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Good day and thank you for standing by. Welcome to the Absci Second Quarter 2024 Business Update Conference 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. I would now like to hand the conference over to your speaker today, Alex Khan, VP, Finance and Investor Relations. Please go ahead.

Thank you. Earlier today, Absci released financial and operating results for the quarter ended June 30th, 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 the email to investors.absci.com, available for a 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

Thanks, Alex. Good afternoon, everyone and thank you for joining us for our second quarter business update call. Today, I'm excited to be sharing updates around new and existing partnerships, as well as continued progress on our own internal pipeline of programs. As always, these achievements are a testament to the work our team does each and every day and reflects our platform's differentiated capabilities in AI drug creation for biologics. With our integrated drug creation platform's unique capabilities in creating differentiated antibody candidates, we believe we offer valuable proposition to potential partners to work together on therapeutic programs. Along those lines, we are pleased to announce that we have recently entered into a new collaboration with Memorial Sloan Kettering Cancer Center, a leading cancer treatment and research center to jointly develop up to six therapeutic programs. MSK has an incredible record of groundbreaking translational and clinical innovations in oncology. By combining MSK's research expertise with our generative AI drug creation platform, we have the potential to unlock critical advances towards treating these devastating diseases. We at Absci are proud to be adding another great partner to our list of collaborators. Now including Astra

Thank you, Sean. As Sean mentioned, we are pleased to have recently announced our new collaboration with Memorial Sloan Kettering Cancer Center, a world-leading cancer treatment and research center, to discover and develop up to six novel oncology therapeutic programs using generative AI. Under the terms of the collaboration, world-leading research teams from both Absci and MSK will work together to co-develop therapeutics designed using Absci's integrated drug creation platform. We believe this co-development collaboration with MSK will leverage considerable synergies between the two organizations. The collaboration will combine MSK's target research and validation capabilities with our generative AI drug creation platform capabilities to potentially create differentiated antibody therapeutics towards novel oncology targets. Furthermore, Absci and MSK plan to collaborate on the early development of these therapeutic assets in advance of out-licensing or partnering them. By working with a premier research institution such as MSK on co-developing therapeutic programs, we aim to leverage R&D synergies that could lead to significant value creation through the generation of first-in-class therapeutics addressing significant unmet medical needs. Moreover, such co-development collaboration structures, which include cost sharing, allow Absci greater diversification on a capital-weighted basis. Our pipeline of potential new drug creation and co-development partnerships remains robust. Hence, we continue to anticipate signing partnerships with at least three more partners in addition to our multi-program partnership with MSK during 2024. This will bring us to a total of at least four new partnerships this year. We look forward to utilizing our expanding set of generative AI capabilities in existing and new partnerships. A particular focus area for existing and potential new partners is leveraging our platform to provide epitope specificity and epitope landscaping at both the local and global level. Our global epitope landscaping capability supports epitope selection by allowing testing and validation of the potency in MOA associated with different epitopes on a given antigen. Our local epitope landscaping capability then enables the identification of desired epitope interactions for potentially improving potency in MOA. That is, once an epitope is selected, our AI model exhaustively samples interface contacts with a designated epitope to further refine potency in MOA. Together, these capabilities offer the potential to enhance potency, reduce biological risk, improve and broaden IP claims, and to achieve differentiated MOA for a given program. We believe that these capabilities and others, such as the ability to design tunable selectivity, multivalency, and pH-dependent binding, make our platform highly attractive to potential partners. As Sean discussed, our growing portfolio of programs includes three wholly owned assets: ABS-101, ABS-201 and ABS-301, all of which were generated using our integrated drug creation platform. We continue to advance these internal programs according to plan. We also continue to make progress on new internal programs and expect to advance at least one additional internal therapeutic program to the lead stage later this year. As a reminder, our business model is focused on out-licensing or selling our internal programs and co-developed programs following value inflection proof points anywhere from preclinical proof of concept to Phase 2 clinical proof of concept. Turning now to our financials, revenue in the second quarter of 2024 was $1.3 million. As we continue to progress our partnered internal programs concurrently, research and development expenses were $15.3 million for the three months ending June 30th, 2024, compared to $12.1 million for the prior year period. This increase was primarily driven by increased lab operations, including direct costs associated with IND-enabling studies for ABS-101 and an increase in stock compensation expense. Selling, general and administrative expenses were $9.3 million for the three months ending June 30th, 2024, compared to $9.4 million for the prior year period. This decrease was due to lower personnel costs and continued reductions in administrative costs offset by an increase in stock compensation expense. Turning to our balance sheet. We ended the quarter with $145.2 million in cash, cash equivalents and short-term investments as compared to $161.5 million as of March 31st, 2024. We continue to enhance our focus on high value proprietary internal programs and co-development arrangements while also seeking high quality drug creation partnerships with industry leaders who can bring talent and complementary expertise. We believe focusing on these initiatives to build a diversified portfolio of partnered programs, rather than simply pursuing a higher volume of programs, best positions us for further success in the future. For 2024, we continue to expect a gross use of cash, cash equivalent and short-term investments of approximately $80 million, including 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.

