Earnings call transcript: Recursion Pharmaceuticals Q2 2025 sees revenue beat

Recursion Pharmaceuticals reported its second-quarter 2025 earnings with revenue significantly surpassing expectations, while earnings per share (EPS) fell short. The company posted an actual EPS of -$0.41, missing the forecast of -$0.35, resulting in a 17.14% negative surprise. Revenue reached $19.22 million, exceeding the forecast of $15.37 million, marking a 25.05% surprise. With a market capitalization of $2.5 billion and strong revenue growth of 29.3% over the last twelve months, the company continues to expand despite profitability challenges. In pre-market trading, the stock rose by 2.41%, reflecting investor optimism despite the EPS miss.

Key Takeaways

• Recursion’s revenue outperformed expectations by over 25%.
• EPS fell short of forecasts, with a negative surprise of 17.14%.
• Pre-market trading showed a 2.41% increase in stock price.
• The company reduced its projected cash burn by 35%.
• New product launches and strategic partnerships are in focus.

Company Performance

Recursion Pharmaceuticals demonstrated robust revenue growth in Q2 2025, driven by advancements in its AI-driven drug discovery platform. According to InvestingPro data, the company maintains a "Fair" overall financial health score, with particularly strong momentum and relative value metrics. The company’s focus on oncology and rare diseases, along with strategic partnerships, has positioned it well in the competitive biotech landscape. Compared to previous quarters, the revenue beat highlights a positive trajectory, though the EPS miss indicates ongoing financial challenges.

Financial Highlights

• Revenue: $19.22 million, surpassing the $15.37 million forecast.
• Earnings per share: -$0.41, below the -$0.35 forecast.
• Cash balance: $533 million, with a reduced cash burn projection.
• R&D tax credit: $29 million received.

Earnings vs. Forecast

Recursion’s revenue for Q2 2025 exceeded forecasts by 25.05%, a substantial beat that underscores the effectiveness of its strategic initiatives. However, the EPS of -$0.41, missing the forecast by 17.14%, points to ongoing operational costs and investment in growth.

Market Reaction

In pre-market trading, Recursion’s stock rose by 2.41%, reflecting positive investor sentiment toward the revenue beat. Trading at $5.75, the stock shows a price-to-book ratio of 2.7x and demonstrates strong return momentum over the past three months. The stock’s movement within its 52-week range suggests cautious optimism, as it remains below its high of $12.36 but well above its low of $3.79. According to InvestingPro’s Fair Value analysis, the stock currently appears fairly valued relative to its fundamentals.

Outlook & Guidance

Recursion forecasts a catalyst-rich 18-month period with significant data readouts expected in late 2024 and early 2025. The company’s cash runway is projected through Q4 2027, supported by anticipated partnership inflows exceeding $100 million by 2026. Future EPS forecasts suggest continued improvement, with projections of -$0.3 for Q3 2025 and -$0.24 for Q4 2025.

Executive Commentary

CEO Chris Gibson emphasized the company’s comprehensive capabilities, stating, "We’re building a true end-to-end capability from target discovery all the way through to clinical trial simulation." He also highlighted the complexity of the fields Recursion operates in: "Biology is really complex. Chemistry is really complex."

Risks and Challenges

• Continued EPS shortfalls could affect investor confidence.
• High operational costs may impact profitability.
• Dependency on partnerships for future inflows could pose risks.
• Competitive pressures in the biotech sector require constant innovation.
• Regulatory challenges in drug approval processes.

Q&A

During the earnings call, analysts inquired about the open-source strategy for the BoltSU tool and patient targeting for the RBM 39 program. The company also addressed partnership milestones and detailed its cash runway and financial projections, reassuring stakeholders of its strategic direction.

Full transcript - Recursion Pharmaceuticals Inc (RXRX) Q2 2025:

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Recursion’s q two twenty twenty five earnings call. My name is Chris Gibson, and I’m the cofounder 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 nine months since the business combination with Accenture about the Recursion OS two point o, and I wanna start there today and tell you a little bit about the way that we’re bringing together the incredible, components from both Accenture 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 wanna talk about a few of the pieces of the Recursion OS that we really, really leaned into in the last quarter.

