Hi, everybody. My name is Chris Gibson, Co-Founder and CEO of Recursion, and I'm delighted to welcome you to our Earnings Call this morning. We're going to go ahead and get started. Perfect. So, of course, important to note that we're going to be providing forward-looking information today, so please understand all of these important caveats. So, I want to begin by just talking a little bit about Recursion's mission, which is to decode biology to radically improve lives. And unlike a traditional biotech, where learnings from a program typically work within that specific program, those learnings could improve a program, or the scientists from a given program might take some of those learnings onto their next program. At Recursion, we're trying to do something different. We're trying to build a learning system, a Recursion Operating System that learns from every program to make the next generation of programs better and better, and that requires some scale. And what you're going to see today is that we're taking decisive action to make sure that we can continue to both take our internal pipeline forward, our partnerships forward, and also that we can continue to run this critical experiment for the biopharma industry, and that is to build the first great TechBio company. I want to talk a little bit about our earliest version of the platform, Recursion 0.1. This was a platform built on top of phenomics and siRNA and repurposing. And today, you'll hear a bit about how some of those programs have done well like our FAP program with preliminary efficacy data and safety data we'll share soon, and also how some of those programs have not turned out the way we hoped, such as our CCM program. But building on the learnings of that first generation, we…

Thank you, Chris. Good morning. Good afternoon. Good evening, everyone. Thank you so much for joining our Q1 2025 earnings call. As Chris mentioned, over the next 40 minutes or so, I'll walkthrough some of the key pipeline updates, delivering on our commitment to sharpen our focus following the combination with Exscientia. I'll also highlight the programs we're advancing with the potential for greatest impact and also programs that we have thoughtfully chosen to discontinue. And in addition to that, I'll round it out. So, we go back to the next prior slide. Chris shared this slide. I just want to double down on a few more points. So first of all, three key points to consider. One is our pipeline really reflects the strategic application of Recursion OS and AI, where it matters the most. So, as I go through each of these programs, I'll talk about places where we have novel biological insight or areas where we're engineering and designing differentiated molecules as well as areas that we're driving precision-based development, a really key theme that we're doubling down on further. But every single asset you see on this page is done with one end in mind, which is programs that aim to create differentiated medicines that patients are waiting for. The second point, in terms of sharpening our focus, we're doubling down in these programs, both in oncology and complementing it with a focused effort in rare diseases. As Chris mentioned, we're advancing over five internally developed programs with first or best-in-class potential, each targeting unmet needs with a clear and efficient path to development and potential launch. And then the third point, look, as part of having portfolio, since we did the integration, the portfolio has grown, and we said that we would actually make disciplined…

Sure. Thank you, Najat. So, where we wanted to start with, when we're going through some of the financials is not only to talk about the pipeline prioritization that Najat just went through and Chris gave a very high-level overview at the beginning, but also talk about how we are trying to make data driven, disciplined decisions across the organization to really maximize our ability to reach all of those milestones that were on the previous slide. So, if you look at how we've been adjusting our operations, not only since the merger but even before, and trying to align that to be able to drive our cash runway as long as possible. What you can see is, we've really had a focus on adjusting our capacity over our capabilities. What I mean by that is our capabilities are the platform overall, what we can actually use out of that platform. The capacity would be more of how many can we use. And so, because we are a tech company, because we focus on automation, we actually have a great ability to adjust our capacity, based on the market conditions, based on the pipeline number we want to execute, while still being able to enable all of those same capabilities across the platform. And that's exactly what you'll see from us, both during the first quarter, but also through the rest of the year. Couple different points that we wanted to hit on. One, we ended the quarter with $509 million in cash. We will talk a bit about cash burn, and this is something that's really important because it's a little confusing, to anyone outside of the Company looking at our financial statements to try and understand what are you actually spending operationally to execute on all of those…

