Okay. All right, I think we're ready to get going with the next session here. Again, thanks everyone for joining us for the Guggenheim SmallCap Biotech Conference. I'm Vamil Divan, one of the biopharma analysts here at Guggenheim, joined by Arseni Serebritski, one of the associates on the team here. And next up in this room, we have Absci joining me up here. We have Zach Jonasson, who's the CFO and Chief Business Officer, and Alex Khan from the Investor Relations side. So maybe, Zach, I'll just start for those people who might be a little less familiar with this story. Obviously, it's been an exciting time for the company over the last many months here. We picked up coverage a few months ago.
But maybe for those less familiar, just kind of the history of the company and kind of where you got to date, and then we'll go into the questions from there.
Yeah, absolutely. So Absci actually started its journey as a synthetic biology company and was the first company to produce full-length antibodies in E. coli. And what the company has done with that foundational technology is pretty remarkable. They scaled it up in a way where we can now, in flow-based experiments, interrogate millions of different antibody sequences and how they bind to a given epitope. So why is that important? We're generating massive amounts of data that we can then use today to train AI models to help us design antibodies to both fast-follower targets as well as novel targets that can't be addressed with traditional approaches.
If you fast forward to today, we've now scaled our AI models to a place where our de novo model, which is a model where you can input an epitope of a target, and you don't need any parental binder, you don't need to have any other antibody that binds to that target, and the model can successfully design antibodies with high affinity and the profile that you want, meaning highly developable, high affinity, easy to formulate, so on and so forth, to that target of interest. We released some data recently illustrating and demonstrating how we're able to use that platform to create antibodies to targets that you can't address with traditional approaches.
For example, we've worked with Caltech to design an antibody, actually more than one antibody, to the caldera region of HIV, which is a very highly conserved area that cannot be addressed with traditional approaches. We've also been able to have success designing against ion channels with one of our pharmaceutical partners. And earlier last year, around August, we 8-K'd some success in our partnership with AZ, where we used our de novo model to design antibodies to an epitope of a transmembrane protein that the partner was unsuccessful at generating antibodies to using traditional approaches. So we're now at a place with our AI where we've scaled it, and it's generalizing to these so-called undruggable targets. On the other side of it, we've also developed our own internal pipeline.
We work in partnership with pharma to design first-in-class, best-in-class therapeutics to their targets. But starting two years ago, we began developing our own internal pipeline. I'm really happy to say today we've got our lead program, which is ABS-101, an anti-TL1A antibody, which will enter the clinic here in the next couple of months. We will have an interim data readout for Phase 1, interim data readout in Q3, Q4 this year. That antibody looks to have a best-in-class preclinical profile, and we're looking forward to showing that profile to translate into a best-in-class clinical profile starting this year. I do need to mention our second molecule in the pipeline, which I think is really exciting. We just released the target, the indication, and preclinical data supporting it about one month ago today. That's an antibody that's targeting the prolactin receptor.
The indication is hair regrowth for androgenetic alopecia, which is an indication that affects up to 90 million patients in the U.S. alone. We think this is a massive market opportunity. The biology is directly in line with what we're trying to do. The safety profile looks terrific. We're in IND-enabling studies already with that molecule, and it's AI-designed to have excellent developability, high affinity, long half-life. We're expecting to be in the clinic early next year and doing everything we can to expedite that.
Okay. Okay. So before we dive deeper into each of the programs, and you touched on some of this already, but you had a, what we thought was a pretty interesting R&D Day back in December, sort of laid out the vision for some of these lead programs. Maybe you just talk about what were the main takeaways from that event, and then we'll dive into the individual assets a little more.
Yeah. I mean, look, I would highlight three things. One is where we are in the AI platform de novo design. As I mentioned, we're now designing successfully. We're using that platform to design antibodies with exemplary properties to targets that you cannot address with other means. And we showed data supporting and demonstrating that. And so I think that's a huge accomplishment in the field. And we've tracked our progress year in, year out. The reason why we've been successful in expanding the capability of the AI platform is really built on what I started the conversation about, that data platform. So we're constantly doing active learning where we generate data, we train the AI models, the AI models make predictions, and then we run those predictions back through the laboratory process where we can evaluate them at scale, and then we make modifications to the AI model.
