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. After the speakers’ presentation, there will be a question-and-answer session. [Operator instructions] Please be advised that today’s conference is being recorded. [Operator Instructions] I would like now to turn the conference over to Alex Khan, Vice President Finance and Investor Relations. Please go ahead.

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.absi.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, 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 statements 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 undue reliance on forward-looking statements. 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 and 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 May 14, 2024. With that, I will turn the call over to Sean.

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 will host on a regular basis moving forward. There are a few reasons for this change. 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 partner. Our new hybrid business model, including our internal pipeline gives us more opportunities 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 have made in 2023 before discussing our programs in 2024. Later in the call, Zach will provide more details on the status and outlook for each of our internal programs and our business as a whole. 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 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 that train AI creates and will that be validate our platform is designed to continuously learn and improve as a result of our…

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 to certain value inflection points, for example, through a Phase 1 or potentially Phase 2 clinical trial, before selling, partnering, or out-licensing set asset. A primary rationale for our strategies 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. As we have said in the past, every program is unique and there is no one size fits all strategy for these assets. As the best practice and guidance 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, pharma industry estimates we have seen pin such figures at three plus years to reach a drug candidate and at a cost of $30 million 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 pipeline. 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,…

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? Question-And-Answer Session Thank you. [Operator Instructions] One moment for the first question. The first question comes from Kripa Devarakonda with Truist Securities. Your line is open.

Hey guys. Thank you so much for taking my question. I have a question about ABS-101. We recently saw exciting preclinical data from the program. I was just wondering if you can talk about your level of confidence that this drug is differentiated versus the other drugs in the same class. Do you - 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? 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 the TL1A and in particular with the monomer versus trimer.

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 TL1A. So we selectively chose an epitope on the monomer that shows no discrimination for monomer versus trimer binding and we designed antibodies using AI. So we completely avoid epitopes that's span multiple sub-units. 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 isoforms. This may have relevance in clinical trials, because it's known that certain monomers are expressed differentially in a certain patient populations.

Great. Thank you so much. Sean, I have a question for you, a big bigger picture question. You were talking about 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, 14 months is already great and $5 million to develop a drug is already great, but just wondering about that. Thank you.

Yeah, 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. 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 cost 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.

Great. Thank you so much.

Next question comes from George Farmer with Scotia Bank. Your line is open.

Hi, good morning, everyone. Thanks for taking my question. I was wondering if you could give us a heads up on what we can expect to see from the non-human primate studies ongoing with ABS-101 later this year.

Yeah, absolutely. Christian, do you want to take that?

Yeah, absolutely. So our non-human primate pharmacokinetic studies are expected to demonstrate that we indeed are able to show an extended half-life of our antibody that’s de-risking the pharmacokinetic profile in humans. So we, in the next few months we will be able to demonstrate that our antibody engineering approach to extend the half-life of the antibody have worked.

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

Yes, we will absolutely measure the non-pharmacodynamic market, as well, obviously, and exactly as you mentioned, it’s demonstrating an extended effect on the pharmacodynamic biomarker will then obviously also de-risk efficacies, Very good point.

Okay. Great. And then, maybe a bit on cash. Your guidance implies, I think some funding coming in probably from partnerships is probably the best guess. Can you kind of elaborate a little bit more on that relative to how we should think about cash usage through 2027?

Yeah, we do see.

Yeah, that’s for Zach.

Yeah, I was going to say, George, we continue to reiterate our guidance of $80 million of gross cash usage for 2024. That's obviously a gross figure and that includes the complete the cost associated with completing the IND-enabling studies for ABS-101. Are forecasts that take within to 2027 includes some modest assumptions around partnering on a regular cadence. But it doesn't include any assumptions around a significant partnership deal. So it's to kind of our typical run rate assumptions built into that. And then, I would point out too, if you look at our net cash usages, that typically comes in well under gross. So, for example, if you look at H2 of 2023, the net cash usage for that second half of last year was roughly $27 million in total. And the net cash usage for Q1 of this year was roughly $15.9 million, which is a little higher given that we paid bonuses in March. So as can see our net cash usage is coming well in - coming well under the gross cash usage.

