Q1 2024 Absci Corporation Earnings Call

May 14, 2024

Operator: Ladies and gentlemen, thank you for standing by. Welcome to the Absci First Quarter 2024 Business Update Call. At this time, all participants are in a listen-only mode.

Ladies and gentlemen, thank you for standing by welcome to <unk> first quarter 'twenty 'twenty for a business update call. At this time all participants are in a listen only mode. After the speaker's presentation. There will be a question and answer session to ask a session don't.

Operator: After the speaker's presentation, there will be a question and answer session. To ask a question during I apologize to ask a question during this session, you will need to press star one one on your telephone.

Apologize to ask a question. During this session you will need to press star one on your telephone you wouldn't hear an automated message advising your hand is raised to withdraw your question. Please press star. One again, please be advised that today's conference is being recorded I would like now to turn the conference over to Alex Khan Vice President.

Operator: You will then hear an automated message advising your hand is raised to withdraw your question. Please press star one one again. Please be advised that today's conference is being recorded. I would like now to turn the conference over to Alex Khan, Vice President of Finance and Investor Relations. Please go ahead.

Finance and Investor Relations. Please go ahead.

Alexander Khan: Thank you. Earlier today, Absci released financial and operating results for the quarter ended March 31, 2024. If you haven't received this news release, or if you'd like to be added to the company's distribution list, please send an email to investors@absci.com. An archived webcast of this call will be available for replay on Absci's Investor Relations website at investors.absci.com for at least 90 days after this call. Joining me today are Sean McClain, Absci's founder and CEO, and Zach Jonasson, Chief Financial Officer and Chief Business Officer.

Alexander Khan: Thank you earlier today, <unk> released financial and operating results for the quarter ended March 31, 2024. If you haven't received this news release or if you'd like to be added to the Companys distribution list. Please send an email to investors at outside dotcom and archived webcast of this call.

Alexander Khan: It will be available for replay on <unk> Investor Relations website at investors dot outside dot com for at least 90 days after this call.

Alexander Khan: Joining me today are Shawn Mcclain as is founder and CEO exactly understand Chief Financial Officer, and Chief Business Officer, Christian Steckman outsized S. P. A drug creation will also joining for Q&A following prepared remarks.

Alexander Khan: Christian Stegmann, Absci's SVP of Drug Creation, will also join for Q&A following prepared remarks. Before we begin, I'd like to remind you that management will make statements during this call that are forward-looking within the meaning of the federal securities laws. These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated, and you should not place any undue reliance on forward-looking statements.

Alexander Khan: Additional information regarding these risks, uncertainties, and factors that could cause results to differ appears in the section entitled Forward-Looking Statements in the press release Absci issued today, as well as in the documents and reports filed by Absci from time to time with the Securities and Exchange Commission. Except as required by law, Absci disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward-looking statements, either because of new information, future events, or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast on May 14, 2024. With that, I'll turn the call over to Sean.

Alexander Khan: Before we begin I'd like to remind you that management will make statements. During this call that are forward looking within the meaning of the federal Securities laws. These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated and you should not place any undue reliance on forward looking statements.

Alexander Khan: Information regarding these risks uncertainties and factors that could cause results to differ appears in the section entitled forward looking statements in the press release issued today and the documents and reports filed by upside from time to time with the Securities Exchange Commission.

Alexander Khan: Except as required by law outside disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward looking statements are there because of new information future events or otherwise. This conference call contains time sensitive information and is accurate only as of the live broadcast May 14 2024.

Alexander Khan: With that I'll turn the call over to Sean.

Sean McClain: Thanks, Alex. Good morning, and thank you to everyone for joining us today for our first business update conference call since 2021. A lot has changed since then.

Sean: Thanks, Alex Good morning, and thank you to everyone for joining us today for our first business update conference call.

Sean: 2021.

Sean: A lot has changed since then.

Sean McClain: While we have been active at investor conferences and other venues sharing our progress, we are excited to welcome you to our quarterly update call, which we'll host on a regular basis moving forward. There are a few reasons for that. Among them, we are pleased with the expansion of our shareholder base and research analyst coverage. We want to provide an open setting to share our latest progress and details and allow for interactive dialogue. Additionally, our business model previously revolved almost exclusively around partner programs, where our communication was influenced by our partners.

Sean: While we have been active at investor conferences, and other than Youre, showing our progress. We're excited to welcome you to our quarterly update call, which will host on a regular basis moving forward.

Sean: There are a few reasons for this change among them.

Sean: With the expansion of our shareholder base and research analyst coverage.

Sean: We want to provide an open starting to share our latest progress in details.

Sean: Now for interactive dialogue.

Sean: Additionally, our business model previously revolved almost exclusively around partner programs, where our communication was influenced by our partner.

Sean McClain: Our new hybrid business model, including our internal pipeline, gives us more opportunity to discuss the exciting progress we are making on each program. With that in mind, I'd like to begin with a brief recap of the achievements we made in 2023 before discussing our progress in 2024. Later in the call, Zach will provide more detail on the status and outlook for each of our internal programs and our business as a whole.

Sean: Our new hybrid business model, including our internal pipeline gives us more opportunity to discuss the exciting progress we are making on each program.

Sean: With that in mind I'd like to begin with a brief recap of the achievements. We made in 2023 before discussing our progress in 2024.

Sean: Later in the call Zach will provide more detail on the status and outlook for each of our internal programs and our business as a whole.

Sean McClain: We are often asked about our differentiating features, what sets us apart and positions us as leaders in AI drug discovery for biologics and a partner of choice across the industry. Any discussion of our integrated drug creation platform starts, "Stop with the data." The ability to generate and screen massive amounts of scalable biological data is an industry breakthrough that enables our platform to operate as it does. Based on these pillars of data to train, AI to create, and wet lab to validate, our platform is designed to continuously learn and improve as a result of our data generation capabilities and integration with our wet lab operations. Looking back on our accomplishments from the first quarter of 2024, it is clear they were only made possible due to the groundwork laid by our dedicated team in the previous year.

Sean: We are often asked about our differentiating features.

Sean: That does apart and positions us as leaders in AI drug discovery for biologics and a partner of choice across the industry.

Sean: Any discussion of our integrated drug creation platform starts and stops with the data.

Sean: The ability to generate and screening massive amounts of scalable biological data, it's an industry breakthrough that enables our platform to operate as it does.

Sean: Based on these pillars of data to train AI to create and wet lab to validate our platform is designed to continuously learn and improve as a result of our data generation capability and integration with our wet lab operations.

Sean: Looking back on our accomplishments from the first quarter of 2024 it is clear they.

Sean: Were only made possible due to the groundwork laid by our dedicated team and the previous year.

Sean McClain: The ability of our platform to rapidly design and create differentiated antibody candidates in a capital efficient manner while achieving epitope specificity is a direct result of our team's efforts through 2023. We started 2023 with the release of a foundational manuscript demonstrating a first in creating and validating de novo antibodies with zero-shot generative AI. Over the year, we expanded our models, harnessing proprietary wet lab technology to generate scalable biological data for model training and validation. We continue to build our talented team.

Sean: The ability of our platform to rapidly design and create differentiated antibody candidates in a capital efficient manner, while achieving epitope specificity is the direct result of our team's efforts through 2023.

Sean: We started 2023 with the release of a foundational manuscript demonstrating a first and creating and validating de novo antibodies with zero shop generative AI.

Sean: Over the year, we expanded our models harnessing the proprietary <unk> technology to generate scalable biological data for model training and validation, we continue to build our talented team.

Sean McClain: Optimize the organization and integrate all of our platform capabilities deeply. In line with our hybrid business model, these steps aim to leverage our platform to create a pipeline of assets and establish validating partnerships with companies like AstraZeneca and Almoral. In October of last year, at our inaugural R&D day, we reached a pivotal moment by unveiling our internal pipeline of asset programs, including potential best-in-class and first-in-class antibody programs. We are excited to continue advancing each of these programs, which Zach will be discussing in greater detail later.

Sean: Optimize our organization and integrate all of our platform capabilities deeply.

Sean: In line with our hybrid business model. These hubs aims to leverage our platform to create a pipeline of assets and established validating partnerships with companies like Astrazeneca and overall.

Sean: In October of last year at our inaugural R&D day, we reached a pivotal moment by unveiling our internal pipeline of asset programs.

Sean: <unk> potential best in class and first in class antibody programs.

Sean: We are excited to continue advancing each of these programs, which <unk> will be discussing in greater detail later.

Sean McClain: But stepping back, it is humbling and gratifying to see the translation of an idea using generative AI with our platform to create differentiated antibody candidates into reality. We demonstrate our platform's ability to create differentiated antibodies, like ABS-101, our anti-TL1A antibody program, with potential best-in-class properties in a very time- and capital-efficient manner compared to industry standards.

Sean: But stepping back is humbling and gratifying to see the translation of an idea using generative AI with our platform to create differentiated antibody candidates.

Sean: To reality.

Sean: We demonstrated our platform's ability to create a differentiated antibody like AVX 101, our anti <unk> antibody program with potential best in class properties in a very time and capital efficient manner compared to industry standards.

Sean McClain: At the beginning of 2024, we unveiled positive preclinical data for this program, and by the end of February, we initiated our IMD needling study. As we advance this program, I want to highlight our platform's efficiency in generating this program and its potential wide implications. In just 14 months, we generated and selected our drug candidate at a cost of less than $5 million. ABS 101 is an early example of the power of our platform.

Sean: At the beginning of 2024, we unveiled positive preclinical data for this program by the end of February we initiated our IND, enabling studies.

Sean: As we advance this program I want to highlight our platforms efficiency in generating this program and the potential vast implications.

Sean: And just 14 months, we generated and selected our drug candidate at a cost of less than $5 million.

<unk> hundred one is an early example of the power of our platform and we see additional opportunity to demonstrate similar results through.

Sean McClain: And we see additional opportunities to demonstrate similar results through our other current and future pipeline programs. At a high level, our platform unlocks the potential for a powerful, novel biotech business model. For example, we could generate a differentiated antibody candidate and complete IND-enabling studies at a cost of approximately $15 million.

Sean: Our other current and future pipeline programs.

Sean: At a high level our platform unlocks the potential for a powerful novel biotech business model.

Sean: We could generate a differentiated antibody candidate and complete IND, enabling studies at a cost of approximately $15 million.

Sean McClain: This could enable a new paradigm in biotech, where capital typically allocated for one asset could be spread across multiple candidates, improving the overall probability of success. In addition to applying our platform to our internal pipeline, we are encouraged by the industry reception, including recent partnerships with industry leaders. It is humbling to count companies like Merck and AstraZeneca among our partners who bring invaluable talent, skill, and expertise to our collaboration. This year and beyond, we look forward to entering into additional partnerships with pharmaceutical and biotech companies.

Sean: This could enable a new paradigm and biotech where capital typically allocated for one asset could be spread across multiple candidates improving the overall probability of success.

Sean: In addition to applying our platform to our internal pipeline, we are encouraged by the industry reception.

Sean: Including recent partnerships with industry leaders.

Sean: It's humbling to account companies like Merck and Astrazeneca, among our partners, who bring invaluable talent scale and expertise to our collaborations.

Sean: This year and beyond we look forward to entering into additional partnerships with pharma and biotech companies.

Sean McClain: These partnerships will leverage our platform to enable and advance their drug discovery programs by potentially shortening timeframes, lowering costs, improving success probabilities, and unlocking new biologies previously thought unachievable. I'm incredibly proud of our team at Absci for these achievements and excited to see the promise of our platform applied to further internal programs demonstrating the potential for disruptive improvements in biotech economics. At Absci, we come to work every day with a mindset focused on innovation and continuous improvement. We are driven by our mission to create better biologics for patients faster. A few months ago, we decided to further strengthen our balance sheet and capital position through an underwritten public offering of common stock.

