Hello, and welcome, everybody, to Recursion's Q2 2025 Earnings Call. My name is Chris Gibson, and I'm the Co-Founder and CEO of Recursion. And I'm excited to share with you today some of the latest updates on our company as we drive forward to decode biology. We've been talking for the last 9 months since the business combination with Exscientia about the Recursion OS 2.0. And I want to start there today and tell you a little bit about the way that we're bringing together the incredible components from both Exscientia and Recursion and building new components of the OS in order to drive forward our mission. At Recursion, we base everything off of proprietary fit-for-purpose data, whether it's data we generate in-house or data that we pull from partners. And we're not just generating data to help discover targets or to help translate programs or to help with clinical trials, we're building a true end-to-end capability from target discovery all the way through to clinical trial simulation. We're really, really excited about the way all of these pieces fit together and add to each other. And everything we do at Recursion is based on iterative cycles of learning, much of our work based on iterative cycles of dry lab predictions and wet lab validations. I want to talk about a few of the pieces of the Recursion OS that we really, really leaned into in the last quarter. And I'm going to start off with talking about Boltz-2. This was a really exciting partnership with both MIT and Nvidia, where we were able to help lead the field of protein folding and lead the field of protein ligand binding predictions with this work that we did with MIT. And we were able to actually open source this project. And…

Thanks, Chris. Great to be here today. So let's dive into this. Chris mentioned the suite of partnerships and partner discovery programs and internal programs that we are progressing. A couple of things to note. On the internal side, you can see there are 6 or so programs that are going through really, really important inflection points, both across oncology and rare diseases. What I'll do today is double- click a bit more on a couple of our more late-stage or later-stage oncology programs, CDK7, monotherapy dose escalation as well as the initiation of our expansion cohort/combination arm and RBM39. We'll share a little bit more around the biomarker enriched, the solid tumors, the patient populations, et cetera, and how we leverage our platform insights in order to hone in on where we go. On the partnership front, I get this question a lot. So I just wanted to step back for a second and share. Across our partnerships, there's 2 major areas of value creation. The first is really around what Chris mentioned in the beginning, proprietary fit-for-purpose data sets that we're co-developing with our partners. So an example of this is, of course, the phenomap, the first neuronal phenomap, IPSC- derived with Roche and Genentech. And the other area of value creation is around partner programs where we are designing using our AI modules on the chemistry side, very challenging first-in-class, best-in-class programs. And just recently, we achieved a fourth milestone in our Sanofi partnership. More to come on that. So just going to the next slide. I'm just going to take a second to do a quick snapshot on the overall programs that we have in our internal portfolio, and then I'll go a bit more into CDK7 and RBM39. So just as a quick reminder, CDK7,…

Terrific. Thanks, Najat. So we had a good quarter and ended with a strong cash balance as we go to the next slide, showing $533 million in cash at the end of the quarter. That was based on not only managing our expenses. So at the time of the merger, we made a commitment to our shareholders that we would not only drive a lot of the growth and the programs and the technology that Chris and Najat talked about, but also manage our expenses. And so you've seen us go from a pro forma burn in 2024 to an expected cash burn in 2026 that's 35% less. And that's really our commitment as a management team to making sure that we're doing this as efficiently as possible. We had some great cash inflows over the quarter. In addition to the Sanofi milestone payment, we also had a $29 million R&D tax credit. This is a U.K. tax credit. We will continue to receive this in the future, although it will be smaller as the legislation around it has changed. Our guidance has not changed, and we continue to project over $100 million in partnership inflows by the end of 2026 and managing our burn below $390 million in 2026, so next year. All of that comes together with an expected cash runway through the fourth quarter of 2027. That cash burn number that I gave you does not include any partner inflows or other financing or inflows that would come in. And with that, I will turn it back over to Chris.