And I’m gonna start off with talking about BoltSU. 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 today, there have been almost 200,000 downloads and almost 50,000 unique users. And what I think is most exciting, what’s gotten the most traction about this work is that we were able to actually make binding predictions that are approaching the level of, the level of efficiency and the level of efficacy of free energy perturbation calculations, but we’re able to do this with about with about a thousand fold less compute. That is really, really, really exciting.

It means that a lot of the sort of real bespoke work that was done with physics based computing could actually be done in a screening format. And while there’s more work to do in this space by us and many others, we are very excited about the way this tool and tools like this are gonna be able to drive the field forward. And what’s more, we’ve already built this technology into the Recursion OS and even improvements on this technology into the Recursion OS. Another area we’ve been talking about for the last year has been our ClinTech platform, and this is something that we are now deploying against every single one of our programs at Recursion. There’s multiple com components to this.

The first is our causal AI applied to human genomics, and this is really exciting. We’re taking patient data that we get from Helix and Tempus. We’re combining that with our perturbation biology data and algorithms from Recursion to help to connect our platform to patients. And this is enable enabling us to identify targets, to stratify patients, and even to do indication expansion. We’ve also started to design and simulate our clinical trials at Recursion using in house, software that we’ve been building.

This is allowing us to potentially, improve the the optimal dose for thirty percent more patients. This is really, really exciting, and, we are now deploying this against our programs at Recursion. And third, we’re now using our AI not just to identify, patients, not just to design our clinical trials, but actually to recruit and execute. The operation side of our clinical trials is really, really important as well. And with the new software that we’ve built and the partnerships we’ve built in this space, we now have the potential for 50% faster enrollment projections at high quality sites.

And this means we can activate trials up to two months faster. Again, this is the early days of our ClinTech platform, but what I’m most excited about is that we’re already deploying these tools against the programs in our pipeline, and we’ll be deploying these against new programs in our pipeline soon. And Najat’s gonna be able to tell you more about that in a few minutes. We continue to advance a pipeline of both internal programs in oncology and rare disease, as well as a suite of R and D collaborations and programs with our partners of Roche, Sanofi, Bayer, and Merck KGA. And we’re really, really excited about all of these programs today.

But what I think is most exciting isn’t any one of the programs. It’s the platform we’re building and these leading indicators where we’re demonstrating that we can bring medicines to the clinic faster and at lower cost. And ultimately, these leading indicators are things that we believe over time are gonna continue to improve, and we’re gonna be able to continue to raise a high bar of quality on our programs and drive them forward at real scale. And to tell you more about the way we’re building momentum, let me turn it over to our chief r and d and chief commercial officer, Najat Khan. Najat?

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: Thanks, Chris. Great to be here today. So let’s dive into this. Chris mentioned, you know, 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 know, you can see there’s six 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, CDK seven, monotherapy dose escalation, as well as the initiation of our expansion cohort slash combination arm, and r b m 39. You know, we’ll share a little bit more around the biomarker enriched, the solid tumors, the patient populations, etcetera, and how we leverage our platform insights in order to hone in on where we go. On the partnership front, you know, I get this question a lot, so I just wanted to step back for a second and share. Across our partnerships, there’s two major areas of value creation.

The first is really around what Chris mentioned in the beginning, proprietary fit for purpose datasets that we’re codeveloping with our partners. So an example of this is, of course, the PhenoMap, the first neuronal PhenoMap iPSC derived with Roche 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 gonna 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 CDK seven and RBM 39. So just as a quick reminder, CDK seven, really important target. The focus really is leveraging leveraging our our AI powered design module in our Recursion OS platform to optimize the therapeutic index. This is a target that has been tried by others before, so that’s the area of focus.

We should have more monotherapy dose escalation data by the end of this year, and as I mentioned, combination initiated. R 39, this is an example actually identified using our phenomaps where we identified a new MOA with synthetic lethal targeting opportunities in genomically unstable cancers. More on that. First half of twenty twenty six, we anticipate some initial data from our monotherapy dose escalation. You heard a little bit about the MEC one two in our in our FAP program.