Sean: These partnerships will leverage our platform to enable and advance their drug discovery programs.

Sean: Centrally shortening timeframes lowering costs, improving success probabilities and unlocking new biology previously thought unachievable.

Sean: I'm incredibly proud of our team at outside for these achievements and excited to see the promise of our platform of flights are further internal programs demonstrating the potential for disruptive improvements and biotech economics.

Sean: At <unk>, we come to work every day with a mindset focused on innovation and continuous improvement.

Sean: We are driven by our mission to create better biologics for patients faster.

Sean: A few months ago, we decided further strengthen our balance sheet and capital position through a underwritten public offering of common stock. We were encouraged by the positive reception and support from a large and diverse group of investors, both new and existing.

Sean McClain: We were encouraged by the positive reception and support from a large and diverse group of investors, both new and existing. This support will help us continue to pursue our vision. As we look ahead to the rest of the year, I'm very excited about what lies ahead. We remain laser focused on execution across all aspects of our business, including partnered and internal programs. Innovation and the pursuit of the impossible are at the core of everything we do. With that, I'll turn the call over to Zach to walk through each of our programs, provide our outlook, and give an update on our financials. Zach?

Sean: This support will help us continue to pursue our vision as we look ahead to the rest of the year I am very excited about what lies ahead, we remain laser focused on execution across all aspects of our business, including partnered and internal programs with.

Sean: With innovation and the pursuit of the impossible at the core of everything we do.

Sean: With that I'll turn the call over to Don to walk through each of our programs provide our outlook and get an update on our financials.

Sean: Zach.

Zachariah Jonasson: Thanks, Sean. As Sean discussed, this past quarter, we closed an underwritten public offering of common stock, raising gross proceeds of approximately $86.4 million. This additional capital will further support our ability to advance our internal pipeline of asset programs. This strategy reflects the hybrid business model that we introduced last year, wherein we intend to develop our internal programs to a certain value at certain value inflection points, for example, through a phase one or potentially phase two clinical trial before selling, partnering, or out licensing said asset.

Don: Thanks, Sean.

Don: Shawn discussed this past quarter, we closed an underwritten public offering of common stock raising gross proceeds of approximately $86 4 million.

Don: This additional capital will further support our ability to advance our internal pipeline of asset programs.

Don: This strategy reflects the hybrid business model that we introduced last year.

Don: And we intend to develop our internal programs to a certain value to certain value inflection points. For example, through a phase one or potentially phase III clinical trial before selling partnering or out licensing set asset.

Zachariah Jonasson: A primary rationale for our strategy stems from our platform's ability to create differentiated antibody drug candidates in a highly efficient manner. We believe our strategy will allow us to create and capture more of the overall value of these internally generated programs. However, as we have said in the past, every program is unique, and there is no one-size-fits-all strategy for these assets.

Don: A primary rationale for our strategy stems from our platform's ability to create differentiated antibody drug candidates in a highly efficient manner.

Don: We believe our strategy will allow us to create and capture more of the overall value of visa term internally generated programs.

Don: As we have said in the past every program is unique and there is no one size fits all strategy for these assets.

Don: As the best practice and guidance strategy, we will look for the right partner at the right time.

Don: As Shawn mentioned earlier, we generated the ABS 101 candidate.

Don: And just 14 months at a cost of less than $5 million by.

Don: By comparison pharma industry estimates.

Zachariah Jonasson: We have seen pin such figures at three plus years to reach a drug candidate and at a cost of $30 to $50 million. And as our platform continues to improve via our data generation and screening cycles, we believe over time that we will even further reduce the time it takes us to generate additional drug candidates. Turning back to our current internal program pipe,

Don: We are seeing pin such figures at three plus years to reach a drug candidate and at a cost of $30 to $50 million.

Don: And as our platform continues to improve via our data generation and screening cycles.

Don: We believe over time that we will either even further reduce the time it takes us to generate additional drug candidates.

Don: Turning back to our current internal program pipeline.

Zachariah Jonasson: Our lead program, ABS 101, is a potential best-in-class anti-TL1A antibody. In January, we presented early preclinical data from three advanced leads from this program. This data showed property that is consistent with a potentially superior product profile, including demonstrated high affinity, high potency, favorable developability, and extended half-life. We used our de novo AI model to design ABS-101 leads towards a specific epitope of TL1A with the objective of creating a drug candidate with superior potency and lower immunogenicity.

Don: Our lead program <unk> 101.

Don: <unk> best in class anti <unk> antibody in January we presented early preclinical data.

Don: Three advanced leads from this program. This data showed properties consistent with a potentially superior product profile, including demonstrated high affinity high potency favorable bulk ability and extended half life.

We used our de Novo AI model to design AVX 101 leads towards a specific epitope of <unk> with the objective of creating a drug candidate with superior potency and lower Immunogenicity.

Zachariah Jonasson: This target product profile, combined with anticipated high bioavailability, can ultimately improve patient experience with easier, less frequent dosing. Following further confirmatory PK studies, in February, we selected a primary and a backup development candidate to advance into IND-enabling studies. We have also recently completed studies demonstrating the ability of the ABS 101 candidates to bind both the TL1A monomer and trimer, which could potentially lead to differentiated clinical efficacy

Don: This target product profile combined with anticipated high bioavailability could ultimately improve patient experience with easier less frequent dosing.

Don: Following further confirmatory PK studies in February we selected a primary and a backup development candidates to advance into IND, enabling studies.

Don: We also recently completed studies, demonstrating AVX 101 candidates ability to bind both the <unk> monomer and tremor.

Don: Which could potentially lead to differentiated clinical efficacy.

Zachariah Jonasson: We plan to share additional preclinical data, including data from non-human primate studies, in the next few months. We then expect to initiate Phase I clinical studies in early 2025, with an interim data readout expected in the second half of 2025. Next, AVS-201, a potentially best-in-class antibody for an undisclosed dermatological target, is designed for an undisclosed dermatological indication with significant unmet need where the efficacy of the pharmacological standard of care is not satisfactory.

Don: Plan to share additional preclinical data, including data from nonhuman Primate studies in the next few months.

Don: We then expect to initiate phase one clinical studies in early 2025 with an interim data readout expected in the second half of 2025.

Don: Next ABS tool, one a potentially best in class antibody.

Don: An undisclosed dermatology target is designed for an undisclosed dermatological indications with significant unmet need.

Don: Where the efficacy for the pharmacological standard of care is not satisfactory, we anticipate selecting a development candidate for this program in the second half of 2024.

Zachariah Jonasson: We anticipate selecting a development candidate for this program in the second half of 2024. Finally, ABS-301, a potentially first-in-class antibody for an undisclosed immuno-oncology target, is a fully human antibody designed to bind to a novel target discovered through our reverse immunology platform. This antibody inhibits an immunosuppressive cytokine and is believed to stimulate an innate immune response.

Don: Finally, ABS 301, and potentially first in class antibody for an undisclosed immuno oncology target.

Don: As a fully human antibody designed to bind to a novel target discovery through our reverse immunology platform.

Don: This antibody inhibits an immunosuppressive cytokines and is believed to stimulate an innate immune response.

Zachariah Jonasson: ABS 301 is being evaluated for broad applicability to a variety of oncology indications, and comprehensive profiling of this program is in progress. We anticipate completion of mode of action validation studies for this program in the second half of 2024. As a reminder, our Reverse Immunology Platform is designed to discover novel antibody targets based on the analysis of tertiary lymphoid structures, or TLSs, from patient tests. Within this platform, we mine antibody repertoires from TLS samples derived from patients who have exhibited an extraordinary immune response. We discovered the novel human antibody, ABS-301, and its corresponding target using this platform.

Don: <unk> 301 is being evaluated for broad applicability to a variety of oncology indications and comprehensive profiling profiling of this program is in progress.

Don: We anticipate completion of the motive action validation studies for this program in the second half of 2024.

Don: As a reminder, our reverse immunology platform is designed to discover novel antibody targets based on the analysis of tertiary lymphoid structures or Tls is from patient samples.

Don: Within this platform, we mined antibody repertoires from the Tls samples derived from patients who have exhibited extraordinary immune response.

Don: Okay.

Don: We discovered <unk>.

Don: <unk> 301 novel human antibody and its corresponding target using this platform. We look forward to sharing additional details later this year.

Zachariah Jonasson: We look forward to sharing additional details later this year. In addition to further development of ABS 101, ABS 201, and ABS 301, we continue to expect to advance at least one additional internal asset program to the lead stage in 2024. In line with our hybrid business model, we continue to execute and make solid progress on our existing drug creation partnership. I am pleased to see the close collaboration between our partners and our own R&D team.

Don: In addition to further development of ABS 101, ABS 201, and <unk> 301, we continue to expect to advance at least one additional internal asset program to a lead stage in 2024.

Don: Further in line with our hybrid business model, we continue to execute and make solid progress on our existing drug creation partnerships I am pleased to see the close collaboration between our partners and our own R&D teams.

Zachariah Jonasson: And while we cannot disclose much detail about our partnered program, the work we are doing with these partners is progressing well and according to our expected timeline. We look forward to sharing more details about these programs at a later date.

Don: And while we cannot disclose much detail about our partnered programs.

Don: The work we are doing with these partners is progressing well and according to our expected timelines we.

Don: We look forward to sharing more details about these programs at a later date.

Don: Additionally, we continue to anticipate finding additional drug creation partnerships with at least four partners in 2024, including one or more multi program partnerships. I'm also pleased to share that we have a robust and diverse pipeline of potential partners and we look forward to updating you on these over the course of the year.

Zachariah Jonasson: Additionally, we continue to anticipate finding additional drug creation partnerships with at least four partners in 2024, including one or more multi-program partners. I'm also pleased to share that we have a robust and diverse pipeline of potential partners, and we look forward to updating you on these over the course of the year. Turning now to our financials, revenue in the first quarter of 2024 was $900,000 as we continue to progress our partnered and internal programs concurrently.

Don: Turning now to our financials revenue in the first quarter of 2024 was $900000 as we continue to progress our partnered and internal programs concurrently.

Zachariah Jonasson: Research and development expenses in the first quarter of 2024 were $12.2 million, as compared to $12.7 million in the prior year period. This decrease was primarily driven by lower personnel costs, offset by an increase in stock compensation expense.

Don: Research and development expenses in the first quarter of 2024 were $12 2 million as compared to $12 7 million in the prior year period.

Don: Decrease was primarily driven by lower personnel costs offset by an increase in stock compensation expense.

Zachariah Jonasson: Selling General and Administrative Expenses were $8.7 million in the first quarter of 2024 as compared to $9.6 million in the prior year period. This decrease was due to lower personnel costs and continued reduction in administrative costs offset by an increase in stock compensation expenses. Turning to our balance sheet, we ended the quarter with $161.5 million in cash, cash equivalents, and short-term investments, as compared to $97.7 million as of December 31, 2023.

Don: Selling general and administrative expenses were $8 7 million in the first quarter of 2024 as compared to $9 6 million in the prior year period.

Don: This decrease was due to lower personnel costs and continued reduction in administrative costs offset by an increase in stock compensation expense.

Don: Turning to our balance sheet, we ended the quarter with $161 5 million in cash cash equivalents and short term investments as compared to $97 7 million as of December 31, 2023.

Zachariah Jonasson: For 2024, we continue to expect a gross use of cash, cash equivalents, and short-term investments of approximately $80 million, inclusive of the expected costs associated with completing the IND enabling studies for ABS 101 with a third-party CRO. Based on our current plans, we believe our existing cash, cash equivalents, and short-term investments will be sufficient to fund our operations into the first half of 2027. Altogether, we are very encouraged by the progress we have made on our internal programs and confident in our ability to execute on these and our partner programs over the course of 2024 and beyond. With that, I'll turn it back to Sean.