Thanks, Ben. Yes, I just want to end by talking a little bit about how we're looking ahead at the future of Recursion. It's been an incredible last 9 months post the business combination with Exscientia. We really feel like we pulled together the best elements of both companies' platforms into the Recursion OS 2.0 as both myself and Najat talked about earlier. And going forward, I think you're going to begin to see us, while maintaining an extraordinarily high bar for quality, bringing unique biological insights identified with our multimodal maps across many different cell types. We're going to see us bring new ideas, new targets, new chemistry. We're going to use our MOA and target deconvolution systems, tools like Boltz-2, our QMMD systems, and even CRISPR screens to help prosecute those exciting targets. And then we're going to continue to deploy this ClinTech platform to help translate the models and the programs that we're developing at Recursion with real-world evidence into programs that can move towards the clinic. And again, we are focused on differentiated high-quality programs that are going to go where others can't. And we're excited for the Recursion 2.0 platform to start to show you some of those programs that are really bringing together all of the elements from target discovery, all the way through to ClinTech in the coming quarters and years. But over the next 18 months, we have a catalyst packed calendar. The second half of this year, looking really exciting, multiple readouts, including FAP and CDK7, as Najat spoke to earlier. In the first half of next year, we'll be talking about our RBM39 program with early safety and PK from the monotherapy trial. And then rolling into the second half of next year, we're going to be looking at both MALT1 and initiating our ENPP1 program, which we were able to bring in recently in -- from our JV with Rallybio. In addition to what you see here from our internal pipeline, we're going to be delivering across all of our partnerships with the potential for additional phenomap options, the potential for new project initiations and the potential for programs being optioned by our partners. So again, Recursion continuing to deliver across both our internal and partner pipeline while also building the future drug discovery platform that we think is going to help to improve the probability of success, the time, the cost, and the potential of the medicines that we're advancing. And with that, we're going to move over to the Q&A portion.

And I'm going to go to the first question, which comes from multiple parties, which is about our Boltz-2 project. So the question is, is Boltz-2 the initiative with a major partner on foundational protein structure modeling that I mentioned at JPM earlier this year? And the answer is yes. This is the partnership that we alluded to at JPMorgan. And one of the questions here is why open source versus keeping it internal? So we believe that discovering and developing medicines is really, really challenging. Biology is really complex. Chemistry is really complex. And there are places where we believe we have a very differentiated advantage, such as with our large-scale phenomics platform and our design platform. These are places where we're going to keep those tools internal. There are other places where we need to be on the forefront, but we believe there are many competitive partners or groups working in the space. And in those areas, rather than try to keep something internal that others have available to them, we actually think it best to help commoditize that particular technology. And that's exactly what we're doing with Boltz-2. So we're commoditizing our complement, making sure that everyone has access to the kinds of tools that many groups are using and then keeping proprietary those tools that we think nobody else really has. The second question is, are you still building proprietary models? And the answer is, absolutely. So we were leveraging the Boltz-2 models before they were public. We also have large-scale internal data sets, and one could imagine that we could take the same kind of architectures, the same kinds of models that have been built in Boltz-2 and training them across much larger proprietary data sets to give us an internal advantage. So the second question, I'm going to go to Najat. And the question is from Dennis at Jefferies. And Dennis asked for the CDK7 combo expansion cohort in ovarian cancer, what standard of care are you allowing in the trial? And remind us the level of efficacy they showed in terms of OR and PFS? And then, Najat, I'll come to the part 2 after you answer the first one.

Thanks, Chris. Thanks, Dennis, for the question. Great question. So the standard of care, as I mentioned during the presentation, it will be single agent chemo plus beva as well. The last that I've seen for that combination, the median PFS was about 6.7 months and then median OS was about 14 to 22 months. And look, for us, for the combination, we definitely want to see meaningful improvement to the standard of care. This is a patient population with very significant unmet need. And the team will look through in terms of what other points might be more critical as well, for instance, the proportion of patients that reach a certain scan by a certain period of time and so forth. So a lot of conversations ongoing there, but we definitely want to see meaningful improvement from the standard of care for PFS.