Yeah, okay. Thanks very much, Zach.

One moment for the next question. The next question comes from Jacqueline Kisa with TD Cowen. Your line is open.

Hi, this is Jacqueline Kisa on for Steven Mah. Thanks so much for taking the question. With the 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 WuXi at the current moment and given the recent discussions that have been ongoing with that, we do believe that the relationship with WuXi will not put us at risk with the current program. But we are engaging with other CROs and do have backup strategies to mitigate any other potential tailwinds that may occur with the new legislation that that may come out.

Great. Thank you. I appreciate the color. 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 before or new therapeutic area? And is the company right-sized to serve both your internal and partnered programs?

Yeah, it's a great question. So, we are focusing on I&I as well as oncology. So we'll fall in one of those therapeutics areas. And then, additionally, we are currently right-sized to be able 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 of the translational side and clinical side. But we see that as modest growth as these programs are being undertaken.

Great. Thank you. And then, if I could just squeeze one more in? Technologies in the AI drug 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 tech in-house?

Yeah, one of the areas that we see as 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 a new novel on biology with standard approaches like stage display, 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 novel biologies from those epitopes. And so, we see this as a major differentiation. This is really what's driven partnerships with AstraZeneca, Almirall, Merck and we will continue to drive our partnership pipeline, but also drive our own internal development, as well. And we have applied that to the internal programs, as well.

Great. Thank you so much. I appreciate it.

One moment for the next question. The next question comes from Steve Dechert with KeyBanc. Your line is open.

Hey guys. Thanks for the question. Could you give us some more color on how discussions are going with potential partners? Is there a wait to get into your goal of four partners this year?

Yeah, I can comment on that, Sean. I'd say well, 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 a even cadence throughout the year. But I would say that our pipeline of discussions is robust and covers both large pharma, and mid and small biotech, as well as leading academic institutions. And as we have these discussions and prosecute the BD strategy, we're really looking for partners who bring a 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 mentioned.

Okay. Thanks. And then, are there any new capabilities that you're investing in, as it relates to your platform? Thanks.

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 neurology side. And one of the areas that we see as a 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 protean panel screen to find out what these antibodies are binding to. And this is a very laborious and time-consuming steps and what we want to do is actually going to reverse direction of the de novo model sensor is going targeting antibody, we go antibody to target this would allow us to rapidly de-orphan and discover new novel targets much faster than previous and we could scale patients’ data and hospital partnerships, as well. And so, this is a kind of another key area of focus for us on the AI development front.

Please stand by for the next question. The next question comes from Li Chen with H.C. Wainwright. Your line is open.

Hello. Good morning. This is Li Chen. Can you hear me well?

Yes.

Hi, I have two questions. One is to expand on previous discussions on the upsize differentiation. So, since the release of the 101 data, have you seen any shifts in the nature of the inbound partnerships or partner interests? What I mean is that you said that previous partnerships were primarily driven by the epitope-specific antibody design. So, anything - any other capabilities that your partner is interested with primary focus on antibody design? And I have another question around 201.

Yeah, Zach can speak to the interest on 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 medics inbound interest around that asset and continue to have discussions. Our strategy as Sean illustrated earlier is to move that asset forward into Phase 1 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, I think this epitope specificity it’s been really intriguing to potential partners. So, highlighting the capabilities of our platform and designing that asset I think has been quite been 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 and case studies, we've shown an ability to design in pH-dependent binding multi band with the unique properties that can be differentiating in a clinical setting. So I think that's an exciting area for us.

Great. Thank you very much. And 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 of 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 was cutting off from and so your question around ABS-201?

Yes. 201 around the competitive landscape and differentiation factors.

Yes. So, we have not disclosed the precise indication for ABS-201 yet. But I will share that this is an indication of high unmet medical needs where this 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 this for ABS-101. And so, in essence, we will deliver a best-in-class profile, not only from an efficacy standpoint platform, also from a patient convenience standpoint.

Yeah, and I will also mention, as well this target is a very underappreciated derm target. And in this case, we would be a second to the clinic. And so, it's not a very crowded space. It’s a very underappreciated target, I'd say almost very similar to TL1A.

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.