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.

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 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. 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.

We started 2023 with the release of a foundational manuscript demonstrating a first in creating and validating de novo antibodies zero-shot generative AI. Over the year, we expanded our models, harnessing the proprietary wet lab technologies to generate scalable biological data for model training and validation. We continue to build our talented team, optimize our organization and integrate all of our platform capabilities deeply.

In line with our hybrid business model, these does aimed to leverage our platform to create a pipeline of assets and establish validating partnerships with companies like AstraZeneca and Almirall. In October of last year, at our inaugural R&D Day, we reached the 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.

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 a differentiated antibody 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. At the beginning of 2024, we unveiled positive preclinical data for this program and by the end of February, we initiated our IND-enabling studies.

As we advance this program, I want to highlight our platform’s efficiency in generating this program and the potential vast 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 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 us, powerful, novel biotech business model, we can generate a differentiated antibody candidate and complete IND-enabling studies at a cost of approximately $15 million.

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 collaborations.

This year and beyond, we look forward to entering into additional partnerships with pharma and biotech companies. These partnerships will leverage our platform to enable and advance their drug discovery programs, but potentially shortening timeframes, lowering costs, improving success probabilities and unlocking new biologies previously thought unachievable. I am incredibly proud of our team at Absci for these achievements and excited to see the promise of our platform flight 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. 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 by what lies ahead. We remain laser focused on execution across all aspects of our business, including partnered and internal programs, with innovation and the pursuit of being possible 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?

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.

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, 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.

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

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

Yeah, that’s for Zach.

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

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.

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.

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.

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

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.

Yes.

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, absolutely. CHRISTIAN do you want to take that one?

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.

I show no further questions at this time. This will conclude today's conference call. Thank you for participating. You may now disconnect.