Don: For 2024, we continue to expect a gross use of cash cash equivalents and short term investments of approximately $80 million.

Don: <unk> of the expected costs associated with completing the IND, enabling studies for <unk> hundred one with a third party CRO.

Don: Based on our current plans, we believe our existing cash cash equivalents and short term investments.

Don: Will be sufficient to fund our operations into the first half of 2027.

Don: Altogether, we are very encouraged by the progress we have made on our internal programs and confident in our ability to execute on these and our partnered programs over the course of 2024 and beyond.

Don: With that I'll turn it back to Sean.

Sean McClain: Thanks, Zach. 2023 was a pivotal and successful year for Absci and our company's evolution. In 2024, we will continue to focus on execution and further demonstrate the power of our platform to create differentiated antibody assets. We are thrilled to advance each of our programs with the goal of creating better medicines for patients faster and fundamentally improving the economics of biotech. We look forward to updating you along the way. With that, I'll turn it back to the operator to begin Q&A. Operator.

Sean: Thanks Zack.

Sean: Q3 was a pivotal and successful year for <unk> in our company's evolution in 2024, we will continue to focus on execution and further demonstrate the power of our platform to create differentiated antibody assets.

Sean: We are thrilled to advance each of our programs with the goal of creating better medicines for patients faster and fundamentally improving the economics of biotech we've.

Sean: We look forward to updating you along the way.

Speaker Change: With that I'll turn it back to the operator to begin Q&A.

Speaker Change: Operator.

Speaker Change: Thank you.

Speaker Change: As a reminder to ask a question. Please press star one one on your telephone and wait for your name to be announced to withdraw your question. Please press star one again.

Operator: Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. One moment for the first question. The first question comes from Kripa Devrakonda with Truist Securities. Your line is open. Hey guys, thank you so much for taking my question. I have a question about ABS 101.

Speaker Change: One moment for the first question.

Speaker Change: Our first question comes from Crippa, Debra <unk> with <unk> Securities. Your line is open.

Debra Crippa: Hey, guys. Thank you so much for taking my question I have a question about AVX 101, we recently saw exciting preclinical data from the program.

Unknown Attendee: You know, we recently saw exciting preclinical data from the program. I was just wondering what your level of confidence is that this drug is differentiated versus the other drugs in the same class. You know, do we truly understand the biology about the importance of targeting monomer versus trimer? And what sort of an edge do you have in understanding that part of it?

Just wondering if you can talk about your level of confidence that this drug is differentiated versus the other.

Debra Crippa: The drug in the same class.

Debra Crippa: Do you do we truly understand the biology about the importance of targeting monomer versus trying more and what does it have an edge do you have in understanding that quite a bit.

Speaker Change: And then I have a follow up question.

Sean McClain: And then I have a follow-up question. Yeah, absolutely. Thank you, Kripa. I'll hand that over to Christian to talk about the differentiated properties that we see with TL1A and, in particular, monomer versus trimer.

Speaker Change: Yes, absolutely I think you're correct.

Speaker Change: I hand over to Christian to talk about the differentiated properties that we see what the tier one and in particular with the monomer versus primer.

Christian Stegmann: Yeah, thank you, Sean. Absolutely. First off, we do think that our extended half-life is an absolutely critical and very differentiated parameter that will address patient convenience topics, but more importantly, also on the monomer-trimer question, I think it's important to highlight that our AI-guided antibody design strategy is really based on epitope-specific targeting using 3D structures, and specifically for 3D structures of Tier 1a. So we selectively chose an epitope on the monomer that So we completely avoid epitopes that span multiple subtypes.

Christian Stegmann: Yes. Thank you Shaun absolutely first off we do think that our extended half life is an absolutely critical.

Christian: Very differentiated.

Christian: Later, we'll address patient convenience topics, but more importantly also on the <unk> question I think it's important to highlight that our AI got it.

Christian: Antibody design strategy is really based on epitope specific targeting using <unk> structures.

Christian: Specifically for <unk> structures of tier one eight so.

Christian: We selectively chose an epitope on the monomer.

Christian: That shows no discrimination for melanoma versus <unk> binding and we designed antibodies using AI.

Christian: Avoid epitopes that span multiple sub units.

Unknown Attendee: This allowed us to produce a development candidate that equally targets both PL1A states, and it also addresses, to our knowledge, all known monomer isomers. This may have relevance in clinical trials because it's known that certain monomers are expressed differentially in a certain patient. Great, thank you so much. Sean, I have a question for you, a bigger picture question. You were talking about, you know, using generative AI models. I was just wondering, with the improved generative AI models and new data, do you think you can continue to improve efficiency and reduce the drug development timelines?

Christian: And this allowed us to produce a development candidate that equally targets both tier one any states.

Christian: And it also addresses to our knowledge all known <unk> isoforms. This may have relevance in clinical trials.

Christian: Because it's known that certain monomers are expressed differentially in certain patient populations.

Speaker Change: Great. Thank you so much John I have a question for you a bigger picture question.

Speaker Change: We're talking about.

Speaker Change: Zing generative AI models I was just wondering with the improved generative AD models and new data do you think you can continue to improve efficiency and reduce the John development timelines I know.

Unknown Attendee: I know, you know, 14 months is already great, and $5 million to develop a drug is already great, but just wondering about that. Thank you. Absolutely. As the models get more and more accurate with the more data we're training and as we continue to improve the AI architectures and our models, we do see these timelines continuing to decrease over time, and the overall cost decreasing.

Speaker Change: 14 months.

Speaker Change: Are there any greater than $5 million does that John consolidated great, but just wondering about that thank you.

Speaker Change: Yes, absolutely as the models get more and more accurate way for more data we're training them.

Speaker Change: As we continue to improve.

Speaker Change: The AI architectures in our models, we do see these timelines continuing to decrease over time and the overall cost.

Speaker Change: Decrease in and this is a very important metric for us inter.

Sean McClain: And this is a very important metric for us internally, these cycle times. And you are going to continue to see, over time, these overall costs decrease, both on how long it takes us to get to a drug candidate, as well as the overall cost associated with generating a drug candidate. So do expect that in the future. Thank you so much.

Speaker Change: Internal way of these these cycle times and you are going to continue to see over time.

Speaker Change: <unk> overall cost decrease both on how long it takes us to get to a drug candidate as well as the overall costs associated with generating a drug candidate. So do you expect that in the future.

Speaker Change: Great. Thank you so much.

Speaker Change: One moment for the next question.

Operator: One moment for the next question. The next question comes from George Farmer with Scotiabank. Your line is open. Hi, good morning, everyone. Thanks for taking my question. I was wondering if you could...

Speaker Change: Next question comes from George Farmer with Scotiabank. Your line is open.

George Farmer: Hi, Good morning, everyone. Thanks for taking my question I was wondering if you could.

George Farmer: This is a heads up on what, Absolutely. Christian, do you want to take this? Yeah, absolutely. So our non-human primate pharmacokinetic studies are expected to demonstrate that we are indeed able to show an extended half-life of our antibody, thus de-risking the pharmacokinetic profile. So in the next few months, we'll be able to demonstrate that our antibody engineering approach to extend the half-life of the antibody has worked. Okay, anything else from those studies we should be looking out for, PD markers, anything like that? Yes, we will absolutely measure the non-pharmacodynamic marker as well, obviously. And exactly as you mentioned, demonstrating an extended effect on the pharmacodynamic biomarker will then obviously also de-risk efficacy. And then, maybe, on cash.

George Farmer: Give us a heads up on what we can expect to see from the non human to human Primate studies ongoing with <unk> hundred one later this year.

George Farmer: Yes, absolutely Christian do you want to take that.

Christian: Yes, absolutely.

Christian: So.

Christian: Our non human Primate pharmacokinetics studies are expected to demonstrate that.

Christian: We indeed are able to show an extended half life of our antibody thus derisking.

Christian: Pharmacokinetic profile in humans. So we in the next few months, we'll be able to demonstrate that our.

Christian: Antibody engineering approach to extend the half life with the antibody has worked.

Speaker Change: Okay anything else from those studies, we should be looking out for the PD markers or anything like that that can kind of shed light on the differentiation of the antibody from competitors.

Speaker Change: Yes, we will absolutely measure the non pharmacodynamic marker as well obviously.

Speaker Change: Exactly as you mentioned.

Speaker Change: Demonstrating and extend that effect on the Pharmacodynamic biomarker will then obviously also de risk efficacy.

Speaker Change: Very good point.

Speaker Change: Okay great.

Speaker Change: Great and then maybe.

Speaker Change: On on cash.

Christian Stegmann: Your guidance implies. I think some funding will come in probably from partnerships, and best guests. Can you kind of elaborate a little bit more on that relative to how we should think about casting?

Speaker Change: Your guidance implies.

Speaker Change: I think some.

Speaker Change: You're funding coming in probably from partnerships is probably the best guess can you kind of elaborate a little bit more on that.

Speaker Change: Relative to how we should think about cash you should see through 2027.

George Farmer: Yeah, we do. Yeah, go for it, Zach. Yeah, I was gonna say, George, we continue to reiterate our guidance of 80 million gross cash usage for 2024. That's obviously a gross figure, and that includes the complete cost associated with completing the IED enabling studies for ABS 101. Unknown Speaker Our forecast that takes us into 2027 includes some modest assumptions around partnering on a regular cadence, but it doesn't include any assumptions around a significant partnership.

Speaker Change: Yes.

Speaker Change: Yes go for it.

George Farmer: Yes, I was going to say George.

Speaker Change: Continue to reiterate our guidance of $80 million of gross cash usage for 2024.

George: It's obviously a gross figure and that includes the complete the costs associated with completing the IND, enabling studies for <unk> hundred one.

George: Our forecast that takes us into.

George: 2027 include some modest assumptions around partnering on a regular cadence, but it doesn't include any assumptions around a significant partnership deal.

George Farmer: So it's kind of our typical run rate assumptions built. And then I would point out, too, if you look at our net cash usage, that typically comes in well under growth. So for example, if you look at H2 of 2023, the net cash usage for the second half of last year was roughly 27 million in total. And then cash usage for Q1 of this year was roughly 16.9 million, which is a little higher given that we paid bonuses in March.

George: So it's kind of our typical run rate assumptions built into that.

Speaker Change: Okay, and then I would point out too if you look at our net cash usages.

Speaker Change: Typically comes in well under growth. So for example, if you look at H two of 2023.

Speaker Change: Net cash usage for the second half of last year was roughly $27 million in total.

Speaker Change: Net cash usage for Q1 of this year was roughly $16 9 million, which is a little higher given that we paid bonuses in March. So you can see our net cash used units was coming well in coming well under the gross cash.

Zachariah Jonasson: So you can see our net cash usage is coming well in, coming well under the gross cash. Thanks very much. One moment for the next question. The next question comes from Jacqueline Kisa with TV Cohen. Your line is open.

Speaker Change: Usage.

Zack: Okay. Thanks, very much Zack.

Speaker Change: One moment for the next question.

Jacqueline: The next question comes from Jacqueline keeps up with TV kind of when your line is outstanding.

Unknown Attendee: Hi, this is Jacqueline Kisa on behalf of Stephen Ma. Thanks so much for taking the questions. With ongoing bipartisan discussions regarding biosecurity, can you give us any color on the third-party CRO you're using for your IND studies? Is it Wuxi Biologics or a China-based CRO? Yeah, that's a great question.

