Recursion Pharmaceuticals, Inc. (RXRX) Earnings Call Transcript & Summary

Hi, everybody. I'm Chris Gibson, Co-Founder and CEO of Recursion, and I'm delighted to welcome you to our update call today, just, just post-close of the business combination with Exscientia. I'm joined today by our Chief Commercial and R&D Officer, Najat Khan; and our newly minted Chief Scientific Officer, David Hallett, and really excited to be sharing a bit more about the go-forward plan for Recursion, coming along very soon here. So let's dive into some slides. Perfect. So I want to just talk a little bit about today, where Recursion is, the overall value proposition post this business closed. And I think I want to start at this high level here. After this business combination, this entity now has about 10 clinical and preclinical programs spanning oncology, rare diseases and other areas of high unmet need. There's another approximately 10 programs in advanced discovery. There's more than 10 programs that have been optioned by our partners and are advancing towards the clinic. And over the next 18 months, we expect to have approximately 10 milestones for our programs that could be new clinical starts, that could be updates on data or even clinical readouts. All of this on top of one unified operating system combining the best elements of first-in-class drug discovery, leveraging technology of Recursion and best-in-class drug discovery, leveraging technology at Exscientia. And I think these 2 companies have now combined into one company with incredible track record in this industry, together having earned $450 million in upfront and milestone payments today. And that is just the start. There's over $20 billion in potential milestone payments in the future, from our 4 large pharma partnerships before the potential for royalties on net sales of many of the programs that we may advance together. So it's a really, really exciting time to be here at Recursion, as we look forward to the future. Our overall strategy remains unchanged. We're going to continue advancing an internal pipeline of assets focused in areas where we believe Recursion can truly build differentiated medicines and advance those medicines to patients. We'll continue to partner with large pharma companies in areas with complex therapeutic challenges, large and tractable areas of biology like neuroscience, immunology and perhaps in the future, places like cardiovascular and metabolism. And then, of course, our data strategy, which is so core to our business, we'll continue to explore mechanisms for licensing subsets of our data and tools like LOWE. And I think together, these 3 value drivers are just so exciting in terms of the long-term value proposition for Recursion. Now to dive in a little bit and talk about the combined Recursion operating system, let's go to this figure. And I want to kind of lift us up as we bring these organizations together and talk about the overall view of how we think about how Recursion is looking at biology and chemistry to try and understand how to advance medicines to patients more quickly. And the way we understand biology and chemistry is by measuring the real world, measuring biology, measuring chemistry, learning from those data and building models of those data that we then use to create hypotheses, and we put them back through this system to test. And we do this in a laboratory, a laboratory full of robots, both in Salt Lake City and in Milton Park here in the UK, where we're coming to you live. We're generating massive quantities of data across millions of experiments every week. And those data are being incorporated into a wide variety of different models. You can see these different kinds of data, these different kinds of models are coming together to create truly, truly fantastic hypotheses and learnings about biology. And ultimately, as we take these models, and we get better and better. Our belief is that eventually, they will become not just models of the real world, but actually a virtual cell. And that's what we'll actually transpose from real-world informing the world models to a virtual cell that informs simulations and hypotheses that we can make to take drugs into the clinic. With that, let's dive into a couple of more slides. Perfect. I want to talk a little bit about our pipeline at a very high level. Ultimately, at the end of the day, we are here to make medicines for patients. And so I want to really start there. And we will go ahead and just head over and look at the pipeline overview. So today, sharing our go-forward pipeline strategy, 10 clinical and preclinical technology-enabled program spanning oncology, rare disease and other therapeutic areas. Many of these programs actually are going to be generating readouts in the coming quarters. As I mentioned before, 10 different milestones over the next 18 months, we're going to be working across first-in-class, best-in-class. And to share a little bit more about these programs. I'm happy to turn it over to my colleagues, Najat and Dave. I think we're going to go over to you first, Dave, to talk a little bit about CDK7.

