enabling smaller and smaller bite sized chunks right. So watch us over the course of the year and hopefully be able to launch other things that let people by not even smaller bets because I just think that's that's what's still selling.

Jason Kelly: Hopefully, be able to launch other things that let people bite off even smaller bits, because I just think that's what's still selling. But yeah. But it is definitely we're also getting external inbound now, which is nice.

Speaker Change: And so but yes, but it is definitely we're also getting external inbound now which is nice.

Speaker Change: The edge of the biggest changes that's going to marketers with tools.

Alright, great. Thanks.

Tejas Savant: All right. Great. Thanks for the updates.

Speaker Change: No.

Jason Kelly: Yep.

Speaker Change: Which is much more favorable for this current environment in terms of what customers are upper buying smaller chunks.

Speaker Change: Unfortunately, I think we're out of time, I think I see Brendan with with his hand up Oh sure.

Mark Dmytruk: Unfortunately, I think we're out of time.

Daniel Waid Marshall: Hey, Daniel. I think I see Brendan with his hand up.

Speaker Change: More arms length is.

Jason Kelly: Oh, sure. Yeah.

Speaker Change: So I think we can fit in.

Speaker Change: Is what the market demands right now.

Daniel Waid Marshall: I think we can fit in one more for sure.

Brian: One of them for sure go ahead, Brian.

Speaker Change: Got it and then maybe.

Mark Dmytruk: Sure. Go ahead, Brendan.

Speaker Change: <unk>.

Speaker Change: After that serious.

Speaker Change: Awesome. Thanks, guys can you hear me, Okay, yes, yes.

Speaker Change: The lead.

Tejas Savant: Awesome. Thanks, guys. Can you hear me okay?

Speaker Change: Lead generation and courses for the newer programs.

Jason Kelly: Yeah.

Daniel Waid Marshall: Yep.

Speaker Change: Thanks for squeezing me in.

Tejas Savant: Awesome. Thanks for squeezing me in.

Mark Ago: Mark I don't know how you really quickly.

Jason Kelly: Mark, I don't know how you.

Speaker Change: Data point tool that draws offerings.

Tejas Savant: Maybe really quickly.

Speaker Change: And how you can do that that's amazing that's beyond my my view so yeah Brendan I appreciate the question.

Jason Kelly: I don't know how you do that. That's amazing. That's beyond my Zoom skills. So yeah, Brendan, appreciate the questions. Go ahead.

Speaker Change: Most of those in turn on the sensor, perhaps you were actively engaging with the customer will be on a broader different project and then that didn't work, but hey, you know something else that popped up you can do or are most of those external at this point as people get more awareness about them.

Speaker Change: Always happy to have Brian.

Tejas Savant: Always happy to impress. Yeah. So maybe just quickly kind of expounding on a couple of the questions previously. Really, on the AI tools offering, can you speak maybe just a little bit more on kind of the training data you're using for some of these models and really just where you're sourcing some of that from? Just because we're starting to get questions on where, as there are more offerings kind of across the sector where people are kind of sourcing a lot of this stuff from, are you able to use partner or licensee datasets to backtrain your models? Or is everything kind of proprietary and generated in-house? Really more so trying to understand how scalable some of those could be over the longer term for you guys.

Speaker Change: Yes, so maybe just quickly kind of kind of.

Speaker Change: Pounding on a couple of the questions previously.

Speaker Change: On the AI tools offering.

Speaker Change: Lamar this upcoming externally now that's what they are and that is great about the tools business like we we put these data drops off like the one we did today and people just download it and get the E. Mails, we follow up and we've gotten chunks of business that way, it's pretty neat.

Speaker Change: Can you speak maybe gets a little bit more on kind of the training data youre using for some of these models and really just where you're sourcing some of that we're starting to get questions on where there are more offerings kind of across the sector, where people are kind of sourcing a lot of stuff from Mark are you able to use partner or licensee datasets. The trade factoring your models or everything kind of propriety.

Speaker Change: So that's exciting it within our closed accounts, we certainly are able to <unk>.

Speaker Change: Expand right. So like you know, there's rfps out right now for automation systems with customers that we've had multi year engagements with us on the solution side. That's obviously puts us in a really nice spots. So so we do see some of that but it's not the only source of leads we are again with the tools business and ideally I'd actually like the tools business.

Speaker Change: Gary and generated in house.

Speaker Change: Really more so I understand trying to understand how scalable those could be over the longer term for you guys.

Speaker Change: Yeah, I can speak to that so yes, we've got a few experiments with that so just like the the models we've put out like a zero for example, which is like an ASM style model trained on our Oh at the public data plus our internal remember we acquired like work drive bio and Radian genomics I imagine.

Jason Kelly: Yeah. I can speak to that. So yeah, we've done a few experiments with this. So just so you know, the models we've put out, like A0, for example, which is an ESM-style model trained on both the public data plus our internal. Remember, we acquired WorkDrive Bio, Radiant Genomics, and Imergen. There's AgBio. There's all these genomic assets we've kind of piled up over time that are actually larger than the public dataset, I believe, at this point, or at least comparable. We trained it up on that. So that is proprietary data. I will say, I think that market's early, right? The ability to go to market as just a pure model company right now in the way that the tech companies have been able to do on the language side, I don't think is really bearing out in the market yet.