Jacqueline: Hi, This is Jacqueline Keith on for Steven MA. Thank so much for taking the questions.

Jacqueline Keith: Ongoing bipartisan discussions regarding bio security can you give us any color on the third party CRM you are using for your IND studies is at Wuxi, biologics or China based CRM.

Sean McClain: We are using WUSHI at the current moment. And given the recent discussions that have been ongoing with that, we do believe that the relationship with WUSHI will not put us at risk with the current program. But we are engaging with other CROs and do have backup strategies to, you know, mitigate any other potential tailwinds that may occur with new legislation that may come out. Great, thank you. I appreciate the color.

Steven MA: Yes, that's a great question, we are using <unk>.

Steven MA: <unk>.

Speaker Change: Current moment.

Jacqueline Keith: And given the recent discussions that have been ongoing with that we do believe that the relationship with Wuxi will not.

Wuxi: Put us at risk with the current program, but we are engaging with other <unk> and you have backup strategies.

Wuxi: Two.

Speaker Change: Mitigate any other potential tailwind that may occur.

Speaker Change: With new legislation that may come out.

Sean McClain: And regarding your fourth internal asset, can you give us any insight on the disease area you're looking to focus on? Is it one you've targeted for a new therapeutic area? And is the company the right size to serve both your internal and partnered programs? Yeah, it's a great question.

Speaker Change: Okay.

Speaker Change: Great. Thank you I appreciate the color.

Speaker Change: And regarding your fourth internal asset can you give us any insight onto the disease area Youre looking to focus on is that when you've targeted for a new therapeutic area and as the company right size to serve both their internal and partnered programs.

Sean McClain: So we are focused on INI as well as oncology. So we'll fall into one of those therapeutic areas. And additionally, we are currently right-sized to continue to take on more programs as we continue. As our model continues to get more and more accurate, we're able to do more with less resources. But one area that we are going to continue to grow in that does not correlate to the model itself is on the disease biology and the translational side. So we're going to continue to build out our drug creation team, again, both on the disease biology, the translational side, and the clinical side. But we see that as modest growth as these programs are being undertaken.

Speaker Change: Yes, that's a great question.

Speaker Change: So we are focused in on <unk> as well as oncology so will fall in.

Speaker Change: One of those therapeutic areas.

Speaker Change: And then additionally.

Speaker Change: We are currently right size to be able to continue to take on more programs. As we continued as our model continues to get more and more accurate.

Speaker Change: Well to do more with less resources, but one area that we are going to continue to grow in.

Speaker Change: That does not.

Speaker Change: Correlate to the model itself is on the disease biology, and the translational side. So we're going to continue to build out our drug creation team again, both on the disease biology of the translational side and clinical.

Speaker Change: <unk> side, but we see that.

Speaker Change: Modest growth.

Speaker Change: These programs are being undertaken.

Unknown Attendee: Great, thank you. And then, if I could just squeeze one more in, technologies in AI drug discovery are pretty fragmented. Are there any white spaces in the tech stack that you could fill in organically?

Speaker Change: Great. Thank you and then if I could just squeeze one more in technologies in the AI drive discovery are pretty fragmented are there any white spaces in the tech stack that you could fill inorganically or do you expect to build on your Tac in house.

Sean McClain: Or do you expect to build on your tech in-house? One of the areas that we see as a big differentiation is the epitope specificity, so being able to landscape an epitope and target an epitope of interest or be able to test epitopes that may give you new, novel biology. With standard approaches like phage display and immunization, you have no control over this epitope specificity.

Speaker Change: One of the areas that we see as big differentiation is the epitope specificity for being able to landscape and epitope and.

Speaker Change: Our target an epitope of interest or be able to test.

Speaker Change: Epitopes that May give you a new novel biology with standard.

Speaker Change: Approaches like phage display immunization, you have no control over this epitope specificity.

Sean McClain: And to the best of our knowledge, this is the only technology that exists out there that allows you to hone in on these epitopes of interest and allow you to elucidate potential new biology from those epitopes. And so we see this as a major differentiation. This is really what's driven partnerships with AstraZeneca, Almerol, and Merck and will continue to drive our partnership pipeline, but also drive our own internal development as well. And we have applied this to internal programs as well. Great. Thank you so much.

Speaker Change: And to the best of our knowledge. This is the only technology that exists out there that allows you to hone in on these other tests.

Astrazeneca: Interest and allow you to elucidate <unk> potential novel biology from those those are the types and so we see this as a as a major differentiation. This is really what's driven partnerships with astrazeneca overall marked and.

Speaker Change: We will continue to drive our partnership.

Astrazeneca: Pipeline, but also drive our own internal development as well and we have applied this to.

Astrazeneca: Two the internal programs.

Astrazeneca: As well.

Speaker Change: Alright. Thank you so much I appreciate it.

Unknown Attendee: I appreciate it. One moment for the next question. The next question comes from Steve Deckert with KeyBank. Your line is open.

Speaker Change: One moment for the next question.

Speaker Change: The next question comes from Steve Dechert with Keybanc. Your line is open.

Steve Deckert: Hey guys, thanks for the question. Could you give some more color on how discussions are going with potential partners as they're late to get into your goal of four new partners this year? Yeah, I can comment on that, Sean.

Steve Dechert: Hey, guys. Thanks for the question could.

Steve Dechert: Could you give us some more color on how discussions are going with potential partners is there a way to get into your goal of four new partners. This year.

Steve Dechert: Okay.

Steve Dechert: Yes, I can comment on that sure.

Zachariah Jonasson: I'd say, well, you know, while signing partnerships is always a little bit lumpy, and if you look at our cadence last year, it's hard to have them come out on an even cadence throughout the year, but I would say that our pipeline of discussions is robust and covers both large pharma, mid, and small biotech as well as leading academic institutions. And as we have these discussions and pursue the BD strategy, we're really looking for partners that bring strong synergies to the table. And typically, that means really robust and deep knowledge of the target biology.

Steve Dechert: I'd say well, while signing partnerships is always a little bit lumpy I mean, if you look at our cadence last year.

Speaker Change: It's hard to have them come out on a even cadence throughout the year, but I would say.

Speaker Change: Our pipeline of discussions is robust and covers both large pharma.

Speaker Change: Mid and small biotech as well as meeting academic academic institutions and as we have these discussions and prosecute the BD strategy. We're really looking for partners that bring a strong synergy to the table and typically that means really robust and deep knowledge of the target biology.

Zachariah Jonasson: That's where we see a really fertile ground for partnering. So I would say we feel like we're well on track to hitting the metrics that you mentioned. Okay, thanks, and then, Are there any new capabilities that you're investing in as it relates to your platform? Thanks.

Speaker Change: Where we see a really fertile ground for partnering so I would say, we feel like we're well on track to hitting the metrics that.

Speaker Change: That you mentioned.

Speaker Change: Okay. Thanks, and then.

Speaker Change: Are there any new capabilities that you are investing in as it relates to your platform. Thanks.

Sean McClain: Yeah, one of the areas that we're continuing to invest in, not only on the de novo AI side but actually on the reverse immunology side. And one of the areas that we see as a bottleneck that AI could really unlock for us is the de-orphaning process. So once we take antibodies from a patient, we do a proteome panel screen to find out what these antibodies are binding to. And this is a very laborious and time-consuming step.

Speaker Change: Yes, one of the areas that we're continuing to invest in not only.

Not mentioned: On the de Novo AI side, but actually on the reverse in the neurology.

Us: And one of the areas that we see as a as a bottleneck that AI can really unlock for US is the <unk> process that once we take antibodies from from a patient.

Speaker Change: Do a protium panel screen to find out what is.

Speaker Change: Antibodies are binding to and this is a very laborious and time consuming stats and what we want to do is actually go in the reverse direction of.

Sean McClain: And what we want to do is actually go in the reverse direction of the de novo model. So instead of going target to antibody, we go antibody to target. This would allow us to rapidly de-orphan and discover new novel targets much faster than before.

Speaker Change: The de Novo models on <unk> targeting antibody.

Speaker Change: My body to target this would allow us to rapidly.

Our fan: Our fan and discover new novel targets much.

My body: Much faster than previous and we could scale Ah patient.

Sean McClain: And we could scale patient data and hospital partnerships as well. And so this is a kind of another key area of focus for us in AI development. As a reminder, to ask a question, please press star 11 on your telephone and wait for your name to be announced. Please stand by for the next question. The next question comes from Lee Chin with HC Wainwright. Your line is open. Hello, good morning. This is Lichun.

Speaker Change: Our data and hospital partnerships as well and so this is a kind of.

Speaker Change: Another key area of focus for us on the <unk>.

Speaker Change: AI.

Speaker Change: Development front.

Speaker Change: As a reminder to ask a question. Please press star one one on your telephone and wait for your name to be announced please standby for the next question.

Speaker Change: The next question comes from Lee Chen with H C. Wainwright Your line is open.

Lee Chin: Can you hear me well? Yes. Hi. I have two questions. One is to expand on the previous discussion on abscise differentiation.

Lee Chen: Oh Hello. Good morning. This is leto, Okay give me well.

Lee Chen: Yes.

Lee Chen: Hi, I have two questions one is.

Lee Chen: To expand on previous discussion.

Lee Chen: As far as differentiation so since the release of the 101 Daytona.

leto: Have you seen any shifts in the nature of the inbound partnership a partner interest what I mean is that.

Speaker Change: Set the previous partnership.

Speaker Change: Many driven by specific.

Speaker Change: Specific antibody design, so any anything any other.

Speaker Change: Capability that your partner is interested with finally focus on antibody design.

Speaker Change: And then I have another question around <unk>.

Zachariah Jonasson: Yeah, Zach can speak to the interest in ABS 101 and the discussions that we've been having on that, but I can say that they are very robust discussions, but Zach, I'll hand that over to you. Yeah, we have had a lot of nice inbound interest around that asset and will continue to have discussions. Our strategy, as Sean elucidated earlier, is to move that asset forward into phase one clinical studies. But we're certainly entertaining discussions now and happy to see the interest from potential partners in that area. And the second part of your question, I'll just mention that I think this epitope specificity has been really intriguing to potential partners.

Speaker Change: Yes, I can speak to the interest on AVX 101, and the discussions that we've been having on that but I can tell you that they are very robust discussions with Zack I'll hand that over to you.

Zack Smith: Yes, we have had a lot of nice inbound interest around that asset and continue to have discussions.

Zack Smith: Our strategy is.

Sean: Sean We stated earlier is to move that asset forward into phase one clinical studies.

Zack Smith: But we're certainly entertaining discussions now and happy to see the interest from.

Zack Smith: For potential partners in that area on the second part of your question I'll just mentioned.

Sean: I think this epitope specificity its been really intriguing to potential partners. So highlighting the capabilities of our platform and designing that asset I think of.

Zachariah Jonasson: So highlighting the capabilities of our platform and designing that asset, I think it's been quite interesting to a number of potential partners and existing partners, as well as our ability to design in unique features. So in some of our other assets, in case studies, we've shown an ability to design in pH-dependent binding, multivalency, unique properties that can be differentiating in a clinical setting. So I think that's an exciting new area. Thank you very much.

Speaker Change: Been quite an interesting to a number of potential partners and existing partners as.

Speaker Change: As well as our ability to design and unique features so in some of our other assets and case studies, we have shown an ability to design and ph dependent binding multibillion, let's see.

Speaker Change: Properties that can be differentiating in a clinical setting. So I think that's an exciting new area for us.

Christian Stegmann: My second question is on 201. Can you give us some color on the current competitive landscape for 201 in that undisclosed disease area, and what's your confidence in the differentiation factors from the current SOC and pipeline drugs? Thank you. Yeah, absolutely. Christian, do you want to take that one? Yes, thank you. My audio is cutting out for a moment.