Thank you, Chris. And truly delighted to join Recursion, as Chief Scientific Officer. The story behind CDK7 is one of precision design and particularly to reflect the fact that this target has broad utility both in cancer, but is also an important enzyme in rapidly dividing healthy cells. Hopefully, I think we're all aware of the impact that the CDK4/6 inhibitors have had in the treatment of breast cancer, but they are imperfect and resistance is an issue. CDK7 is a multifaceted protein. It can be thought of as sitting upstream of some of the CDKs, including 4/6. So it controls progressive cell cycle. It is involved in transcriptional kind of [indiscernible]. And interesting as well, it also actually modulates the activity of the [indiscernible] receptor. But because an impact on healthy rapid dividing cells, this is a story of therapeutic index and very thoughtful precisely like the premises that we wanted to deliver and the compound has to be oral. It had to reversible in nature because we didn't want to inhibit the target for too long during the course of the day. We have [indiscernible] designed a molecule that has meant to have a relatively short half-life in humans. Again, this kind of Goldilocks effect of inhibiting the target just enough to actually kind of drive efficacy by allowing the target some freedom to actually embrace itself in Healthy cells. We've been doing a very pre-clearing 136 compounds to design what we can to qualified candidates. We have an ongoing monotherapy dose escalation study that I'll be delighted to reveal some data on. And this is an AACR special event in Toronto in December, where I'll give some insight into the ongoing study. So looking at pharmacokinetics, Pharmacodynamics and also initial safety signals. And also will be telling a story about how well did we do against our design parameters.

Thank you, Dave. And just a comment on precision design and why it's so important, the ability to actually increase permeability so that you have higher systemic exposure versus GI something that has plagued some of the other peer compounds that are available. So potential best-in-class, but depending on how things go, it also has the potential to be a first-in-class with appropriate...

Indeed is.

And that's where you'll see a common theme through the one pages, the one we will touch on today, but also overall in the corporate deck, which is using AI and machine learning to really solve the harvest problems in that design, to create that differentiated value Chris mentioned. So let's go to another example in oncology. RBM39 degrader. REC-1245. So the unmet need in solid tumors in lymphoma is significant. Over 100,000 patients in U.S. and EU. The mechanism of action, this is a degrader focused on RBM39, which is an important splicing factor, really critical for maintaining splicing fidelity. And by degrading that leads to many challenges, which we wouldn't want, such as tripling cell stress and apoptosis. So what is the differentiation play? I think the first is really the biological insight, which came from the Recursion platform. This is what you've heard from Chris before, and this is the foundation of Recursion, which is around phenotypic screening, looking at [indiscernible] of cells, disease and healthy, understanding what compounds naturally reverse to that healthy state. Now we're combining that with transcriptomic proteomics, truly becoming a multimodal powerhouse in terms of decoding biology to change patients' lives. That was the first differentiation is the insight. And by the way, it looks similar phenotypically to CDK12, which has been really challenging to drug, right? So this is an alternate approach to do that. The second piece is it's an oral first-in-class potent. And then third, of course, we looked at some in-vivo data. So as you'll see here, here is on CDF model that there are multiple CDF and PDX models where you start to see at monotherapy regressions of the tumor. A couple of things to note, similar to what you heard from Dave, the number of compounds we're synthesizing 150, 200 to get to the lead which in industry average range in the multiple thousands. And also doing that from target insight to actually IND-enabling studies in 18 months, true, so really accelerating the end-to-end. That's what the AI end-to-end tech stack can do. So next step, as you heard, IND-clearance, few weeks ago, we are imminently looking forward to opening the study site activation in first patient dose with a Phase I update slated on this monotherapy dose escalation for the first half of 2026. All right. So we had 2 examples in oncology. Now we're going to move over to rare diseases. We'll give you a couple of snapshot examples as well. Here's REC-4881 focused on FAP. So again, a disease with high unmet need, 50,000 patients in the U.S. and EU, no approved therapy today. Colectomy is what is done in adolescents. But even after that, there is a high incidence of not just cancer and risk of cancer, but also just challenges to quality of life. So 4881 is a MEK 1/2 inhibitor, selectively blocks the MAPK pathway. A couple of things to note from a differentiation perspective. Again, potential for first-in-class in FAP and definitely a best-in-class, there are MEK inhibitors out there but focused in other areas versus FAP. It is potent, allosteric. And another point I want to note is really around the preferential GI exposure. That's important for a disease like this where you're basically having hundreds of thousands of Polyps in the GI. Preclinical data, this is mouse model, APC min mouse model, kind of tiny, but I'll tell you 2 highlights. Number one, in terms of polyp production, significant polyp production even at the lowest dose, 1 mg per kg and outperforming that on celecoxib, which is a drug that's used quite often today, a COX-2 inhibitor as standard of care. The other, it's not just a reduction in the polyps, but also a reduction in the pre-cancerous polyps as well. So what are we looking for in this Phase II that's running right now? The primary endpoint is polyp reduction. That going to be important for a key consideration around benefits, key conspirations around risk, of course, for the class effects that you have that effects with MEK 1/2 inhibitors and more. All right. I'm not going to go through the reversion approach with very, very similar phenotype screening to really identify this insight and then the drug, the starting compound that we have now optimized. And as first fast track and orphan designation, futility analysis for this expected focused on polyp reduction in about 10 or so evaluable patients in the first half of 2025. So with that, I'm going to hand it back to Dave to tell us more about ENPP1 inhibitor.