Thanks, Ben. I want to talk a little bit about Recursion 2.0 and the experiment that we're here to run at Recursion. You've heard from Ben and Najat today, and on behalf of them and the entire team, we thank you for your attention. I just want to share with all of you that we believe that Recursion will continue to lead the TechBio space, and we're going to do that through this sustainable continued growth plan that we shared today. We're going to remain committed to our internal pipeline, though it's going to be more focused than it has been in the past. We're going to continue to execute on our partnerships, and we believe there are substantial milestones that we have the potential to earn over the coming quarters and years. We're going to continue to increase our focus on leveraging AI, not only in drug discovery, but all the way through development with some really exciting build happening in clinical development that we'll share more on soon. As Ben just shared, we're going to continue increasing the efficiency of Recursion while also never stopping our investment in the Recursion Operating System, because ultimately, it's that operating system, that learning system that we believe will give Recursion an advantage in the coming years. And so, with that, huge thanks to all of you for your attention. I think we're going to go ahead and turn it over to Q&A, and I will start.

Looks like Eric Joseph at JPMorgan has asked. Given your stated runway to mid-2027, what burn rate do you anticipate exiting '25 or entering '26 with? From where would you expect incremental efficiencies still to be derived, and do you plan to raise capital? For that, I'll turn it over to you, Ben.

Sure, of course. So, we haven't given specific guidance on the runway, but you can imagine if our budget for this year is $450 million or less, we're targeting a runway of less than that. And so, we will give additional detail as the year goes forward. I think we're also going to continue to look for different efficiencies across the organization, and let me give you a couple of examples. We've been able to, for example, drive better contracts with our partners. We're a more skilled organization. We've been able to integrate different parts of the business where we had high cost on one side previously and low cost on other, eventually reaching lower cost overall, And we’ll continue to drive into every aspect that we can extend that runway without impacting our ability to execute and deliver on our pipeline programs both internally and with our partnerships. So, we’ll keep driving on that. As far as raising capital, as you know, we and no one else get guidance on financing, but we plan to just really continue our previous business practices. We'll continue watching the market. We do have an ATM facility, which we have used moderately in the past. And so, we'll continue to use our current business practices going forward.

Thank you so much, Ben. Next, we got James and Joe asking a question on partnerships. When can we see an option in on a molecule candidate from one of your four main partnerships, and any further insights on new levers in the OS for accelerating partnership programs to commercialization? I'll take the first part of that. So, we've already had four programs optioned, in our collaboration with Sanofi, another program optioned in our collaboration with First Genentech, and we believe that those programs and many others coming behind them have the potential, not only to get those early options, but perhaps to have the potential to go to later stage options, where they would might move into our partners' pipelines. And obviously, the economics are significantly higher at those stages. So, we're continuing to do that work, and we think a lot of promising progress so far. For the second part, maybe I'll turn it over to you, Najat. Any further insights on new levers in the OS for accelerating partnership programs to commercialization?

Yes. I mean, I'll mention maybe three. One on biology. We've talked a lot about the phenomics work that Recursion is doing now adding transcriptomic. I think the clinical genomic data that we have, it really helps you make the stack multimodal, but not just to understand holistically the biology, but also very early on start to better understand what the patient population may be. Really creating a more differentiated TTP upfront and earlier on, that's one area. The second, on the chemistry and the design module. You saw some of the examples I showed for internal. It's very, very similar to what we're doing with partners, in terms of can we try to model in or model out aspects that we know are challenging with molecular dynamics, QN. You'll see much more coming up in that space. And then also being able to model and predict some of the admin aspects that makes a drug more drug like earlier on. And the third is more in development. Chris touched on this a little bit. As we partner, whether it's not just on a discovery program perspective, but also on potential partnership on an asset perspective, et cetera. We're also going to leverage some of our ClinTech capabilities. Again, using multimodal data to really precisely understand the patient population that we just target that would have the highest signal to noise and then also will be more rapid, in terms of how we can do it.