So I just wanna highlight. This is again another phenotypic insight where we actually derive the fact that there’s a connection, an important relationship in an unbiased fashion between MET one two and the and the relationship with MAP kinase pathway, signaling pathway, and APC and WIN signaling pathway, which disease this is for FAP. So, again, we should expect more data beyond the initial cut we shared earlier this year, 2025, so end of this year. And MALD one, this is another program where now we’re using and leveraging our AI powered chemistry design portion of the Recursion OS platform, again, to lower the liability that’s associated with UGT one a one inhibition. That’s also in monotherapy dose escalation.

And to round it out, we also have a couple of preclinical programs here that are going through important inflection points in the development candidate slash IND enabling phase. But, you know, a lot of these programs, and we talked about this before, were really focused on the earlier versions of the Recursion OS platform. And as we iterate and learn and add more components to our Recursion OS platforms, we expect the next wave of programs to be even more high potential and and and potential to do it in a more efficient way. But I wanted to get take you a little bit under the hood of what’s actually in the Recursion, OS, especially the two point o platform following the integration with, Excientia. So, if you just look to the left hand side, we first start with the AI powered biological insights.

This is where we are actually deriving novel targets. This is from multiomic data, whether it be phenomic, transcriptomics, etcetera, connecting that early on with the patient. This is the ML based patient connectivity data layer that’s really important to the datasets such as from Tempus, Helix, and others, ensuring that we can actually take these biological insights and deconvulate the MOA, and very early on do a screening approach, around triaging what are some of the binding affinities early on. So this is where approaches such as BOLTS two that Chris mentioned earlier is already being incorporated into our workflow. In addition to that, we’re also developing proprietary algorithms in house.

So as soon as we put this on a slide, I have to say it gets outdated because there’s so much rapid iteration and work that’s happening. In the middle, AI enabled precision design, this is where we’re designing our molecules, optimizing both for novel scaffolds. This is where we use generative AI approaches. And also active learning in order to optimize drug like properties. This also includes using QMMD approaches, which is a three d protein and atomistic models.

And one important point here is the wet and dry lab integration that we have. So this is where aspects are on automated chemistry, automated biology, and automated admit becomes incredibly important so we can design out certain elements earlier, faster to ensure that we have better molecules out of discovery. And last but certainly not the least, and one that’s close to my heart, is ensuring that we do this also in clinical development. Chris touched on this in terms of some of the areas that we’re building out, and you’ll see some of the examples we’re using in our current programs already around causal inference on patient stratification and also smarter trials and faster improvement. So as I go through each of the programs, I will actually highlight which area of the Recursion OS module and platform we are integrating and actually in, highlighted insights for our program.

So let’s start with RBM, 39. So in this program, as I mentioned earlier, the focus was really around, leveraging our maps of biology. So just as a reminder for everyone, starting on the left hand side, we start with these really large maps of biology, whole genome CRISPR knockouts, and then we profile compounds that are proprietary to us in order to get better understanding of the initial chemical substrates that might actually modulate the biological insight that we have identified. So the example here is how we identified r b m 39, which pheno to phenomimics, CDK 12. So CDK 12, and this is to the panel to your right hand side, has been an attractive target in oncology, right, for its role in DDR modulation.

But generally has been has suffered from challenges in selectivity because of how homologous CDK 13 is. Leveraging our phenomaps, we actually identified that r b m 39 is similar, phenotypically, at least, to CDK 12. Well, we could and not to CDK 13. So that was the first insight. The second insight was the fact that we were actually developed we’re able to develop molecular glues and degraders for RBM 39, which you’ll see in a moment, that are also phenotypically mimics CDK 12.

So this was our first inkling that this could potentially RBM thirty nine inhibitors or degraders could potentially provide a druggable potential analog. And then I wanna say something else that doesn’t get talked about enough, which is if you look at the middle panel, we also look not just for CDK 12 or CDK 13, but we look more expansively across the map to see is there well established dependencies that are known of already biologically that are also being validated. An example here is a CDK 12 and cyclin e cyclin k, similar phenomic readout. But this is just a small detail in the entirety of the map that we look at. And if you go to the next slide, this is another expansion of that same map.