Speaker Change: Great. Thank you very much my second question is one to one.

Speaker Change: Can you give us some color on the current competitive landscape of two one in the undisclosed disease area and what's your confidence of the differentiation factors from.

Speaker Change: Current SLC and pipeline books.

Speaker Change: Okay.

Christian: Yes, absolutely Christian do you want to take that one.

Christian Stegmann: So your question is around ABS 201. Yes, it is around the competitive landscape and differentiation factors. Yes, so we have not disclosed the precise indication for ABS-201-NET, not yet, but I will share that this is an indication of high unmet medical needs where the current standard of care is unsatisfactory. And we also plan to employ extended half-life antibody technology to basically improve patient convenience as well, just like we did for ABS1.

Christian: Yes. Thank you and my audio is cutting out from them. So your question is around <unk> 21.

Christian: Yes.

Christian: Around the competitive landscape and differentiation differentiation factors.

Christian: Yeah.

Christian: Yes, so we have not disclosed the precise indication for Avs tour one net.

Speaker Change: Yes, but I will I will share that.

Speaker Change: This is an indication of.

Speaker Change: High unmet medical need.

Speaker Change: Whereas the current standard of care is unsatisfactory and we also plan to.

unknown: We also plan to employ extended half life antibody technology to basically improve patient convenience as well just like we did for Aps 101.

Christian Stegmann: So, in essence, we will deliver a best-in-class profile, not only from an efficacy standpoint, but also from a patient standpoint. Yeah, and I will also mention as well that this target is a very underappreciated DERM target. And in this case, we would be second to the clinic. So it's not a very crowded space, a very underappreciated target, I'd say, almost very similar

Speaker Change: So in essence, we will deliver a best in class profile not only from an efficacy standpoint, but also from a patient convenience standpoint.

Speaker Change: Okay.

Jeremy: And I will also mention as well this target is a very underappreciated alright, Jeremy target.

Speaker Change: In this case, we would be second to the clinic.

Speaker Change: So it's not a very crowded space, a very underappreciated target I'd say almost very similar to Tijuana.

Speaker Change: Great. Thank you very much.

Speaker Change: Okay.

Speaker Change: I show no further questions at this time.

Speaker Change: This will conclude today's conference call. Thank you for participating you may now disconnect.

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Lee Chin: Great, thank you very much. I show no further questions at this time. This will conclude today's conference call. Thank you for participating. You may now disconnect. ??? ??? ??? ??? ??? ??? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? Ladies and gentlemen, thank you for standing by.

Speaker Change #100: Ladies and gentlemen, thank you for standing by welcome to <unk> first quarter 2020 for a business update call. At this time all participants are in a listen only mode.

Operator: Welcome to Absci's First Quarter 2024 Business Update Call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during, I apologize to ask a question during this session, you will need to press star one one on your telephone.

Speaker Change: After the speaker's presentation, there will be a question and answer session to ask a session.

Operator: You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would like now to turn the conference over to Alex Khan, Vice President, Finance, and Investor Relations. Please go ahead.

Speaker Change: I apologize to ask a question. During this session you will need to press star one on your telephone you.

Alexander Khan: You will then hear an automated message advising your hand is right to withdraw your question. Please press star. One again, please be advised that today's conference is being recorded I would like now to turn the conference over to Alex <unk>, Vice President Finance and Investor Relations. Please go ahead.

Speaker Change: <unk>.

Alexander Khan: Thank you. Earlier today, Absci released financial and operating results for the quarter ended March 31, 2024. If you haven't received this news release, or if you would like to be added to the company's distribution list, please send an email to investors@absci.com. An archived webcast of this call will be available for replay on Absci's investor relations website at investors.absci.com for at least 90 days after this call. Joining me today are Sean McClain, Absci's founder and CEO, and Zach Jonasson, Chief Financial Officer and Chief Business Officer.

Alexander Khan: Thank you earlier today, <unk> released financial and operating results for the quarter ended March 31, 2024. If you hadn't received this news release or if you'd like to be added to the Companys distribution list. Please send an email to investors at <unk> dot com and archived webcast of this call.

Investor Relations: <unk> will be available for replay on <unk> Investor Relations website at investors dot outside dot com for at least 90 days after this call.

Alexander Khan: Joining me today are Shawn Mcclain, as ice founder and CEO, Zach Johnson, Chief Financial Officer, and Chief Business Officer, Christian Stegman, <unk> SVP of drug creation will also joined for Q&A following prepared remarks.

Management: Before we begin I would like to remind you that management will make statements. During this call that are forward looking within the meaning of the federal Securities laws. These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated and you should not place any undue reliance on forward looking statements additional information regarding these risks uncertainty.

Management: And factors that could cause results to differ appears in the section entitled forward looking statements in the press release issued today and the documents and reports filed lab side from time to time with the Securities Exchange Commission, except as required by law outside disclaims any intention or obligation to update or revise any financial or product pipeline protections or.

Speaker Change #102: Other forward looking statements either because of new information future events or otherwise. This conference call contains time sensitive information and is accurate only as of the live broadcast May 14 2024.

Sean McClain: With that I'll turn the call over to Sean.

Sean McClain: Thanks, Alex. Good morning, and thank you to everyone for joining us today for our first Business Update conference call since 2021. A lot has changed since then. While we have been active at investor conferences and other venues sharing our progress, we are excited to welcome you to our quarterly update call, which we'll host on a regular basis moving forward. There are a few reasons for this.

Sean: Thanks, Alex.

Sean McClain: And thank you to everyone for joining us today for our first business update conference call since 2021.

Sean: A lot has changed since then.

Sean: While we have been active at investor conferences, and other venues Shine our progress. We're excited to welcome you to our quarterly update call, which will host on a regular basis moving forward.

Speaker Change #111: There are a few reasons for this change among them.

Sean McClain: Among them, we are pleased with the expansion of our shareholder base and research analyst coverage. We want to provide an open setting to share our latest progress and details and allow for interactive dialogue. Additionally, our business model previously revolved almost exclusively around partner programs, where our communication was influenced by a partner.

Speaker Change #104: With the expansion of our shareholder base and research analyst coverage.

Speaker Change #113: We want to provide an open starting to share our latest progress in details and allow for interactive dialogue.

Partner: Additionally, our business model previously revolved almost exclusively around partner programs, where our communication was influenced by our partner.

Speaker Change #105: Our new hybrid business model, including our internal pipeline gives us more opportunity to discuss the exciting progress we are making on each program.

Speaker Change #106: With that in mind I'd like to begin with a brief recap of the achievements. We made in 2023 before discussing our progress in 2024 later.

Speaker Change #105: Later in the call that we will provide more detail on the status and outlook for each of our internal programs and our business as a whole.

Sean McClain: We are often asked about our differentiating features, what sets us apart and positions us as leaders in AI drug discovery for biologics and a partner of choice across the industry. Any discussion of our integrated drug creation platform starts and stops with data. The ability to generate and screen massive amounts of scalable biological data is an industry breakthrough that enables our platform to operate as it does. Based on these pillars of data to train, AI to create, and wet lab to validate, our platform is designed to continuously learn and improve as a result of our data generation capabilities and integration with our wet lab operations. Looking back on our accomplishments from the first quarter of 2024, it is clear they were only made possible due to the groundwork laid by our dedicated team in the previous year.

Speaker Change #107: We are often asked about our differentiating features.

Speaker Change #119: That does apart and positions us as leaders in AI drug discovery for biologics.

Speaker Change #109: A partner of choice across the industry.

Speaker Change #118: Any discussion of our integrated generation platform starts and stops with the data.

Speaker Change #121: The ability to generate and screening massive amount of scalable biological data with an industry breakthrough that enables our platform to operate as it does.

Speaker Change #109: Based on these pillars of data to train AI, great and wet lab to validate our platform is designed to continuously learn and improve as a result of our data generation capability and integration with our wet lab operations.

Speaker Change #108: Looking back on our accomplishments from the first quarter of 2024 it is clear they.

Speaker Change #108: Were only made possible due to the groundwork laid by our dedicated team and the previous year.

Sean McClain: The ability of our platform to rapidly design and create differentiated antibody candidates in a capital efficient manner while achieving epitope specificity is a direct result of our team's effort through 2023. We started 2023 with the release of a foundational manuscript demonstrating a first in creating and validating de novo antibodies with zero-shot generative AI. Over the year, we expanded our models, harnessing proprietary wet lab technology to generate scalable biological data for model training and validation. We continue to build our talented team.

Speaker Change #108: The ability of our platform to rapidly design and create differentiated antibody candidates in a capital efficient manner, while achieving epitope specificity is the direct result of our team's efforts through 2023.

Speaker Change #110: We started 2023 with the release of a.

Speaker Change #117: A foundational manuscript demonstrating a first and creating and validating de novo antibodies with zero soft generative AI.

Speaker Change #114: Over the year, we expanded our models harnessing the proprietary <unk> technology to generate scalable biological data for model training and validation we.

Speaker Change #115: We continue to build our talented team.

We: Optimize our organization and integrate all of our platform capabilities deeply in.

We: In line with our hybrid business model. These hubs aims to leverage our platform to create a pipeline of assets and established validating partnerships with companies like Astrazeneca and overall.

Speaker Change #120: In October of last year at our inaugural R&D day, we reached a pivotal moment by unveiling our internal pipeline of asset programs, including potential best in class and first in class antibody programs.

Speaker Change #116: We are excited to continue advancing each of these programs, which <unk> will be discussing in greater detail later.

our platform: But stepping back is humbling and gratifying to see the translation of an idea using generative AI with our platform to create differentiated antibody candidates.

Speaker Change #129: To reality.

Speaker Change #130: We demonstrated our platform's ability to create a differentiated antibody like ABS 101, our anti <unk> antibody program with potential best in class properties in a very time and capital efficient manner compared to industry standards.

Sean McClain: At the beginning of 2024, we unveiled positive preclinical data for this program, and by the end of February, we initiated our IMD needline studies. As we advance this program, I want to highlight our platform's efficiency in generating this program and its potential wide implications. In just 14 months, we generated and selected our drug candidate at a cost of less than $5 million. ABS 101 is an early example of the power of our platform.

Speaker Change #133: At the beginning of 2024, we unveiled positive preclinical data for this program by the end of February we initiated our IND, enabling studies.

Speaker Change #134: As we advance this program I want to highlight our platform efficiency in generating this program and the potential vast implications.

Speaker Change #122: And just 14 months, we generated and selected our drug candidate at a cost of less than $5 million.

Speaker Change #135: 101 is an early example of the power of our platform and we see additional opportunity to demonstrate similar results through our other current and future pipeline programs.

Speaker Change #138: At a high level our platform unlock the potential for a powerful novel biotech business model.

Speaker Change #123: We can generate a differentiated antibody candidate and complete IND, enabling studies at a cost of approximately $15 million.

Speaker Change #125: This could enable a new paradigm and biotech where capital typically allocated for one asset could be spread across multiple candidates improving the overall probability of success.

Speaker Change #125: In addition to applying our platform to our internal pipeline, we are encouraged by the industry reception.

Speaker Change #125: Including recent partnerships with industry leaders.

industry leaders: It's humbling to account companies like Merck and Astrazeneca, among our partners, who bring invaluable talent scale and expertise to our collaborations.

Speaker Change #127: This year and beyond we look forward to enter into additional partnerships with pharma and biotech companies.

Speaker Change #126: These partnerships will leverage our platform to enable and advance their drug discovery programs.

Speaker Change #140: Shortening timeframes lowering costs, improving success probabilities and unlocking new biology previously thought unachievable.