It's this iterative loop that we've been running for the past four years that have allowed us to take this leadership position in de novo design. A big part of our R&D Day was on the platform and how it's accelerated its capabilities. I'd say today I firmly believe we're clearly in the leadership position in AI design of antibodies. Then secondly, it was heavily focused on some of the new data we released around ABS-101. We showed some in vitro data supporting the superior ADA profile we expect to see in the clinic. Secondly, more recently, at JPM, we released the PD study, the pharmacodynamics study from our NHP study that we've done with our CRO. That PD data looked exemplary as well. We showed prolonged target engagement out to the full-time course of the study, which was 60 days.
We're looking at a greater than 3x improvement in durability of target engagement versus similar doses of the Merck molecule as well as the Roivant molecule. We also saw dose response, which we wanted to see in that study. We also saw that our subQ formulation was directly in line with the performance of the IV. We're really looking forward to that Phase 1 readout later this year, and we're all set for our subQ formulation. Finally, a heavy focus in our R&D Day was on ABS-201. That was the release of that indication and that target. I guess what I would say there is excellent safety profile. The biology is very clear. It looks to be a mechanism that can be a durable effect.
So if we're correct here, this could be a course of treatment that's maybe three injections over six months. And the average human might see a four-year durability of effect for hair regrowth and potentially restoration of pigmentation. We think that could translate into a market that's easily $20 billion a year in the U.S. alone.
Okay. Great. So then the 101 data you touched on this that you presented last month, the non-human primate data. So just sounds like interesting data you have here. What were you looking for going into that? Maybe kind of what you saw versus what your expectations were going in. And now this is obviously a pretty competitive space. A lot of players. You mentioned Merck and Roivant, but others out there too. How does that profile sort of set you up in terms of moving forward potentially in terms of the competitive landscape here?
Yeah. Look, I've been doing science for a long, long time. It's very rare that you get a study done and it's exactly as you hoped it would be. But in that PD study, we saw exactly what we want to see. And that's what we want to see in human patients. So in that NHP setting, we saw that durable target engagement over the full 60-day life of that study. We saw at the same dose, the Merck and the Roivant molecule fall off. So we're looking at at least a 3x improvement in the durability of target engagement. So we'd like to see that in the human Phase one as well. We also saw that our subQ formulation is working just as designed. And I should mention we have a high concentration formulation there, 200 mg per mL.
We're very well set up to go directly for subQ throughout clinical development. I would say very happy with the profile there. As we look forward, we think we're differentiated, not just in affinity and potency, but we hit the monomer and the trimer, which we think could translate into some additional efficacy for certain types of patients. We also have, as I mentioned, the subQ formulation, the longer half-life. And I think one of the underappreciated components is what I alluded to earlier. We think we're going to come with a very low ADA profile, similar to what Merck has. And I think that's going to be a growing concern as you see further clinical development of Roivant. We're not sure exactly how the ADA profile will look for some of the next-gen competitors, but we're aware that their epitopes are more similar to where Roivant's is.
So we think we're well positioned to have a superior ADA profile on a longer half-life therapeutic. And Alex, I don't know if you want to add to that, but we're really excited about the profile.
Yeah. Not totally. Okay. So maybe then shifting to 201, obviously massive market opportunity here. Maybe you just talk a little bit more about the pathway that the target here. And then I think there's also a competitor in China, I believe, or in Asia that maybe you can just talk about the competitive landscape and then also just sort of, again, obviously early days still, but the development sort of pathway here.