And what we see here that’s actually quite intriguing is in the center in the black box is what I was referring to in the earlier slide, which is the r b m 39 and the degrader itself and some some of the associations that we see with CDK 12, CDK 13, and so forth. But you look broader and you also see associations mechanistically in DNA damage repair, epigenetic regulation, cell cycle control, and transcription. And this, when you look at it from an MOA perspective, which I’ll turn on next, actually intuitively makes sense. RBM 39, if you go to the next slide, is focused is is important for splicing fidelity. Degradation of RBM 39 leads to splicing defects.

Now if you combine that with, tumors that are already already genomically unstable, whether it’s because of DNA repair pathway vulnerabilities or transcriptional regulation, then that can actually increase the amount of instability leading to potential apoptosis and cell death. So just want to share with you how an insight is then, triangulated with understanding of mechanism of action. But that’s not enough. So if we go to the next slide, in addition to that, we also looked at in vitro and in vivo work. Starting with look.

When we look at the broader patient population, just given the connectivity across the maps that you note that I noted, for replication stress, tumors that suffer from epigenetic dysregulation, cell cycle alterations, or oncogenic drivers are relevant as well as those tumors that have DDR effects. So so both of those. And that spans several solid tumors from colorectal, breasts, etcetera, along with some pretty clinically actionable alterations that we’ll be studying and looking into more such as MSI high, MYC amplification, etcetera. But we wanted to look at the in silico understanding and triangulate that with and in vivo work. So if you look at the in vitro cell lines, you clearly see that RBM 39 degraders, so Rec one two four five in this case, there is greater sensitivity in cell lines that have higher replication stress versus cell lines that don’t have higher replication stress.

So this was a good early signal for us. And if you go to the next slide, we see a similar trend hold in in vivo as well, where you see, a reduction in tumor volume across different tumor types that actually have high replication stress signatures. So this helps us to two things. Number one, better understand the importance of r b m thirty nine as a first in class target in solid tumors. Second, also give a give us a better sense in terms of which, patient population, tumor segments, etcetera, might be relevant for us to target.

And if you go to the next slide, we went a step further than that. We also wanted to look at the totality of it. So you have the recursion, OS inside, definitely the preclinical data that I mentioned, but also looking into mechanistic validation, in the middle panel. And, you know, we see two things here. First, the d max is approaching almost a 100% in r b m 39 degradation with quite potent, d 50, numbers as well.

So rapid and potent r b m 39 degradation. Now we wanted to go even a step further, you go to the next slide, which is, if you go on slide before, please. Okay. That’s okay. If you go to the next slide.

So this has actually helped us inform what our dose escalation and our combination arm is is is going to be. So for RBM, 39, monotherapy dose escalation, but in terms of the cancers that we’re looking after or going after is endometrial, ovarian, etcetera, with cancers with high genomic instability. And we will also be focusing on some of these biomarker enriched populations such as MSI high. So, again, first patient dose, patients are enrolling in this study. We should have early safety and PK data from on this monotherapy trial in the 2026.

Now we’ll go to CDK seven, which is our next program. Here, we actually leverage two components of our Recursion OS platform. First, focused on designing a molecule that can really optimize for the therapeutic index. Second, leveraging some of our clin tech approaches in order to hone in on which patient population and which combination arm we will hone in on. So let’s go to the next slide.

Okay. So just a quick reminder in terms of how the molecule was designed. A couple of things to note here. The CDK seven is has been an important target for some time as well. It is a master regulator, both cell cycle progression as well as transcription.

But one of the challenges that other compounds have seen so far is, you know, challenges with permeability, efflux, and not rapid absorption. So we wanna change that around. We use generative AI models to actually design new scaffolds. And I think this part is really important, which is leveraging active learning and experimental admit data to quickly learn, iterate, and optimize, the molecules to reduce the components that we wanted to design out, such as ensure that there’s high permeability, rapid absorption, and low efflux. And, similar to RBM, 39 degrader, which was done in a very short amount of time, eighteen months from start to IND enabling, with about 200 compounds or so synthesized.