Thanks, Najat. Next up, we've got Vikram from Morgan Stanley, who's asking a question on the pipeline. Your pipeline prioritization leans heavily towards oncology. Do you generally see a pivot away from rare disease for your pipeline and platform? And if so, which aspects of the recursion operating system, underlying approach do you think make onco stronger fit, in addition to rare disease? I think at a high level, we believe that both oncology and rare disease are fantastic areas for us to deploy our platform. In both of those areas, we have some genetic markers that often give us sort of an anchor point of biology from which to work from. And so, we'll continue to follow the data, and I can imagine us continuing to drive both rare disease and oncology programs forward. The data is going to be ultimately what drives where what the balance of the portfolio looks like, but I do not see us abandoning either oncology or rare disease in the near-term. Next up, we'll go to Dennis from Jefferies, Gil from Needham, Alec from Bank of America, Brandon from Cowen, and many other folks, who are asking questions around the FAQ readout. And I'm going to read these off one by one because we got a whole bunch here, and I'll have Najat answer them. So, the very first one. Talk about the FAP data shared at DDW, and how is that differentiated from other programs that we may have seen in this space?

Yes, happy to do that. So, when we look at the FAP data, which I just shared efficacy valuable about NF6 patients, median polyp burden reduction in the 40s, 43%, but again, early data, right? And I also talked a little bit about the safety, where most of what you're seeing there is on target classified from MEK1/2 inhibitors. The two other programs that exist, the celecoxib, as I mentioned, used off-label, and then also another program focused on [rapamycin] and [capaslida rapamycin], which is in a competitor's pipeline. Both so far have shown polyp reductions 20% to 30%. So just from the primary endpoint that we're looking at. The second piece I think that's also important to note is the change in the Spiegelman scoring. And also, we are encouraged by the congruence that we see polyp burden, polyp count, and then also the Spiegelman stage. Again, early data, but some of the reductions that we're seeing so far is pretty encouraging. I see there's another question in terms of the non-responders, and just take that and couple it. So, I'm talking through the data more holistically. Non-responder with a six-fold increase in polyps. What do we see in natural history? So, in natural history, the polyp burden is increasing for these patients. But there are prior studies, and one of our competitors studies where about 40% to 50% of patients are non-responders in these studies, right? Non-responders from a polyp burden or from a polyp count perspective. And recent data has shown that even in that 40% of non-responders of polyp increase, there is anywhere from 1x to 2x to 6x increase in polyp burden. So, for our one non-responder, as I mentioned earlier, we're going to do -- we're doing a lot of work to better understand the reason for that and then the work will continue. As we have a larger N, these numbers will evolve. And that's going to be important as we look for more mature data later on this year.

The next question on FAP was, will we continue to dose higher than 4 milligrams?

What we want to do first is, we're encouraged by the reduction that we're seeing, 30% to 80% polyp burden reduction is pretty significant. We want to look at some of the data later this year, [indiscernible]. And then, next steps would be either if we need to dose higher, but then also discussions with the regulatory agencies and the potential path forward. So first, we want to complete the 4 milligram cohort really better understand data, and then take next steps from there.

And then the last two, where do you see the bar for success in FAP? First, in terms of FDA approval, but also as it relates to broader uptake among patients?

Yes, I mean, that's a great question. The bar for success for FAP, what we see with some of the off-label agents that are used anywhere from 20% to 30%, there's nothing approved. So clearly there's a huge unmet need for these patients, because if not, they're doing multiple surgeries throughout their lifetime. There is another agent that's in just starting Phase 3. You can see some of the data, our polyp burden reduction to-date is encouraging and higher, but much more to do in terms of learning about the data.

And any next steps for the program?

Yes. So, as I mentioned, more patients on the 4 milligram by the end of this year, and then conversations with the FDA on the path forward. So far, endpoints have been a composite endpoint for FAP. And one of the components, as I mentioned earlier, is actually the inclusion of Spiegelman scores. So, we're watching all of those different aspects and more to come later this year.

All right. Next up, we have Alec from BFA, who's asking. Remind us how CCM, NF2, and C. diff, which are three of the programs that we just continued, were initially discovered or developed, and how the refined pipeline strategy may be better reflects the current capabilities of the Recursion platform? I'll take this one. So, look, CCM, NF2, and FAP were all products of our Recursion 0.1 platform, where we were using RNAi, and tools, to identify repurposing candidates. And it's exciting to see the FAP program showing us some preliminary efficacy. Our C. diff program came out of our Recursion 1.0 platform, where we started to explore new chemical entities, and we see no reason today why the science doesn't continue to hold on that program. That decision today was really based on looking at the commercial landscape and the unmet need and making sure we prioritize our investment. Obviously, and are too low to draw any conclusions, but we designed Recursion as a learning platform, where each generation of the platform has a higher probability of identifying and uncovering medicines that we think will have an improved probability of success. And again, the end on Recursion 0.1 will be too low versus Recursion 1.0. But as we continue to learn and iterate on this platform, I'm confident that on average, the probability of success of our programs is likely to go up. That's what we're here to do.