Yeah. It's really exciting. The biology is really interesting and very clear to us. And I would say our head of R&D and members of his team actually worked on this target when they were at Bayer. So there's a long history and institutional knowledge that was part of our team here at Absci. But if I'm going to summarize the mechanism here, what you find in androgenetic alopecia is the hair follicles have hyperprolactinemia. And that leads to a movement of the hair follicle into an anagen phase, which is a phase where you're shedding hair, you're not growing hair. So what we're doing by targeting the prolactin receptors, we're interrupting that signaling, and we're shunting the hair follicle back into the anagen phase from the catagen phase. And the anagen phase is the growth phase.
That's typically for a human a two to six-year durable period of hair growth. Our objective here is to treat patients with this approach, like I said, potentially up to three doses over six months and move potentially almost all of the hair follicles that are in this catagen phase back into the anagen phase, so thereby providing a durable efficacy that can be appreciated by patients. This is why we refer to this as a completely new type of therapy for this market. Right now, the standard of care is minoxidil or finasteride. Both of those have side effects. They have very limited efficacy, very variable efficacy. For women patients, they can't use f inasteride, so they're even more limited. Those agents you have to apply topically every day or you see an immediate regression.
This is a new type of therapy which could give durable efficacy. And again, it's all focused on moving each of these hair follicles that's in a catagen or telogen phase back into that anagen phase.
Just to remind us, I know you're trying to move quickly with this program. What's the next sort of update in terms of?
Yeah. We're currently in IND-enabling studies. We're looking to maybe do some additional animal work that we would release later this year. But the goal is to move as rapidly through the IND-enabling and get into a Phase 1 setting. It's a SAD study as soon as possible and then transition that to a MAD. The goal would be to have proof of concept by late 2026.
Yeah. For this program, even before we unveiled it publicly, we assembled this network of KOLs who, about a dozen or so of them, which is growing by the day. Just among that network, they alone see about 500,000 androgenetic alopecia patients in their clinics each year. They're advising us very closely on the clinical path for development here. They think it would be a quite straightforward path to enrollment and to the endpoint. So we feel confident in having the sort of expertise around us for this program.
Yeah. I mean, and just to pick up on what Alex is saying, I mean, part of the other really exciting feature of this program is we can execute the clinical development. The endpoints are well established in pharma. You're basically taking microscopic images of different points on the scalp, and you're doing hair count. You're assessing the width of the girth of the hair. You're looking at coloration. All very objective endpoints. And what we've been told by the KOLs that we have around this is that there'll be a waiting list to get into these trials. So recruitment won't be an issue. The trials are not expensive to run, and the market is enormous.
Okay. Let me turn to our study.
So maybe a quick follow-up on this 201 program. I understand you haven't started clinical development yet, but is there anything on the preclinical side that gives you confidence in the efficacy of this approach and also potential safety?
Absolutely. There's in vitro studies using biopsies from patients that look at prolactin signaling, and you'll see that if you get over-signaling prolactin, you'll see pigmentation is lost, and you'll see that you move that follicle into that catagen phase, so there's good biology mechanism behind the target, but even more importantly, there's a wonderful translational model, so Bayer commissioned a study with its antibody, which has now been licensed to a small Chinese company, and in that study, they looked at a certain type of macaque monkey that actually at adolescence has natural androgenetic alopecia, and in that study, they were able to show after dosing a four-year durability of effect, and you can see visibly the regrowth of hair and the restoration of the black coloration, so it's very rare that you get a translational model in animals where you're not chemically inducing the disease or the disorder.
Here, it's a naturally occurring androgenetic alopecia in a non-human primate. And you saw extended durable efficacy. We have also since with our molecule recently done a mouse study. And we selected a particular strain of mouse, and an age of that mouse when we know the hair follicles are in that catagen phase. And then we shave the mouse. We treat it with our molecule. We also treated it with minoxidil as a positive control. And we saw significant regrowth of hair versus minoxidil in that study. And that's data we released around JPM as well.