Speaker Change #131: I'm incredibly proud of our team at outside for these achievements and excited to see the promise of our platform of flights of further internal programs demonstrating the potential for disruptive improvements in biotech economics.

Speaker Change #131: At <unk>, we come to work every day with a mindset focused on innovation and continuous improvement.

Speaker Change #132: We are driven by our mission to create better biologics for patients faster.

unknown: A few months ago, we decided further strengthen our balance sheet and capital position through a underwritten public offering of common stock.

Speaker Change #137: We're encouraged by the positive reception and support from a large and diverse group of investors, both new and existing.

unknown: This support will help us continue to pursue our vision as we look ahead to the rest of the year I am very excited about what lies ahead, we remain laser focused on execution across all aspects of our business, including partnered and internal programs with.

unknown: With innovation and the pursuit of the impossible at the core of everything we do.

Speaker Change #222: With that I will turn the call over to Don to walk through each of our programs provide our outlook and get an update on our financials.

unknown: Zach.

unknown: Thanks, Sean.

Don: As Sean discussed this past quarter, we closed an underwritten public offering of common stock raising gross proceeds of approximately $86 4 million.

Zach Johnson: This additional capital will further support our ability to advance our internal pipeline of asset programs.

Zach Johnson: This strategy reflects the hybrid business model that we introduced last year.

Sean: We intend to develop our internal programs to a certain value to certain value inflection points. For example, through a phase one or potentially phase III clinical trial before selling partnering or out licensing set asset.

Speaker Change #139: The primary rationale for our strategy stems from our platform's ability to create differentiated antibody drug candidates in a highly efficient manner.

Speaker Change #148: We believe our strategy will allow us to create and capture more of the overall value of obesity through internally generated programs.

Speaker Change #139: As we have said in the past every program is unique and there is no one size fits all strategy for these assets.

Zachariah Jonasson: As a best practice and guiding strategy, we will look for the right partner at the right time. As Sean mentioned earlier, we generated the ABS 101 candidate in just 14 months at a cost of less than $5 million. By comparison, Farm Industry Estimates, We have seen 10 such figures at three plus years to reach a drug candidate and at a cost of 30 to $50 million. And as our platform continues to improve via our data generation and screening cycles. We believe over time that we will even further reduce the time it takes us to generate additional drug candidates. Turning back to our current internal pipeline.

Speaker Change #145: As the best practice and guiding strategy, we will look for the right partner at the right time.

Sean McClain: As Shawn mentioned earlier, we generated the ABS 101 candidate.

Speaker Change #139: And just 14 months at a cost of less than $5 million.

Speaker Change #139: By comparison pharma industry estimates.

Sean McClain: We are seeing pin such figures at three plus years to reach a drug candidate and at a cost of 30 million to $50 million.

Sean McClain: And as our platform continues to improve via our data generation and screening cycles.

Sean McClain: We believe over time that we will either even further reduce the time it takes us to generate additional drug candidates.

Speaker Change #143: Turning back to our current internal program pipeline.

Zachariah Jonasson: Our lead program, ABS 101, is a potential best-in-class anti-TL1A antibody. In January, we presented early preclinical data from three advanced leads from this program. This data showed properties consistent with a potentially superior product profile, including demonstrated high affinity, high potency, favorable developability, and extended half-life. We used our DeNovo AI model to design ABS-101 leads towards a specific epitope of TL1A with the objective of creating a drug candidate with superior potency and lower immunogenicity.

Speaker Change #144: Our lead program <unk> 101 is.

Speaker Change #152: Is it a potential best in class anti <unk> antibody in January we presented early preclinical data from.

January: From three advanced leads from this program. This data showed property is consistent with a potentially superior product profile, including demonstrated high affinity high potency <unk>.

Speaker Change #154: Favorable <unk> ability and extended half life.

Speaker Change #147: We used our de Novo AI model to design AVX 101 leads towards a specific epitope of tailwind with the objective of creating a drug candidate with superior potency and lower Immunogenicity.

January: This target product profile combined with anticipated high bioavailability could ultimately improve patient experience with easier less frequent dosing.

January: Going further confirmatory PK studies in February we selected a primary and a backup development candidates to advance into IND, enabling studies.

January: We also recently completed studies, demonstrating AVX 101 candidates ability to buy in bulk <unk> monomer and trimer.

Speaker Change #156: Which could potentially lead to differentiated clinical efficacy.

Zachariah Jonasson: We plan to share additional preclinical data, including data from non-human primate studies, in the next few months. We then expect to initiate Phase I clinical studies in early 2025, with an interim data readout expected in the second half of 2025. Next, ABS-201, a potentially best-in-class antibody for an undisclosed dermatological target, is designed for an undisclosed dermatological indication with significant unmet need where the efficacy of the pharmacological standard of care is not satisfactory.

January: Glenn to share additional preclinical data, including data from nonhuman Primate studies in the next few months.

Glenn: We then expect to initiate phase one clinical studies in early 2025.

Glenn: As an interim data readout expected in the second half of 2025.

Glenn: Next ABS 201, a potentially best in class antibody.

Glenn: An undisclosed dermatology target is designed for an undisclosed dermatological indications with significant unmet need.

Glenn: Where the efficacy for the pharmacological standard of care is not satisfactory, we anticipate selecting a development candidate for this program in the second half of 2024.

Glenn: Finally, ABS 301, essentially first in class antibody for an undisclosed immuno oncology target is a fully human antibody designed to bind to a novel target discovery through our reverse immunology platform.

Speaker Change #157: Antibody inhibits an immunosuppressive cytokines and is believed to stimulate an innate immune response.

Zachariah Jonasson: ABS 301 is being evaluated for broad applicability to a variety of oncology indications, and comprehensive profiling of this program is in progress. We anticipate completion of mode of action validation studies for this program in the second half of 2024. As a reminder, our Reverse Immunology Platform is designed to discover novel antibody targets based on the analysis of tertiary lymphoid structures, or TLSs, from patient samples. Within this platform, we mine antibody repertoires from TLS samples derived from patients who have exhibited an extraordinary immune response. We discovered the novel human antibody, ABS-301, and its corresponding target using this platform.

Speaker Change #157: <unk> 301 is being evaluated for broad applicability to a variety of oncology indications and comprehensive profiling profiling of this program is in progress we anticipate completion of the motive action validation studies for this program in the second half of 2024.

Speaker Change #149: As a reminder, our reverse immunology platform is designed to discover novel antibody targets.

unknown: Based on the analysis of tertiary lymphoid structures or Tls is from patient samples.

unknown: Within this platform, we mined antibody repertoires from the Tls samples derived from patients.

Speaker Change #150: We have exhibited extraordinary immune response.

Speaker Change #150: Okay.

Speaker Change #151: We discovered.

Speaker Change #151: <unk> 301 novel human antibody and its corresponding target using this platform. We look forward to sharing additional details later this year.

Speaker Change #151: In addition to further development of ABS 101, ABS 201.

Speaker Change #151: <unk> 301, we continue to expect to advance at least one additional internal asset program to a lead stage in 2024.

ABS: Further in line with our hybrid business model, we continue to execute and make solid progress on our existing drug creation partnerships I am pleased to see the close collaboration between our partners and our own R&D teams.

ABS: And while we cannot disclose much detail about our partnered programs.

Zachariah Jonasson: The work we are doing with these partners is progressing well and according to our expected timeline. We look forward to sharing more details about these programs at a later date. Additionally, we continue to anticipate finding additional drug creation partnerships with at least four partners in 2024, including one or more multi-program partners. I'm also pleased to share that we have a robust and diverse pipeline of potential partners, and we look forward to updating you on these over the course of the year.

ABS: The work we are doing with these partners is progressing well and according to our expected timelines.

Speaker Change #158: We look forward to sharing more details about these programs at a later date.

Speaker Change #155: Additionally, we continue to anticipate finding additional drug creation partnerships with at least four partners in 2024, including one or more multi program partnerships. I'm also pleased to share that we have a robust and diverse pipeline of potential partners and we look forward to updating you on these over the course of the year.

Zachariah Jonasson: Turning now to our financials, revenue in the first quarter of 2024 was $900,000 as we continue to progress our partnered and internal programs concurrently. Research and development expenses in the first quarter of 2024 were $12.2 million, as compared to $12.7 million in the prior year period. This decrease was primarily driven by lower personnel costs, offset by an increase in stock compensation expenses.

Speaker Change #155: Turning now to our financials revenue in the first quarter of 2024 was $900000 as we continue to progress our partnered and internal programs concurrently.

Speaker Change #155: Research and development expenses in the first quarter of 2024 were $12 2 million as compared to $12 7 million in the prior year period.

Speaker Change #155: Decrease was primarily driven by lower personnel costs offset by an increase in stock compensation expense.

Zachariah Jonasson: Selling General and Administrative Expenses were $8.7 million in the first quarter of 2024 as compared to $9.6 million in the prior year period. This decrease was due to lower personnel costs and continued reduction in administrative costs offset by an increase in stock compensation. Turning to our balance sheet, we ended the quarter with $161.5 million in cash, cash equivalents, and short-term investments, as compared to $97.7 million as of December 31, 2023

Speaker Change #155: Selling general and administrative expenses were $8 7 million in the first quarter of 2024 as compared to $9 6 million in the prior year period.

Speaker Change #155: This decrease was due to lower personnel costs and continued reduction in administrative costs offset by an increase in stock compensation expense.

Zachariah Jonasson: For 2024, we continue to expect a gross use of cash, cash equivalents, and short-term investments of approximately $80 million, inclusive of the expected costs associated with completing the IND enabling studies for ABS 101 with a third-party CRO. Based on our current plans, we believe our existing cash, cash equivalents, and short-term investments will be sufficient to fund our operations into the first half of 2027. All together, we are very encouraged by the progress we have made on our internal programs and confident in our ability to execute on these and our partner programs over the course of 2024 and beyond. With that, I'll turn it back to Sean.

Speaker Change #155: Turning to our balance sheet, we ended the quarter with $161 5 million in cash cash equivalents and short term investments as compared to $97 7 million as of December 31, 2023.

Speaker Change #155: For 2024, we continue to expect a gross use of cash cash equivalents and short term investments of approximately $80 million.

Speaker Change #155: Inclusive of the expected costs associated with completing the IND, enabling studies for <unk> hundred one with a third party CRO.

Speaker Change #155: Based on our current plans, we believe our existing cash cash equivalents and short term investments will be sufficient to fund our operations into the first half of 2027.

Speaker Change #227: Altogether, we are very encouraged by the progress we have made on our internal programs and confident in our ability to execute on these and our partnered programs over the course of 2024 and beyond with that I will turn it back to Sean.

Operator: Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. One moment for the first question. The first question comes from Kripa Devrakonda with Truist Securities. Your line is open. Hey, guys. Thank you so much for taking my question. I have a question about ABS 101.

Sean: Thanks Mac.

Speaker Change #225: 2023 was a pivotal and successful year for <unk> in our company's evolution in 2024, we will continue to focus on execution and further demonstrate the power of our platform.

Speaker Change #223: Create differentiated antibody assets.

Speaker Change #228: We're thrilled to advance each of our programs with the goal of creating better medicines for patients faster and fundamentally improving the economics of biotech.

Speaker Change #245: We look forward to updating you along the way with that I will turn it back to the operator to begin Q&A.

Speaker Change #155: Operator.

Speaker Change #225: Thank you.

Speaker Change #233: As a reminder to ask a question. Please press star one one on your telephone and wait for your name to be announced to withdraw your question. Please press star one again.

Speaker Change #224: One moment for the first question.

Speaker Change #232: Our first question comes from Crypto.

Speaker Change #229: <unk> with <unk> Securities. Your line is open.