In this case, you also see about a 136 novel compounds synthesized and getting to candidate ID in less than twelve months. Now one of the components for designing high permeability rapid absorption and low efflux was to ensure that we would have sufficient exposures, and you see that on the right hand side panel. Both ten milligram QD, twenty milligram QD clearing the I c 80 line. And when we actually look at versus some of the peers, it’s an order of magnitude higher than the exposure that they’re seeing. So as of November slash December 2024 data cutoff, the compound showed one confirmed PR in ovarian cancer as well as multiple cases of stable disease.

So far with a favorable safety profile and no MTD reached. If we go to the next slide, what we have done since then is really design which, combination arm we will focus on. So the one that we’re going to focus on, that we have announced today is second line plus platinum resistant ovarian cancer. How do we get to that? So first, we looked at preclinical data.

So cell panels in vivo, you see an ovarian. Both are of them are sensitive to CDK 17, and that there are multiple panels that were done. And then in addition to that, as part of our ClinCheck approach, we also use causal inference using some of this multi omic and clinical data. And this was very important to better understand the cause and effect factors here. And what we see is that a higher expression of ovarian cancer based on this data is associated with lower overall or worse overall survival.

This was based on about thirty two thousand patient records. So this gave the totality of the evidence from preclinical and also some of what we see in our early clinical data so far, combined with some of this causal inference work, gave us more confidence in terms of the first indication that we would go after. Were there significant unmet need in second line plus platinum resistant ovarian cancer. So if you go to the next slide, site selection and activation, is in progress right now. The for the combination arm, the standard of care includes single agent chemotherapy, beva plus chemotherapy, and in some cases, PARP inhibitors.

In addition to that, the monotherapy arm is ongoing, and we anticipate more data from that, later on this year. If you go to the next slide. So I’ll also share a bit more about some of our partnered discovery programs. Next slide, please. Great.

So if you look at Sanofi as an example, just mentioned that we have our fourth program milestone achieved in the last eighteen months. I just wanna take a moment to say that some of these programs, both in immunology and oncology, first in class, best in class, some of the milestones that we’re going through include important milestones in discovery, series, development candidate, and so forth. And we have several programs advancing to those milestones, including development candidate in the next twelve to fifteen months. This effort leverages what you saw in the Recursion OS platform, a lot of the AI powered chemistry, design module. And in terms of Roche, you know, five phenomaps built to date.

So you saw an example for RBM 39, how we use some of our phenomaps. These are specific in for the neuroscience and GI space. I mean, for the neuroscience one that we delivered last year, over a trillion iPSC derived cells use, whole genome knockout, and also other perturbations in terms of overexpression. So you’re really getting a very holistic understanding of, biological pathways and a lot of work in progress there in order to take those insights and translate them into novel programs. So more to come on that.

And then also on the GI, ONC indication over four maps already, developed there and already one program, that has been optioned and more work happening. And I think one point to note here, it’s it’s a real pleasure and honor to partner with partners such as Roche, Sanofi, Bayer, and Merck KGA. Where we bring the best of our capabilities, you know, the Recursion OS, the Recursion, you know, drunk hunter expertise, and the platform tech expertise along with the deep biology expertise and chemistry expertise in Genentech, Sanofi, and others. And then when it comes to Bayer and Mercury GIs, similarly, you know, the second area of value creation that I mentioned earlier, which is challenging targets, developing molecules, for them using our chemistry platform, or actually highlighting and nominating novel or undruggable targets from our maps of biology. With the potential here, a lot of work ongoing for over a 100,000,000 in partnership milestones by the 2026.

So with that, I’m gonna hand it over to Ben Taylor, our CFO and president of UK, to tell us a little bit more about our financial update. Ben?