Thank you, Najat. Super excited to be presenting this today. For those of you not aware, hypophosphatasia is a rare genetic disorder. It's actually caused by mutations in a human gene called tissue nonspecific alkaline phosphatase. And the impact of those mutations is that you see detrimental effects on bone mineralization. So bones, obviously can make calcium and phosphorous deposits amongst other things. In really extreme basis, it's actually lethal before birth. Again, in kind of -- even if the kind of the children kind of actually survive is that they then go on to a very short lives of very poor quality. And in the mild case, if you can call that is early onset loss of teeth and bone breaking life. And the pro standard care is an enzyme replacement therapy. The problem with that is that currently, it's over $1 million per patient year to administer that drug. Unfortunately, as the auto antibodies get generated as a function of time, so it affects vain. ENPP1 is genetically validated in a preclinical setting. And to the best of our knowledge, Recursion is the first company to demonstrate that chronic oral administration of an ENPP1 prototype molecule that we call REV101, not only has suppressive effects on a key biomarker and inorganic pyrophosphatase, kind of shown in the graphic here. But more importantly has kind of functional benefits both on the movement of the animals but also on bone morphometry as kind of shown in this diagram. These materials were actually presented by our key opinion leader, Jose Millan, at a key Board meeting couple of months ago. We are advancing a much more superior compound that we call in REV102, looking to actually formally declare environment candidate status before the end of this year. Really lucky molecule, very potent, very selective. Remember, it's likely that a drug like this will be have to be taken for the rest of somebody's life. So obviously, safety is kind of front and center.. And I'm hoping to kind of be able to showcase some of the in vivo data and we have behind this potential development candidates in the coming months.