Thanks,

[Operator Instructions] Our first question comes from Steven Mah with TD Cowen. Your line is open.

Great. Thanks for taking the questions. I had a question on ABS-101, the non-human primate data. When you're saying that the two to three times additional half-life and the bioavailability, is that based on head-to-head data that you use from competitor molecules, or is it based on publications on the clinical competitors?

Yes, great question, Steve. So it is a head-to-head comparison with the clinical competitors. And Christian, do you want to dive into the details on that?

Yes. Thank you, Sean. Absolutely. We have indeed compared ABS-101 with two competitor molecules that are in clinical development. This is RVT-3101 and MK-7240. So the Roivant molecule and the Merck molecule. And we could see in our study head-to-head that we have seen a two- to-three-fold improvement in plasma half-life of ABS-101 over these two molecules. Does that answer your question?

Yes, I guess you got the sequences of the antibodies from their patents and then you expressed them yourself to do the head-to-head studies.

That's correct, yes.

Okay. Got it. All right. And then a quick one on the Memorial Sloan Kettering partnership. Can you give us a little bit more detail on the level of the code development that your scientists and the MSK scientists are going to be working on? Also if there's any IP sharing details you can share, and then if MSK is going to be providing any patient real world data or the data genomics, genome profiling, or proteomics? Thank you.

Absolutely.

Sure. Yes. Steve, we're really excited about this partnership with MSK. It's a -- to think of this as a 50-50 cost sharing co-development platform where we're going to look at six different programs. MSK will be bringing a lot of validation around novel targets, so that validation work could encompass all of the areas that you referenced. We will jointly decide on which programs to nominate into program development for us to work on from the drug creation side, and then would be collaborating throughout that process, including, once we have a drug candidate to advance those through IND-enabling and potentially through Phase 1 development. Does that answer your question?

Yes, that does. Thanks.

Thank you. Our next question comes from Kripa Devarakonda with Truist. Your line is now open.

Hi, guys, thank you so much for taking my question. So, I have a question about the ABS-101 non-human primate data. Obviously, it's the totality of the data and the totality of the profile of the drug that is important. And you lead out -- know how the drug compares with the other drugs on different metrics. But I was wondering if you were to pick characteristic of the drug that you think will be tough to replicate for a competitor and help maintain the differentiation, which ones would you point to? Thank you.

Thanks, Kripa. Christian, you want to take that?

Yes, absolutely. Great question. So, I think in a nutshell, the totality of the data in the way we differentiate from competition is the combination of attributes we have combined here overall to achieve a best-in-class profile. So what we mean by best-in-class profile, we have achieved very high affinity of both the TL1A trimer, as well as the monomer, we have achieved significant plasma half-life extension over competitors. We've achieved very good CMC properties that allow us to formulate this molecule at 200 mg/ml. And then finally, we have also worked on the immunogenicity profile, which will hopefully lead to lower antidrug, antibody rates in clinical development. So, overall, I think it's the combination of different attributes all addressing liabilities of the competitor molecules that will make ABS-101 a highly differentiated asset.

Got it. And then you mentioned the 200 milligrams per milliliter concentration. That's a pretty high concentration. I was just wondering if, while you were designing the molecule itself, was there anything that was engineered to be able to give you this high level of solubility of the protein?