Speaker Change #234: Hey, guys. Thank you so much for taking my question I have a question about AVX 101.

Speaker Change #238: And he saw exciting preclinical data from the program.

Speaker Change #229: Just wondering if you can talk about your level of confidence that this drug is differentiated versus the other.

Speaker Change #229: The drug in the same class.

Speaker Change #229: Do you do we truly understand the biology about the importance of targeting monomer versus trimer and what does it have an edge do you have in understanding that quite a bit.

Speaker Change #229: And then I have a follow up question.

Christian Stegmann: Yes, absolutely I think you're correct.

Speaker Change #231: I'll hand that over to Christian to talk about the differentiated properties that we see with the tier one and in particular, the monomer versus primer.

Christian Stegmann: Yeah, thank you, Sean. Absolutely. First off, we do think that our extended half-life is an absolutely critical and very differentiated parameter that will address patient convenience topics. But more importantly, also on the monomer-trimer question, I think it's important to highlight that our AI-guided antibody design strategy is really based on epitope-specific targeting using 3D structures, and specifically for 3D structures of Tier 1a. So we selectively chose an epitope on the monomer that shows no discrimination for monomer versus trimer binding, and we designed antibodies using AI. Thus, we completely avoid epitopes that span multiple subtypes.

Christian: Yes. Thank you Shaun absolutely first off we do think that our extended half life is an absolutely critical.

Speaker Change #155: It.

Speaker Change #155: Very differentiated.

Speaker Change #155: Amit.

Speaker Change #235: We'll address patient convenience topics.

Speaker Change #230: And more importantly also on the <unk> question I think it's important to highlight that our AI got AI guided antibody design strategy is really based on epitope specific targeting using <unk> structures.

Speaker Change #230: Specifically for <unk> structures of tier one eight so we selectively chosen epitope on the monomer.

Speaker Change #214: That shows no discrimination for melanoma versus trimer binding and we designed the antibodies using AI.

Speaker Change #214: Really avoids epitopes that span multiple sub units.

Christian Stegmann: And this allowed us to produce a development candidate that equally targets both TL1A states, and it also addresses, to our knowledge, all known monomer isomers. This may have relevance in clinical trials because it's known that certain monomers are expressed differentially in a certain patient. Great, thank you so much. Sean, I have a question for you. A big, bigger picture question.

Speaker Change #214: And this allowed us to produce a development candidate that equally targets both tier one eight states.

Speaker Change #214: And it also addresses to our knowledge all known <unk> isoforms. This may have relevance in clinical trials.

Speaker Change: Because it's known that certain monomers are expressed differentially pay.

Speaker Change #209: Patient populations.

Unknown Attendee: You were talking about, you know, using generative AI models. I was just wondering, with the improved generative AI models and new data, do you think you can continue to improve efficiency and reduce the drug development timelines? I know, you know, 14 months is already great, and $5 million to develop a drug is already great, but I was just wondering about that. Thank you. Yeah, absolutely. As the models get more and more accurate with the more data we're training on and, you know, as we continue to improve the AI architectures and our models, we do see these timelines continuing to decrease over time and the overall cost decreasing.

Speaker Change #236: Great. Thank you so much John I have a question for you a bigger picture question.

Speaker Change #159: You were talking about using generative AI model I was just wondering with the improved generative AD models and new data.

Speaker Change #246: Thank you can continue to improve efficiency and reduce the drug development timelines I know, but 14 months.

Speaker Change #159: Is already greater than $5 million developing Chinese validate a great, but just wondering about that thank you.

Speaker Change #239: Yes, absolutely.

Speaker Change #237: The models get more and more accurate with the more data we are training and.

Speaker Change #178: As we continue to improve the AI architectures in our models, we do see these timelines continuing to decrease over time and the overall cost.

Unknown Attendee: And this is a very important metric for us internally, these cycle times, and you are going to continue to see, over time, these overall costs decrease, both on how long it takes us to get to a drug candidate, as well as the overall costs associated with generating a drug candidate. So do expect that in the future.

Speaker Change #178: Decreasing and this is a very important metric for us.

Speaker Change #178: Internal A&D is these cycle times and you are going to continue to see over time.

Internal A&D: These overall cost decrease both on how long it takes us to get to a drug candidate as well as the overall costs associated with generating a draw.

Speaker Change #173: Candidate So do you expect that in the future.

Speaker Change #241: Great. Thank you so much.

Speaker Change #240: One moment for the next question.

Sean McClain: Great, thank you so much. One moment for the next question. The next question comes from George Farmer with Scotiabank. Your line is open. Hi, good morning, everyone.

Speaker Change #241: Next question comes from George Farmer with Scotiabank. Your line is open.

George Farmer: Thanks for taking my question. I was wondering if you could... give us a heads up on what? Absolutely. Christian, do you want to take that?

George Farmer: Hi, Good morning, everyone. Thanks for taking my question I was wondering if you could.

George Farmer: Give us a heads up on what we can expect to see from the non human to human Primate studies ongoing with <unk> hundred one later this year.

Speaker Change #155: Okay.

Speaker Change #155: Absolutely Christian do you want to take that.

Christian Stegmann: Yeah, absolutely. So our non-human primate pharmacokinetic studies are expected to demonstrate that we are indeed able to show an extended half-life of our antibody, thus de-risking the pharmacokinetic profile. So we, in the next few months, we'll be able to demonstrate that our antibody engineering approach to extend the half-life of the antibody works. Okay, anything else from those studies we should be looking out for, PD markers, anything like that? Yes, we will absolutely measure the non-pharmacodynamic marker as well, obviously. And exactly as you mentioned, demonstrating an extended effect on the pharmacodynamic biomarker will then obviously also de-risk efficacy. And then, maybe, on cash.

Christian: Yes, absolutely.

Speaker Change #155: So.

Christian: Our non human Primate pharmacokinetics studies are expected to demonstrate that we.

Christian: We indeed are able to show an extended half life of our antibody thus derisking.

Speaker Change #155: Pharmacokinetic profile in humans. So we in the next few months, we'll be able to demonstrate that our.

Speaker Change #155: Antibody engineering approach to extend the half life of the antibody has worked.

Speaker Change #243: Okay anything else from those studies, we should be looking out for the PD markers or anything like that that can kind of shed light on the differentiation of the antibody from competitors.

Speaker Change #167: Yes, we will absolutely measure the non pharmacodynamic marker as well obviously.

Speaker Change #167: Exactly I assume as you mentioned.

Speaker Change #167: Demonstrating and extend that effect on the Pharmacodynamic biomarker will then obviously also derisk efficacy.

Speaker Change: Very quick point.

Speaker Change #164: Okay great.

Speaker Change #248: Great and then maybe.

On on cash.

George Farmer: Your guidance implies that I think some new funding is coming in probably from partnerships, best guests. Can you kind of elaborate a little bit more on that relative to how we should think about casting?

Speaker Change #155: Your guidance implies.

Speaker Change #155: I think so.

Speaker Change #244: You're funding coming in probably from partnerships is probably the best guests can you kind of elaborate a little bit more on that.

Speaker Change #169: Relative to how we should think about cash usage through 2027.

Zachariah Jonasson: Yeah, we do. Yeah, go for it, Zach. Yeah, I was gonna say, George, we continue to reiterate our guidance of 80 million gross cash usage for 2024. That's obviously a gross figure and that includes the cost associated with completing the IEG enabling studies for ABS 101. Our forecast that takes us into 2027 includes some modest assumptions around partnering on a regular cadence, but it doesn't include any assumptions around a significant partnership.

Speaker Change #155: Yes.

Speaker Change #160: Yes go for it.

Speaker Change #208: Yes, I was going to say George we continue to reiterate our guidance of $80 million of gross cash usage for 2024.

George: So obviously, a gross figure and that includes the complete the costs associated with completing the A&D, enabling studies for <unk> hundred one.

Speaker Change: Our forecast, but take within Q2.

George: 2027 include some modest assumptions around partnering on a regular cadence, but it doesn't include any assumptions around a significant partnership deal.

Zachariah Jonasson: So it's kind of our typical run rate assumptions built. And then I would point out, too, if you look at our net cash usage, that typically comes in well under growth. So for example, if you look at H2 of 2023, the net cash usage for the second half of last year was roughly $27 million in total. And then cash usage for Q1 of this year was roughly $16.9 million, which is a little higher given that we paid bonuses in March.

Speaker Change #160: It's kind of our typical run rate assumptions built into that.

Speaker Change #249: And then I would point out too if you look at our net cash usages, but typically comes in well under growth. So for example, if you look at page two of 2023.

Speaker Change #172: The net cash usage for the second half of last year was roughly $27 million in total on the net cash usage for Q1 of this year was roughly $16 9 million, which is a little higher given that we paid bonuses in March.

Speaker Change #160: You can see our net cash used units was coming well in coming well under the gross cash.

Speaker Change #160: Usage.

Speaker Change #160: Okay.

Zack Smith: Thanks, very much Zack.

Speaker Change #174: One moment for the next question.

Speaker Change #176: The next question comes from Jacqueline Chiesa with TV Cowen Your line is outstanding.

Jacqueline Kiesa: Thanks so much for taking the questions. With ongoing bipartisan discussions regarding biosecurity, can you give us any color on the third-party CRO you're using for your IND studies? Is it WuXi Biologics or a China-based CRO? Yeah, that's a great question. We are using WUSHI at the moment.

Speaker Change #160: Hi, This is Jacqueline Keith on for Steven MA. Thanks, So much for taking the questions.

Speaker Change #196: With ongoing bipartisan discussions regarding bio security can you give us any color on the third party CRM you are using for your IND studies is at Wuxi, biologics or China based <unk>.

Sean McClain: And given the, you know, recent discussions that have been ongoing with that, we do believe that the relationship with WUSHI will not put us at risk with the current program. But we are engaging with other CROs and do have backup strategies to, you know, mitigate any other potential tailwinds that may occur with new legislation that may come out. Great, thank you. I appreciate the color.

Jacqueline Keith: Yes, that's a great question, we are using.

Speaker Change #160: Lucy.

Speaker Change #160: Current moment.

Speaker Change #162: And given the recent discussions that have been ongoing with that we do believe that the relationship with Wuxi will not.

Speaker Change #161: Put us at risk with the current program, but we are engaging with other CRM and youre backup strategies.

Speaker Change #161: Two.

Speaker Change #161: Mitigate any other potential tailwind that may occur.

Speaker Change #161: With new legislation that may come out.

Jacqueline Kiesa: And regarding your fourth internal asset, can you give us any insight on the disease area you're looking to focus on? Is it one you've targeted for a new therapeutic area? And is the company the right size to serve both your internal and partnered programs? Yeah, that's a great question.

Speaker Change #161: Yeah.

Speaker Change #207: Great. Thank you I appreciate the color.

Speaker Change #168: And regarding your fourth internal asset can you give us any insight onto the disease area Youre looking to focus on is it one you targeted for a new therapeutic area and as the company right size to serve both your internal and partnered programs.

Speaker Change #182: Yes, that's a great question.

Speaker Change #163: So we are focused in on <unk> as well as oncology, so well fall in.

Speaker Change #163: One of those therapeutic areas.

Speaker Change #166: And then additionally, we.

Speaker Change #177: We are currently right size to be able to continue to take on more programs. As we continued as our model continues to get more and more accurate, we're able to do more with less resources, but one area that we are going to continue to grow in.

Speaker Change #168: That does not.

Speaker Change #171: Correlate to the model itself is on the disease biology, and the translational side. So we're kind of continue to build out our drug creation team again, both on the disease biology of the translational side and clinical.

Speaker Change #166: <unk> side, but we see that.

Speaker Change #166: Modest growth.

Speaker Change #166: These programs are.