Thanks, Najat. You hit part 2 there. So I'll move on to the next question, which is Brendan from Cowen and Alec from BofA ask, you mentioned the multiomic profiling that's ongoing for REC-1245, that's our RBM39 program. Do you expect the data from this analysis will in part dictate which patients you enroll in future studies? And what data from this analysis would you be able to leverage when targeting or enrolling future patients? And finally, can you point to the differentiation of RBM39 compared to other CDK targeting assets?

Great. Lots of questions. Thank you, Brendan, and thank you, Alec. I'll start with the first couple of questions, which is the data from this analysis dictating -- the data from this analysis dictating the patients that we'll go into and then also future question. Look, as I mentioned during the presentation today, really instead of having -- I think the beauty of the mass cell biology, the phenomaps, the multiomic approach, and so forth is instead of having like a single screen in a certain area for a certain target, you saw the holistic nature of how you can see the target being important and interesting across different pathways. That was really important for us to understand that, look, for various forms of replication stress, which can be epigenetic, which can be other areas as well, and DNA repair vulnerabilities are both very important for RBM39 as a target. That was step one. And that's actually what helped us for our monotherapy dose escalation to select patients in those areas, right, as you saw in our press release this morning. The other thing I'll also say is, look, the monotherapy dose escalation is going to be important. We're going to see patients with certain biomarkers recruited and enrolled and so forth, and we'll make more of the honing in of where we go based on data that we received. But this is a great way of actually using some of this data, not just for a novel target discovery, but something I've said before, but also while you're in discovery to have a better hypothesis of which patients you might actually want to go forward with 100,000 patients plus, and the expansion is because it actually targets a broad -- has a potential, I should say, to target a broad set of tumor types that are genomically unstable.

Thanks, Najat.

And then the…

Go ahead.

I just wanted to make sure I answer that. The point of differentiation in RBM39 and CDK7. RBM39 is not a kinase, right? And a lot of the kinases, for instance, as I mentioned, CDK12 has always been, for a long time, an important oncogenic target, but the homology with CDK13 just makes it challenging to really get that selectivity that you're looking for. So for us, it was born out of that inspiration of selectivity for a target that's important for DDR modulation, but went beyond much more when we looked at the broader map. And trust me, the map I even showed you today just for DDR pathways, it's a big, beautiful map. It's much broader than that. So at some point, I'd love to be able to show you more and what we see there.

Thanks, Najat. Okay. Next question. Brendan from Cowen and Sean from Morgan Stanley asks, for the upcoming FAP data, where do you see the threshold for success in that readout that would give you confidence in the path forward? And given the high unmet need in FAP, do you think the magnitude of polyp production you've seen to date would support approval and uptake in this patient population if replicated in Phase III?

Thank you, Chris. And thank you, Brendan and Sean from Morgan Stanley for the question. Yes, look, for FAP, the standard of care -- well, there is no therapeutic that's been approved for FAP. So let me just back up by saying that. So Celecoxib and others are used off-label polyburden reduction about 20% to 30% or so forth. So that -- we are definitely looking for a meaningful improvement in the polyburden reduction and some of the initial data has been promising. However, what's going to be really important for us is to look at the data later on this year, where we will have a broader patient population. And the second question around support for approval and uptake, following the data that we see later this year, of course, it's going to be important to have conversations with regulators. Once we do, happy to follow-up and share more in terms of what's going to take from an approval perspective.

Thanks, Najat. And next, we have partnership questions coming from Gil at Needham and Sean at Morgan Stanley. Najat, I'm going to send the first one over to you, which is, for the $7 million milestone achieved under the Sanofi collaboration, one of the latest in many milestones we've earned from that collaboration. Can you go into more detail as to what exactly was achieved to merit this milestone?