Yes, absolutely. The artificial intelligence engine we have built at Absci clearly aids us in improving developability properties of all our antibodies. So, in essence, we are really leveraging artificial intelligence to basically improve our antibody profiles. And that certainly includes CMC properties that allow us these high concentrations.

Okay, great. Thank you so much.

Thank you. Our next question comes from George Farmer with Scotiabank. Your line is open.

Hi. Good afternoon. Thanks for taking my questions. Also, some more questions on the 101 NHP data. Can you talk about toxicity and how high you dosed in these animals? I'm assuming this is part of your GLP tox studies, is that right? And also, you know, you mentioned a number of partnerships that you're counting on closing this year. Can you give us a ballpark estimate of how much cash you think that will bring into the company? Thanks.

Yes, thanks, George. Christian, you want to take the first one then?

Absolutely. So, yes, you are correct. Our GLP toxicology studies are currently ongoing, and we will disclose the results of this study once they are concluded. And we have aligned on the publication strategy for those. We have not yet disclosed the doses of these studies.

Sure. And I can address the second question. So, we don't have guidance on cash inflows from partnerships, but we do have guidance on bringing in three additional partners in addition to the MSK partnership this year. Some of those would likely be multi-program partnerships and those could range from more traditional drug creation partnerships that have upfronts and milestones as well as development milestones and royalties to arrangements that are like what we've done with MSK, which are co-devs or co-development programs.

Okay, great. Sorry, Sean, go ahead. Yes.

So, I was just going to say, yes. We've given guidance on the four partnerships. This is one out of the three. So we do expect another three to be announced from now through the end of the year.

Okay. Yes. Great. And then regarding the MSK partnership that you have, does MSK have publication rights, can we expect that they'll be kind of actively publishing papers on the fruits of this collaboration or is that going to be restricted in some way?

Yes, that all flows through the joint steering - go ahead, Christian.

Go for it,

Yes, I was just going to say that has to be done in joint collaboration as well. So we have a joint steering committee that oversees the partnership. And so publication decisions would run through that committee.

Okay. But the plan is to be able to publish the work in the future. Right, great. All right, thanks very much.

Although to your point, George, I think we will work with them to be careful about publishing too early. But yes, so there is - it's a decision that's made jointly. But to Sean's point, we do want to publish on some of the great science we'll be doing there.

Yes, of course. Okay, thanks again.

Thank you. And our next question comes from Vikram Purohit with Morgan Stanley. Your line is now open.

Hi, everyone. This is Morgan on for Vikram. Thanks for taking your question. So we had one on ABS-201. Do you anticipate disclosing the target upon choosing a development candidate later this year? Thank you.

Yes, we do plan on disclosing the target once the development candidate is selected, either at the end of this year or beginning of next year.

Okay, thanks.

Thank you. And our next question comes from Scott Schoenhaus with KeyBanc. Your line is now open.

Hi, team. Thanks for taking my question. I wanted to quickly ask on 101, you mentioned in your release that it was observed to have an increased bio-distribution in non-human primates. And then you say this could lead to you know, faster penetration, basically. When will you have a readout on that? Or when will you be announcing more on that specific attribute?

Yes. Thanks, Scott. Christian, I'll let you take that.

Yes, absolutely. So, what we disclosed today are non-human primate data. And obviously, these data are usually quite translational into the human setting. However, of course, there are caveats. These are not humans. We think the ultimate proof on the pharmacokinetic properties will be in the clinic. So, we will observe during our first-in-human study the actual pharmacokinetic properties in humans. And we think these data will then be very telling regarding the biodistribution properties, which we now think are quite promising based on the non-human primate data. Does that answer your question?

Yes. Thanks. And then a follow-up on the partnerships, just generally speaking, team, I guess Sean and

Yes, I think that what we're seeing is pharma and great institutes like MSK are looking for differentiated technologies, such as what Absci is developing. I think one of the things that got MSK excited about what we're doing here is being able to start to drug some of these undruggable targets like GPCRs and ion channels using our AI drug discovery platform. And that's what we're seeing in discussions with large pharma and biotech as well. And I think if you can start to have -- show that AI can be highly differentiated and ultimately create differentiated assets, whether best-in-class or first-in-class, that is really driving discussions, even, I would say, in a backup, that has been tougher for biotech. And so I think that that's really exciting to see that kind of, regardless of the environment, we are seeing high interest just given the differentiation we have in our AI platform.