Speaker Change: Keep enabling smaller and smaller bite sized chunks, Brian. So yeah. So you know watch us over the course of the year, hopefully got a launch or other things that let people bite off even smaller bets because I just think that's that's what's still selling.

Speaker Change: AG bio there's always like genomic assets, we've kind of piled up over time that are actually larger than the public data set I believe at this point or at least comparable.

Speaker Change: And so but yeah, but it is definitely we're also getting external inbound now which is nice.

Speaker Change: Alright, great. Thank stepped it.

Speaker Change: Yes.

Speaker Change: We we trained it up on that so that is proprietary data I will say like I think that market's early right like we're not like the ability to go to market as just a pure model company right now and the way that like the tech companies have been able to do on the language side I don't think Israeli bearing out in the market yet. So that's served as like kind of a.

Speaker Change: Unfortunately, I think we're out of time, Hey, Danielle I think I see Brendan with a with his hand up Oh sure.

Speaker Change: So I think we can fit in one manner for sure sure go ahead Brian.

Brian: Awesome. Thanks, guys can you hear me, Okay Yep Yep.

Jason Kelly: So that's served as kind of an appetizer to help people come in for data points to generate their proprietary data at the large and midsize pharmas. But just going to market purely as a model, I don't really see it working in the market today. Certainly, people are trying it. We tried it. But it hasn't been a big revenue driver for us yet, unfortunately.

Mark Massaro: Thanks for squeezing me in Mark.

Brian: Mark I don't know how you really quickly.

Speaker Change: Like an appetizer to help people come in for data points like generate their proprietary data at the large mid sized pharma as well.

Brian: Or how you can do that that's amazing that it's beyond my might be asking also have run and I. Appreciate the question.

Brian: Always happy to umbrella.

Speaker Change: Mike just going to market like purely as a model I don't really see it working in the market today certainly people are trying it we tried it but.

Brian: Yeah. So maybe just quickly kind of a kind of a.

Brian: Pounding on a couple of the questions.

Brian: Italy.

Speaker Change: But it hasnt been a big revenue driver for us yet Unfortunately.

Brian: On the AI tools offering.

Speaker Change: We think they may get a little bit more on kind of the training data youre using for some of these models and really just where you're sourcing some of that in front of us the preferring to get questions on where you know and there are more offering kind of across the sector, where people are kind of forcing a lot of stuff from are you able to use partner licensee datasets. The train bacterin your models or is everything kind of proprietary.

Speaker Change: Okay, Alright, gotcha. Thanks, guys appreciate the time.

Tejas Savant: Okay. All right. Gotcha. Thanks, guys. Appreciate the time.

Jason Kelly: Yep.

Thanks Brendan.

Mark Dmytruk: Thanks, Brendan. All right. I think that's all for tonight. Just a reminder, if you have any other questions, you can always email us at investors@ginkgobioworks.com. Thanks for joining us.

Speaker Change: Alright, I think thats.

Offer Tonight, just a reminder, if you have any other questions you can always E mail us at investors I can't go <unk> Dot com, thanks for joining us.

Jason Kelly: Yep. Appreciate all the questions, everybody. Thank you.

Speaker Change: All the questions everybody. Thank you. Thank you.

Daniel Waid Marshall: Thank you. Bye.

Gary: Gary and generated in house.

Gary: Really more so I understand trying to understand how how scalable those could be over the longer term for you guys.

Gary: Yeah, I can speak to that so yeah. We've got a few experiments with essar. So just so you know like the the models we've put out like a zero for example, which is like an E. S. M style model trained on our both the public data plus our internal remember we acquired like work drive bio and Radian genomics zymogen never there.

Speaker Change: [music].

Speaker Change: Uh huh.

Gary: AD buyer, we there's always like genomic assets, we've kind of piled up over time that are actually larger than the public data set I believe at this point or at least comparable.

Gary: We we trained it up on that so that is proprietary data I will say like I think that market's early right like we're not like the ability to go to market as just a pure model company right now and the way that like the tech companies have been able to do on the language side I don't think Israeli bearing out in the market yet. So that's served as like kind of a.

Speaker Change:

Speaker Change: Yeah.

Speaker Change: I can't imagine a better and more unique type of device.

Tejas Savant: I can't imagine a better and more unique type of device than one.

Gary: Like an appetizer to help people come in for data points, a July generate their proprietary data at the large midsize farmers.

Gary: But Mike just going to market as a like purely as a model I don't really see it working in the market today certainly people are trying it we tried it but it hasn't been a big revenue driver for us yet Unfortunately.

Speaker Change: Okay, Alright, gotcha. Thanks, guys appreciate the time.

Thanks Brendan.

Speaker Change: Alright, I think that's a that's all for Tonight. Just a reminder, if you have any other questions. You can always E mail us at investors I can't go buy works Dot com. Thanks for joining us Yep Bridgette Heller question, thereby thank you. Thank you.

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