Great. So the programs that we have, and again, up to 15 programs as part of this partnership. I can't disclose exactly, of course, the target. But I can say that this was a challenging target in the immunology space. And what we do see is the milestone is focused on lead series, right, actually being able to successfully accomplish that. Next upcoming milestones would be development candidate. I think the point that's important to note is, look, these are all very, very challenging first-in-class, best-in-class targets and to design them is hard. It's not how you do it traditionally. And the fact that we've been able to get 4 out of 4 so far, knock on wood, somewhere, I think, is an important testament to how new approaches can help us and augment what we could do before. But more to come over the next 12 to 15 months.

I think this is one of the interesting things about the tech bio space, Najat and Dennis -- or I should say Gil and Sean, is that a lot of the companies in this space that are partnering with large pharma are working on some of the very hardest targets that were not amenable to more traditional approaches. So progress by us and others on these milestones is pretty exciting. Ben, I'm going to turn it over to you now. What visibility, if any, do you have on the potential $100 million in milestones by 2026? Are any assumed in the cash runway calculations? And again, this comes from Gil at Needham and Sean at Morgan Stanley.

Sure. Thanks, Gil and Sean. So in a way, we have a lot of visibility in the sense of that guidance was only based on existing partnerships and existing programs in those partnerships. Now of course, we don't have certainty that those milestones will be accomplished. And so what we do is we actually look at all of the programs that we know and we probability weight them. And so this is a probability weighted number, not the full amount. If we were to take the absolute number, it would be higher than this. And we don't include any potential new business development or additional expansion on programs that are not yet identified. So those are 2 areas where we could grow potential milestones in the future, but this is our best estimate that we felt safe in given the existing business.

Thank you, Ben. And next, we're going to go to Dennis from Jefferies and Mani from Leerink, who are both asking questions about our cash runway and how we get to our guidance of Q4 2027 cash outlook.

Sure, absolutely. So a couple of important notes here. One, it's really important to always focus on the cash flows when you're thinking about cash runway. So if you look at our P&L statement, our operating expenses or our net income actually include a lot of noncash expenses in it. So it's really important to go to that cash flow statement and look down at what is flowing through there. Secondly, all of our guidance that we gave, the $450 million this year, the $390 million next year is cash-based operating expense and CapEx, not including any partner inflows or new business development or financing. And so what we do is we then look, what are all the scenarios that could take us forward and get us to 2027? And actually, what we found is, there are many different ways that we get to the fourth quarter 2027. What we felt comfortable with is even just looking at our existing partnerships, like I was just talking about with the milestones, we felt comfortable that operating in a smart way that we are right now and trying to be as efficient as possible with our expenses, trying to really execute on our existing partnerships and following the same sort of strategy that we have on other cash inflows, including financing, we felt very comfortable we can get to the fourth quarter '27. And so we will continue to move forward. And as time goes forward, we'll look to optimize as best we can around those different variables.

Thanks, Ben. Final question here from John, who asks or says, we've seen companies like XAI making bold moves such as investing heavily in compute with millions of chips to accelerate their vision. Can you share how RXRX is similarly tripling down? What ambitious or transformative initiatives are you planning to reflect your next level of thinking? John, thanks. Great question, I think, to end it. First, I'd just say, if you looked at the State of AI Report that Nathan Benaich puts out, you'll actually see that Recursion is, I believe, one of the only biopharma companies that's actually listed as the top 20 private or public companies in the world, nongovernmental companies in terms of the scale of our compute. Now we're nowhere near Tesla, XAI, or any of those companies, but we really are driving one of the most sophisticated large-scale compute initiatives in the whole of biopharma. And I think that speaks to the kind of ambition that we have for how technology is going to drive this field forward. But in terms of other initiatives, I've spoken at prior events, including JPMorgan, about our belief in this field racing towards what we call a virtual cell. And this is essentially a computational model of cellular biology that would allow you to predict what would happen to a cell, many different kinds of cells, if you acted on them in any way, you add a protein, you add -- you change the effect of a gene or the expression level of a gene, you add a small molecule or multiple small molecules. And we believe that building a reliable and robust virtual cell is going to require not just having really good protein folding data, not just having really good atomistic and physics modeling and not…