Speaker Change #251: <unk> undertaken.

Jacqueline Kiesa: Great, thank you. And then, if I could just squeeze one more in, technologies in AI drug discovery are pretty fragmented. Are there any white spaces in the tech stack that you could fill in organically?

Analyst: Alright. Thank you and then if I could just squeeze one more in technologies in the AI drive discovery are pretty fragmented are there any white spaces in the tech stack that you could fill inorganically or do you expect to build on your Tac in house.

Sean McClain: Or do you expect to build on your tech in-house? One of the areas that we see as a big differentiation is epitope specificity. So being able to landscape an epitope and target an epitope of interest or be able to test epitopes that may give you a new insight into biology, you know, with standard approaches like phage display and immunization, you have no control over this epitope specificity. And to the best of our knowledge, this is the only technology that exists out there that allows you to hone in on these epitopes of interest and allow you to elucidate potential new biology from those epitopes.

Speaker Change #250: One of the areas that we see as big differentiation is the epitope specificity for being able to landscape.

Speaker Change #181: Epitope and.

Speaker Change #181: Target an epitope.

Speaker Change #166: Interest or be able to test.

Speaker Change #170: <unk> that May give you new novel Biology with standard.

Speaker Change #179: Approaches like phage display and utilization you have no control over this epitope specificity.

Speaker Change #179: And to the best of our knowledge. This is the only technology that exists out there that allows you to hone in on these other tests.

Speaker Change #179: <unk>.

Speaker Change #179: Interest and allow you to elucidate <unk> potential novel biology from those those are the types and so we see this as a as a major differentiation. This is really what's driven partnerships with astrazeneca overall marked.

Sean McClain: And so we see this as a major differentiation. This is really what's driving partnerships with AstraZeneca, Almerall, and Merck. And, you know, we'll continue to drive our partnership pipeline but also drive our own internal development as well. And we have applied this to internal programs as well. Great. Thank you so much.

Speaker Change #179: And we will continue to drive our partnership.

Speaker Change #170: Pipeline, but also drive our own.

Speaker Change #170: Internal development as well and we have applied this.

Speaker Change #170: Two of the internal programs.

Speaker Change #170: As well.

Jacqueline Kiesa: I appreciate it. One moment for the next question. The next question comes from Steve Deckert with KeyBank. Your line is open.

Speaker Change #196: Alright. Thank you so much I appreciate it.

Speaker Change #175: One moment for the next question.

Speaker Change #183: The next question comes from Steve Dechert with Keybanc. Your line is open.

Steve Deckert: Hey guys, thanks for the question. Could you give some more color on how discussions are going with potential partners as they're awaiting to get into your goal of four new partners this year? Yeah, I can comment on that, Sean.

Steve Dechert: Hey, guys. Thanks for the question could you give us some more color on how discussions are going with potential partners is there a way to get into your goal of four new partners. This year.

Steve Dechert: Okay.

Speaker Change: Yes, I can comment on that sure.

Zachariah Jonasson: I'd say, well, you know, while signing partnerships is always a little bit lumpy, and if you look at our cadence last year, It's hard to have them come out on an even cadence throughout the year, but I would say that our pipeline of discussions is robust and covers both large pharma, mid, and small biotech as well as leading academic institutions. And as we have these discussions and implement the BD strategy, we're really looking for partners that bring strong synergies to the table.

Speaker Change #189: I'd say well, while signing partnerships is always a little bit lumpy and if you look at our cadence last year.

Speaker Change #170: It's hard to have them come out on a even cadence throughout the year, but I would say that our pipeline of discussions is robust and covers both large pharma mid.

Speaker Change #170: Mid and small biotech as well as meeting academic academic institutions.

Speaker Change #170: As we have these discussions.

Speaker Change #170: And prosecute the BD strategy, we're really looking for partners that bring strong synergy to the table and typically that means really robust and deep knowledge of the target biology, that's where we see a really fertile ground for partnering so I would say, we feel like we're well on track to hitting the metrics that you.

Zachariah Jonasson: And typically, that means really robust and deep knowledge of the target biology. That's where we see a really fertile ground for partnering. So I would say we feel like we're well on track to hitting the metrics that you mentioned. Okay, thanks, and then, Are there any new capabilities that you're investing in as it relates to your platform? Thanks.

Speaker Change #170: You mentioned.

Speaker Change: Okay. Thanks, and then are.

Speaker Change #188: Are there any new capabilities that youre investing in as it relates to your platform. Thanks.

Zachariah Jonasson: Yeah, one of the areas that we're continuing to invest in, not only on the de novo AI side but actually on the reverse immunology side. And one of the areas that we see as a bottleneck that AI could really unlock for us is the de-orphaning process. So once we take antibodies from a patient, we do a proteome panel screen to find out what these antibodies are binding to. And this is a very laborious and time-consuming step.

Speaker Change #193: Yes, one of the areas that we're continuing to invest in not only.

Speaker Change #188: On the de Novo AI side, but actually on the reverse in neurology.

Speaker Change #180: And one of the areas that we see as a as a bottleneck that AI could really unlock for US is the <unk> process that once we take antibodies from from a patient.

Speaker Change #180: Do a protium panel screen to find out what is a scanner.

Speaker Change #180: Antibodies are binding to and this is a very laborious and time consuming stats and what we want to do is actually going the reverse direction of.

Sean McClain: And what we want to do is actually go in the reverse direction of the de novo model. And so I'm going target to antibody; we go antibody to target. This would allow us to rapidly de-orphan and discover new novel targets much faster than before.

Speaker Change #180: The de Novo models, I'm, sorry of <unk> targeting antibody we have.

Speaker Change #192: <unk> antibody to target this would allow us to rapidly.

Speaker Change #192: You are fine and discover new novel targets much.

Speaker Change #180: Much faster than previous and we could scale Ah patient.

Speaker Change #195: Data and hospital partnerships.

Speaker Change #200: Well. So this is a kind of another key area of focus for us on the <unk>.

Speaker Change #180: AI.

Speaker Change #180: Development front.

Speaker Change #199: As a reminder to ask a question. Please press star one one on your telephone and wait for your name to be announced.

Speaker Change #187: Please standby for the next question.

Speaker Change #194: The next question comes from Lee Chen with H C. Wainwright Your line is open.

Lee Chin: Can you hear me well? Yes. Hi. I have two questions. One is to expand on the previous discussion on abscise differentiation.

Speaker Change #186: Hello. Good morning, this is leto, okay, Jimmy well.

Speaker Change #186: Yes.

Speaker Change #211: Hi, I have two question one is.

Speaker Change #184: To expand on previous discussion.

Speaker Change #191: As far as differentiation so since the release of the 101 data.

Lee Chin: So since the release of the one-on-one data, have you seen any shifts in the nature of the inbound partnerships, partner interests? What I mean is that you said the previous partnerships were primarily driven by the Ampitobe-specific antibody design. So anything, any other capability that your partner is interested in, primarily focused on antibody design, and I have another question around 201. Yeah, Zach can speak to the interest in ABS 101 and the discussions that we've been having on that, but I can say that they are very robust discussions, but Zach, I'll hand that over to you.

Speaker Change #184: Have you seen any shift in the nature of the inbound partnership a partner interest what I mean.

Speaker Change #184: Is that.

Speaker Change #185: Set the previous partnership horse.

Speaker Change #209: Primarily driven by the.

Speaker Change #185: Specific antibody design, so any anything any other.

Speaker Change #185: Capability that your partner is interested with plenty of focus on antibody design.

Speaker Change #204: And I have another question around <unk>.

Speaker Change #185: Yes, I can speak to the interest on AVX 101, and the discussions that we have been having on that but I can say that they are very robust discussions with Zack I'll hand that over to you.

Lee Chin: Yeah, we have had a lot of nice inbound interest around that asset and continue to have discussions. Our strategy, as Sean elucidated earlier, is to move that asset forward into phase one clinical studies. But we're certainly entertaining discussions now and happy to see the interest for potential partners in that area. And the second part of your question, I'll just mention, I think this epitope specificity has been really intriguing to potential partners.

Zack Smith: Yes, we have.

Speaker Change #203: <unk> had a lot of nice inbound interest around that asset and continue to have discussions.

Zack Smith: Our strategy is.

Sean: Sean We stated earlier is to move that asset forward into phase one clinical studies.

Speaker Change #202: But we're certainly entertaining discussions now and happy to see the interest from.

Speaker Change #202: From potential partners in that area on the second part of your question I've just mentioned.

Speaker Change #217: This epitope specificity its been really intriguing to potential partners, so highlighting the capabilities of our platform and designing that asset I think of.

Lee Chin: So highlighting the capabilities of our platform and designing that asset, I think, has been really helpful, has been quite interesting to a number of potential partners and existing partners, as well as our ability to design in unique features in some of our other assets. For example, in case studies, we've shown an ability to design in pH-dependent binding, multivalency, unique properties that can be differentiating in a clinical setting.

Speaker Change #217: Been quite an interesting to a number of potential partners and existing partners as.

Sean: As well as our ability to design and unique features so in some of our other assets and case studies, we have shown an ability to design in ph dependent binding multi valency.

Sean: Unique properties that can be differentiating in a clinical setting. So I think that's an exciting new area for us.

Zachariah Jonasson: So I think that's an exciting new area. Thank you very much. My second question is on 201. Can you give us some color on the current competitive landscape of 201 in that undisclosed disease area? And what's your confidence in the differentiation factors from the current SOC and pipeline drugs? Thank you.

Speaker Change #212: Great. Thank you very much my second question is one to one.

Sean: You gave us some color on that.

Speaker Change #205: Turning to competitive landscape of 201 in that undisclosed disease area.

Speaker Change #218: What's your confidence of the differentiation factors from the <unk>.

Speaker Change #220: <unk> and pipeline Brooks. Thank you.

Speaker Change #205: Yeah.

Speaker Change #205: Yes, absolutely Christian do you want to take that one.

Christian Stegmann: Yes, thank you. My audio is cutting out for a moment. So your question is around ABS 201. Yes, it is around the competitive landscape and differentiation factors. Yes, so we have not disclosed the precise indication for ABS-201-NET, not yet, but I will share that this is an indication of high unmet medical needs where the current standard of care is unsatisfactory. And we also plan to employ extended half-life antibody technology to basically improve patient convenience as well, just like we did for ABS 101.

Speaker Change #198: Yes, Thank you and my audio was cutting out from them. So your question is around <unk>.

Speaker Change #198: Yes.

Speaker Change #215: Around the competitive landscape and differentiation differentiation factors.

Speaker Change #205: Yes, so we have not disclosed the precise indication for Avs tour one net.

Christian: But I will I will share that.

Christian: This is an indication of.

Speaker Change #198: High unmet medical need.

Speaker Change #201: Whereas the current standard of care is unsatisfactory and we also plan to.

Speaker Change #201: We also plan to employ extended half life antibody technology to basically.

Speaker Change #201: <unk> patient convenience as well just like we did for Aps 101.

Speaker Change #201: So in essence, we will deliver a best in class profile not only from an efficacy standpoint, but also from a patient convenience standpoint.

Jeremy Target: Yeah, and I will also mention as well this target is a very underappreciated alright, Jeremy target and in this case, we would be second to the clinic.

Speaker Change #201: So it's not a very crowded space, a very underappreciated target I'd say almost very similar to Tijuana.

Lee Chin: Great, thank you very much. I have no further questions at this time. This will conclude today's conference call. Thank you for participating. You may now disconnect.

Speaker Change #219: Great. Thank you very much.

Speaker Change #219: Okay.

Speaker Change #221: I show no further questions at this time.

Speaker Change #212: This will conclude today's conference call. Thank you for participating you may now disconnect.

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