Great. Thank you so much.

Thank you. And our next question comes from Li Chen with H.C. Wainwright. Your line is now open.

Hi, everyone. This is [indiscernible] for Li Chen. I have a question regarding the breadth of the potential of your epitope capabilities. So, should we think about it as a disease-agnostic capabilities, or do you think there are certain disease indications that your platform is particularly good at identifying? And related question is that in the future, how we should actually think about partnership focus? Is it more oncology and cytokines where you have discussion regarding additional therapeutic areas? Thank you.

Yes, absolutely. So we really see this as disease-agnostic really the input to our model is the structure of the target, whether that's experimentally derived through, let's say, Cryo EM or X-ray crystallography, or it is computationally derived through, let's say AlphaFold. You take that structure of the target and you feed that into the model, and then you can then specify what epitope you want the antibody to bind to, and then the model is able to then design the CDRs that will bind to that particular epitope of interest, allowing you to start to test some of these hypotheses that have been difficult to test in the past just because of the lack of being able to generate antibodies. And so that's where we really see this as disease-agnostic. And you can even see that in our partnerships with Astra

Sure. Can you remind me of your last question?

Yes. It's more about, in terms of future partnerships fully. Should we think about oncology and cytokine focus, or it can also include other potential disease areas?

Oh, yes, absolutely. So we view cytokine biology, really as the first frontier for AI-driven disruption of the biologics market. And we deeply believe that this is really just the first frontier. We are actively working on addressing various path mechanisms with various biologic modalities, really fully leveraging artificial intelligence for drug creation. So absolutely, we are convinced that we can tackle difficult targets as mentioned, GPCRs and other difficult target as well.

Yes. And I would say with our own pipeline, really, where we're focused and we're continuing to stay focused, is in immunology and oncology. And so I think the pipeline programs that you're going to start to see come to fruition will be really focused on immunology as well as oncology. But again, in partnerships, we plan to expand outside of that.

Thank you for the clarification.

Thank you. Our next question is a follow-up from Steven Mah with TD Cowen. Your line is open.

Hi. Thanks for taking the follow-up question. And this question is just more in response to a prior answer you gave where you said that MSK got excited because you can do drug level targets with your gen AI platform. My understanding is that MSK doesn't have any other AI drug development partnerships with industry, and I'm not 100% sure if they have any other non-AI drug development partnerships, but it seems pretty rare for them. So, just curious, if you can disclose, did MSK come to you with some targets in mind, or was it the genesis of the deal with them, was it through your BD team? Thanks.

Yes.

Yes, sure. Yes. So, Steven, this came through the BD interactions, and it started as just a conversation around, you know, how we could collaborate and their interest in how we could deploy AI against some of the novel targets that they're discovering and validating at MSK. And to my knowledge, this is the first partnership they've done with an AI company, and I think they're very excited about it. We're very excited about it. And the second part of your question, did they come with initial targets? And the answer, there is no. Really, this is sort of a real understanding of how these two capabilities could fit together. So, we're starting that process now of starting to look at targets with them, and that's just kicked off because we just signed the partnership. But really, the genesis of this is just understanding how these two platforms could be really synergistic. So, we're going to go through the process now of selecting targets together and advancing those together.

Yes, and I think they saw, like, a lot of the target. Sorry.

No, go ahead, Sean.

Yes, I think a lot of the targets that they are seeing that are emerging are more difficult to drug targets like GPCRs. And I think having this capability, I think it's a really, really nice synergy. I mean, they're bringing the oncology expertise, the disease biology, the target biology. And then we're bringing our AI expertise in the antibody design to be able to develop first-in-class, best-in-class oncology assets. And then obviously being able to work with them on taking this through a Phase 1, I think makes a ton of sense. And so I think the synergies that we have here, I think are going to be really important for not only the success of this partnership, but even with our own oncology pipeline, I think we're going to be able to leverage this partnership to progress our own pipeline as well.

Okay. Thanks for the color and congrats on the partnership.

Thanks, Steve.