Ben Taylor, CFO and President of UK, Recursion Pharmaceuticals: Terrific. Thanks, Neja. 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 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 form a burn in 2024 to a 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 29,000,000 r and d tax credit. This is a UK 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 a 100,000,000 in partnership inflows by the 2026 and managing our burn below 390,000,000 in 2026, so next year. All of that comes together with an expected cash runway through the 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.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thanks, Ben. Yeah. I just wanna end by talking a little bit about how we’re looking ahead at the future of Recursion. It’s been an incredible last nine months post the business combination with Accenture. We really feel like we’ve pulled together the best elements of both companies’ platforms into the Recursion OS two point o as both myself and Najat talked about earlier.

And going forward, I think you’re gonna 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 gonna see us bring new ideas, new targets, new chemistry. We’re gonna use our MOA and target deconvolution systems, tools like BOLTS two, our QMMD systems, and even CRISPR screens to help, prosecute those exciting targets. And then we’re gonna continue to deploy this ClinTech platform to help translate the models and the and the programs that we’re developing at Recursion with real world evidence into programs that can move towards the clinic. And, we are focused on differentiated, high quality programs that are gonna go where others can’t, and we’re excited for the Recursion two point o 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 eighteen months, we have a catalyst packed calendar. The second half of this year looking really exciting, multiple readouts including FAP and CDK seven, as Najat spoke to earlier. In the first half of next year, we’ll be talking about our RBM 39 program with early safety and PK from the monotherapy trial. And then rolling into the second half of next year, we’re gonna be looking at both malt one and initiating our e m p p one program, which we were able to bring in, recently in in, from our JV with Rally Bio. In addition to what you see here from our internal pipeline, we’re gonna 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 drug discovery platform that we think is gonna 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 gonna move over to the q and a portion, and I’m gonna go to the first question, which comes from multiple parties, which is about our Bolts two project. So the question is, is Bolts two 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 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, you know, discovering, 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 phonomics platform and our design platform.

These are places where we’re gonna 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 two. So we’re commoditizing our complement, making sure that, 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 two models before that they were public. We also have large scale internal datasets, and one could imagine that we could take the same kind of, architectures, the same kinds of models that have been, built in Boltz two and training them across much larger proprietary datasets to give us an internal advantage. So the second question, I’m gonna 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 two after you answer the first one.

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: 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 six point seven months, and then median OS was about fourteen to twenty two months.

And look. For us, you know, for the combination, we definitely wanna see meaningful improvement to the standard of care. This is a patient population with very significant unmet need. And, you know, 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 on go ongoing there, but we definitely wanna see meaningful improvement from the standard of care for PFS.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thanks, Sanjot. You hit part two there. So I’ll move on to the next question, which is, Brendan from Cowen and Alec from BFA ask, you mentioned the multiomic profiling that’s ongoing for REC twelve forty five, that’s our RBM thirty nine 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 r b m thirty nine compared to other CDK targeting assets?

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: 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 oh, 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, you know, really, instead of having I think the beauty of the maps of biology, the phenomaps, the multiomic approach, 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 to for us to understand that, look, for various forms of replication stress, which can be epigenetic, which can be, you know, other areas as well, and DNA repair vulnerabilities are both very important for r b m 39 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 in our in our, press release this morning. The other thing I’ll also say is, look.

The monotherapy dose escalation is gonna be important. We’re gonna 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 receive. 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 wanna go, forward with. 100,000 patients plus, and the expansion is because it actually targets abroad has a potential, I should say, to target a broad set of of tumor types with that are genomically unstable.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thanks, Najat.

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: And then the

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Oh, go ahead.

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: I didn’t answer the question. Just wanted to make sure I answered that. The point of differentiation, r b m 39 and c d k acid. Look. R b m 39 is not a kinase.

Right? And a lot of the kinases, for instance, as I mentioned, CDK 12 has always been, for a long time, an important oncogenic target, but the homology with CDK 13 just makes it challenging to really get that selectivity that you’re looking for. So for us, it 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 d DDR pathways is 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.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thanks, Anshat. Okay. Next question. Brendan from Cowen and Sean from Morgan Stanley asked 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 to 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 three?