And your question on the safety component, there is a case report from the New England Journal of Medicine from a few years ago of a patient, a woman who reported to the doctor presenting because she was unable to lactate. And what they found in doing the study is that she had a complete natural double knockout of the prolactin receptor her entire life. And when they ran the serum hormone electrolyte levels, everything completely normal. She lived a completely healthy life, still alive, has two healthy children. So the safety profile for this looks very clean as well.
Yeah. I mean, it's very rare you get that animal translational model that's so good, and then you get a human knockout as a safety signal. So we feel very comfortable with the efficacy profile and the safety profile as we move into human clinical.
You can't have healthy volunteers who are affected by alopecia, right? Potentially you can get to a proof of concept very quickly.
Absolutely. That's why we believe we could get to some proof of concept here in 2026.
And then last question on 201. You mentioned that the effect is very durable, for example, the effect that we see in animals. I understand it's the early days, but how do you think it will be dosed ultimately? Is it the type of thing that's like once a year, once a quarter?
Yeah. I mean, our thinking now based on the modeling we've done is you do a six-month course of therapy, two to three injections over that six month. Recall we have a half-life extension built into the Fc of this molecule. So two to three doses over six months. And then the durability could be two to six years. So I'd say on average around four years for a human patient. And then when you get close to that four years, you'd come back in for a new course of therapy. We've talked to KOLs about this too, and they think that this is very conducive to patients. Patients are very used to injectables today. It's actually the fastest growing category of aesthetics right now and the highest margin. And the other thing that's really interesting here is the provider networks for this are immense.
If you look at everything from dermatologist offices all the way to med spas, if you look at those types of clinical offerings, there's more of those centers in the U.S. than there are Starbucks. There's a ready go-to-market here. A lot of providers are very interested in having a product like this.
So then maybe we can talk a little about some of your other programs that are further back in development. Specifically, you already touched on this HIV caldera study , but I'm curious to hear about ABS-301 and your reverse immunology platform. I understand there are no near-term catalysts for that program, but what gets you excited about it?
Yeah. And that's a great point. And I think it also just kind of speaks to the diversity of our platform and portfolio that we have because we have ABS-101 for TL1A. We have ABS-201, prolactin receptor for hair regrowth. And then ABS-301 is a potential first-in-class IO target that we discovered with our reverse immunology platform. This is combining TLS biology, AI, and our wet lab to essentially discover novel targets and antibodies that we then optimize to bring forward to a drug program. So to your point, that one is earlier on in our pipeline, but we do look to have a DC for that in the first half of this year.
We did have some data out at R&D Day a little bit more about this, and we are intentionally keeping the target masked for a little bit just given the first-in-class nature of this novel target we discovered. But with the data we've seen, we see that it could be implicated in a lot of squamous cell carcinomas, particularly head and neck and esophageal. And we showed some data at R&D Day as well showing that with some data from Tempus that there's high expression levels of this target in patients even after they've had chemo or even after having checkpoint inhibitor treatments. So we see a broad opportunity in those types of cancers as well. But to your point on the HIV caldera, I mean, I think that was a fantastic case study.
It's gotten a lot of potential partners excited too because it demonstrates, as I had mentioned earlier, sort of the more unique capabilities of our platform, that it's not just about trying to design an antibody faster or cheaper, but designing something better or designing something that could not be done at all. So for example, in this case, something that creating an antibody long enough and stable enough to get into the deep crevice of the HIV caldera, to our knowledge, has not been something that's been able to be done before. And does that give us anything else on the HIV study, the UCLA work to touch on?
Just to your point, I mean, it's a really difficult design challenge. If you put undruggable targets in a rank order, that's somewhere near the very top, and so it was really, I think, a significant accomplishment from our team.
Can you talk about your ongoing partnership and collaboration efforts to maybe leverage some of these unique capabilities more? What are the main priorities on that front for 2025?
Yeah. So as I mentioned, we continue to accelerate our AI platform and our model development. So in the partnerships we have today, particularly Almirall and AZ, for example, and Merck, we're deploying the de novo platform for difficult targets. We think that's the big value proposition. And I would say as we look to this year, we're giving guidance that we will sign at least one more large pharma platform deal, potentially more. But I'm very confident in saying that given where discussions are today and given the kind of validation we've been able to show for that platform, i.e., HIV, i.e., some of the work we've done on ion channels and this transmembrane target I mentioned before.