And Chris, if I could just add one point coming in less than a year ago, just looking at the overall programs, just going back to our go forward portfolio strategy. One of the things you'll see I mentioned is really, being very thoughtful, in terms of how the molecules are designed, and we can do that in house today, and even more so, doubling down on that post the integration with Exscientia. CCM and NF2 and FAPs were all in licensed/repurposed program. So, that's number one from a design perspective, from a chemistry, biology perspective, Chris mentioned as well. And then, the third is also the development strategy, right? I think for a company like us having rapid learnings, rapid go no go, rapid and clear, with endpoints, that have some precedence was also going to be important for us. So, those are some of the other aspects that we're incorporating.

That's the kind of scaled learning that we're going to get with a with a scaled portfolio. And in some way related, Gil from Needham is asking. If we contextualize the use of AI in clinical development, like for study design and maybe how that's relevant for programs like RBM39. I know this has been a big area of focus over the last year.

Yes. Absolutely. So, yes, let's take whether it's CDK7, RBM, or even MALT1. So, I'll just take CDK7 as an example. There are other programs in the competitor pipeline. Which indications do you go after? Solid tumors is very broad, same with RBM, same thing with others. How do you enrich the what, how do you enrich the biomarker for the patient population? How do you ensure that the patient populations you're going into have certain overexpression or under expression that is predictive of greater signal to noise? I can speak more about that, but that's one of the things that we're doing, leveraging clinical genomic data like Tempus, but then also a lot of predictive algorithms that we are developing from our cell line work that we're doing internally as well frequently. So, much more to say here. The last thing I want to say, sometimes enrollment and recruitment gets forgotten. And also, sometimes, real world data to contextualize any open-label study also gets forgotten. Both of those are really important, not just for regulatory purposes, but also for internal go-no-go decision making. How much conviction do we have in the signal to noise? So, a lot of those approaches really scaling up in the last few years or so.

Perfect. Next up, we have Melissa who asks. What criteria were used to prioritize certain programs over others, and how does this focus advance or align with Recursion's long-term strategic objectives? Please.

Yes. I mean, in terms of the criteria that we use, is very much what, is best-in-class in industry. So, first and foremost, it always starts with what is the potential value of the drug. Patient population, unmet need, scientific data starting from preclinical, clinical data, competitive differentiation, et cetera. Also, in terms of the development plan, is there a feasible development plan? And then we look at risk, which is the other side of the coin. So, for each program, look, if I can coin it in one sentence, taking all of those components and we've done our computational approach bottom up, so we're not being objective or we're being objective in terms of the decision-making comes down to, do you believe this can be a differentiated medicine and is it serving an unmet need that will exist by the time you are going to be in the market? That's the most important. That bar has to be very, very high for us.

And the final question, Brendan from Cowen asks. Do you expect any meaningful impact to your internal partnership strategy in light of the FDA's updated animal testing guidance? And I'll take that one to end us. Look, Recursion was built for an evolving regulatory framework like the one we're seeing from the FDA. And we'll continue to monitor for additional updates as the FDA explores all the ways that AI and other tools can be used. But from our discovery platform to our predictive admin platform to even our in vivo platform, we are generating large-scale data sets. We're building foundation models that are allowing us to move from a test at scale in the lab sort of regime for preclinical studies to a predict and validate regime for preclinical studies. And so, I think Recursion is not just positioned to take advantage of these regulatory updates, but actually positioned to lead in this space going forward.

So, with that, we appreciate everybody's deep attention. Thanks to everyone for joining. And we look forward to seeing you all out on the street. Thank you so much, everybody. Bye-bye.