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: Thank you, Chris. And thank you, Brandon 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. Cytokoxib and others are used off label, polypropylene 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 gonna be really important for us is to look at the data later on this year where we’ll have a broader patient population. And the second question around, support for approval and uptake, you know, following the data that we see later this year, of course, it’s gonna be important to have conversations with regulators.

Once we do, happy to follow-up, and share more in terms of what’s gonna take from an approval perspective.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thanks, Najat. And next, have partnership questions coming from Gil at Needham and Sean at Morgan Stanley. Najat, I’m gonna send the first one over to you, which is for the 7,000,000 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?

Najat Khan, Chief R&D and Chief Commercial Officer, Recursion Pharmaceuticals: Great. So, the programs that we have and, again, up to 15 programs as part of this partnership. We 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 does design them It’s not how you do it traditionally.

And the fact that we’ve been able to get four out of four 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 twelve to fifteen months.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: I think this is one of the interesting things about the tech bio space, Najat and and Dennis or I I should say Gil and Sean is that, you know, a lot of the, 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 gonna turn it over to you now. What visibility, if any, do you have on the potential 100,000,000 in milestones by 2026? Are any assumed in the cash runway calculations?

And again, this comes from Gil, Needham, and Sean at Morgan Stanley.

Ben Taylor, CFO and President of UK, Recursion Pharmaceuticals: 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 would 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 two 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.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: Thank you, Ben. And next, we’re gonna 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 q four twenty twenty seven, cash out.

Ben Taylor, CFO and President of UK, Recursion Pharmaceuticals: Sure. Absolutely. So couple 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 and 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 and look down at at what is flowing through there. Secondly, all of our guidance that we gave, the 450,000,000 this year, the 390,000,000, next year is cash based, operating expense and CapEx, not including any partner inflows or new business development or financing. And so what 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 twenty twenty seven. What we felt comfortable with is even just looking at our existing partnerships like I was just talking about with the 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 could get to the fourth quarter twenty seven. 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.

Chris Gibson, Co-Founder and CEO, Recursion Pharmaceuticals: 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 that reflect your next level of thinking? John, thanks.

Great question, I think, to end it. First, I’d just say, if you’ve looked at the, State of AI report that Nathan Benioch 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, x AI, or any of those companies, but we really are, driving one of the most sophisticated large scale compute initiatives in the whole of of biopharma. And I think that speaks to the kind of ambition that we have for how technology is gonna drive this this field forward. But in terms of other initiatives, you know, 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 of a gene or or the expression level of of a gene, you add a small molecule or multiple small molecules. And we believe that building a reliable and robust virtual cell is gonna require not just having really good protein folding data, not just having really good atomistic and physics modeling, and not just having good patient data or pathway data. It’s gonna require having all of those different data layers and being on the frontier of all of those. And I think Recursion today through our partnerships with companies like Tempus and Helix really driving the patient layer, through our own work at Recursion, building the pathway data with both genome scale knockout maps across more than a dozen different, human cell types.

And then as you heard heard today with our Boltz modeling and some of our QMMD modeling, we’re able to really work at the protein folding and the atomistic, modeling layer. And I think being able to operate across all those layers is gonna be a real advantage as we race towards the virtual cell and deploy early versions of that internally. What’s more, we have a team at Recursion called the Frontier Research Group, and the Frontier Research Group is a dedicated group of folks who are working at the very frontier in high risk but high reward areas. And while this, virtual cell is a part of the work that that group is doing, some of the work you heard about today, including the causal AI modeling using Tempest data, actually started in this frontier research group and now has gone into production across the Recursion OS. And these are the bets we make in high risk, high reward areas that then get deployed, in some cases, just six or nine months later.

I can’t tell you about all the things we’re doing in that group, but I will say one of the areas we think is super interesting, we’re watching very closely, is the use of agents to automate the way we discover things and to automate the way we might discover medicines. And that’s certainly an area that we’re working, to to stay really close to as well. So lots of exciting work happening at Recursion and across the whole field. It feels like a very, very exciting area, to watch for the next half decade or so. So I wanna thank everybody for joining us today.

We really appreciate having you, really appreciate the questions, and we look forward to seeing you at the next earnings call or perhaps sometime before then. Thanks, everybody.

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