Okay. Then last question for me before I turn it back to Vamil. Obviously, there is a lot of interest in AI beyond biotech as a broader investment theme. And recently, there was a lot of volatility in the sector with the announcement of the Stargate project. Then this company out of China announced the DeepSeek model. And I think your stock has reacted at least to some of those events and reacted quite significantly. So my question is, do those events actually impact your industry? Is there a direct read-through that you see maybe now, maybe in the future, or does it impact it indirectly? And in that case, what is the mechanism there? And how do you manage investor expectations in this sort of reality?
Sure. Do you want to?
Yeah. I mean, I'll start with the Stargate side. I mean, we were obviously very encouraged to see that sort of investment committed into building out AI infrastructure across the U.S. and maintaining U.S. leadership in that field. And also appreciate the comments from Larry Ellison of Oracle at the press conference where he mentioned the potential of AI to really be deployed in healthcare because we're in full alignment on that front that there's immense opportunity to use these certain AI technologies, for example, in our case for drug design to improve patients' lives. And then on the DeepSeek side, as you mentioned, I mean, Zach and team have been intimately involved with the collaboration that we struck with AMD recently, which also involved a strategic investment.
I think that's an area where it looks similar to the roadmap that we're looking at there, which is how can you get more efficiency and more use out of your GPUs and chips in a more cost-effective way?
Yeah. We think that particularly the DeepSeek news is really terrific, honestly, because we're developing a strategy with AMD where we could get potentially better performance, but certainly lower cost per performance, and looking at some of the efficiency gains that DeepSeek achieved and using that as a roadmap gives us even greater commitment to find ways to make our process more efficiency and more efficient and reduce our overall cost for compute relative to the outputs we're getting.
Great. Let me turn it back to you.
Yeah. Maybe while we have a minute or so left, just maybe to wrap up, just laying out the catalysts as we should look over the next year, 18 months, and also just your current cash position and runway would be helpful.
Yeah, and just start with the runway. We haven't changed our guidance. We still have runway into early 2027. The catalysts we think are really exciting this year. We're entering the clinic for our lead program, ABS-101. We should have an interim data readout, as I mentioned, here in the second half. We're also giving guidance that we're going to have at least one new significant pharma partnership on the platform this year, potentially more. And then when we look at ABS-201, as I mentioned, we're in IND-enabling and we'll be releasing some more data as we go through IND-enabling this year. And we should be in the clinic by early next year. We're doing everything we can to pull that timeline in.
And I guess one thing I would just noticing the time I would mention is we've had great reaction from investors and analysts on the ABS-201 program. They're just starting to dig in. And I think every conversation we've had over the last three weeks has been, this is highly interesting. We're going to engage and do homework on this. It's not reflected in the price yet, but we think there's a significant upside there for us, for the company, and for investors in that program.
Yeah. Because we obviously had a lot of interest and excitement ourselves in that program, but we're wondering how the public reaction would be to it, and to be honest, it was even above our expectations, the positive reception we've gotten from the, I'd say, dozens of investors we've spoken to since unveiling the hair regrowth program just about seven weeks ago at this point, and one more thing I'd add on to the list Zach mentioned is as we continue to advance our programs like ABS-101, like ABS-301, there is the potential based on our business model to also see a potential asset transaction on one of those wholly owned programs this year. Not something we're particularly guided to per se, but there is that potential given the progress we've made on those.
Yeah. I mean, to Alex's point, we have active discussions with partners around ABS-101. That would be significant upside to the runway. And so we're looking forward to finding a partner there potentially this year.
Okay. Interesting. Well, congrats on all the progress. We'll be keeping track as we go through the year. Thanks so much for joining us.
Thank you.
Thanks for having us.