Awesome. Thank you, Najat, thanks Dave. It's fantastic to hear a bit about those 4 programs. Just 4 of 10 that we have in our clinical or nearly clinical pipeline of Recursion. But beyond those programs, we also have some incredible partnership programs. And we've had the great fortune to be able to partner with some of the best companies in the industry from a therapy perspective, Roche Genentech, for several years into this massive partnership focused on neuroscience, the whole of neuroscience and a single program in oncology. We are partnered with Sanofi, focused in both oncology and immunology. That partnership is going extraordinarily well. We're partnered with Bayer, focused in various areas of precision oncology. And in addition to that, Bayer is one of the first companies leveraging our LOWE software platform and of course, partnered with Merck AGA in oncology and immunology. I don't think there's any other tech bio-company in the industry that's able to put together such an incredible roster of partners. And beyond just this roster of partners, we are demonstrating delivery in each one of these partnerships, as you can see here. Now we won't be able to update this all the time. There's a lot of information in here, but this gives you a sense of the scale that Recursion is operating across all 4 of these partners and several others. Each of these programs has the potential, we believe to be a compelling medicine for patients. And we're going to continue working hard not only on our internal pipeline, but on every one of these programs as well. And beyond the therapeutic partnerships, we've also partnered across the technology spectrum and the data spectrum with partners like NVIDIA and Google Cloud, with partners like Tempus and Helix, we're helping to augment the incredible data sets that we're building in-house at Recursion. And of course, our partners in Enamine who are helping us to simplisize many of the molecules that we need at scale. These are the incredible partners that we want to see going forward with us into the future, continuing to build on the incredible operating system that we have at Recursion. Now we talked a lot about our strategy for our pipelines, our partnerships and our data. I do want to take a minute and focus a little bit on the culture and team because this is a really big day for us. We've been flying all around. We're coming due live from Oxford today. We've been spending time with the teams here. We'll be spending time with the team in Salt Lake and across all of our different sites, tomorrow and for the rest of this week. And we really feel like we have an opportunity to bring together some of the best employees across the entire, not just tech bio industry but biopharma industry, in this United mission to decode biology to radically improve lives. And in addition to all of the incredible people on our teams at Recursion, I want to share some of the updates to our executive team and Board today. We have Dave joining us, of course, the CSO. But I also want to share that Ben Taylor, the Chief Financial and Chief Strategy Officer of Exscientia has joined us as Chief Financial Officer. We've promoted Kristen Rushton to Chief Operating Officer; and we have Matt Kinn being promoted to Chief Business Officer; and Lina Nilsson joining us as Head of Platform from within Recursion. Really excited to have such a capable team of executives guiding this company now across multiple countries, multiple clinical programs, multiple partnerships is really an incredible team. And I do want to take a moment to say a huge thank you to Tina, Michael and Laura, 3 incredible members of our executive team who've been with us for half a decade or more in every case. And they've just been such incredible colleagues, partners, ventures, and we can't wait to see all the incredible things that each of them goes to do next. In addition to our executive team changes, we're also welcoming Franziska Michor from Dana-Farber to our Board. She was part of the Board in Exscientia. She's now part of the Board at Recursion as of earlier this morning. And this is a stack Board, really incredible folks from the technology side, from the biotechnology side, from academics and from industry. And I think together with this executive team, the incredible team we have at Recursion now approximately 800 employees across site in Valpitas, Salt Lake City, Toronto, Montreal, New York, London and the Oxford area. This is truly, I think, the tech bio company to watch and the tech bio company to be. And we are all very, very excited about the mission going forward. We're going to work extraordinarily hard to deliver on it for patients and for all of you, our shareholders. And we really appreciate your support during what's been a very busy few months and we're looking forward to pulling our heads back up and getting forward on some of the science. And with that, I think we'll turn over to some questions.

Let's see. Going to the Board. First, we have a question from Joe. Can you talk about your reasons from shifting from cell painting to brightfield imaging for your screening of cells? Thank you, Joe, great question. So actually, we put a blog post out about this recently. And I would say at a high level, it turns out, despite it looking like very, very challenging to see a lot of information in a brightfield image to a human eye, you can train a computer vision algorithm to extract, essentially, all of the same or almost as much information as you can get out of a fluorescently labeled image. And because we were able to train these massive computer vision models on millions, hundreds of millions of brightfield images, we put ourselves in a position to be able to not have to fix and stain cells. And the huge advantage there is it means we can now do time lags. And if you're trying to build causal models of biology, not just understanding correlations between different genes and pathways but actually have different genes and pathways cause and affect each other, this time series data is going to be incredibly important. So thank you for that fantastic question. All right. Next, let's head over to -- let's talk about -- Dennis Ding from Jefferies. Can you speak more to the CDK7 monotherapy data coming in December and what will constitute good data for a Phase I dose escalation? What's your relative confidence in threading the needle on efficacy, safety as others have tried to drug CDK7 and faced safety issues. I think I'll turn it over to you first on that one, Dave.

Yes, it's a great question. So the plan in this meeting is to sort of -- is to present human pharmacokinetics, also looking at blood-based pharmacodynamic measures. So as we kind of dose escalate kind of what we're doing in terms of target engagement. Obviously, looking at kind of adverse event profile as we've dose escalated. I will add we're still actually in the dose escalation phase. We've not recent MTD yet. That's still ongoing. What would look like? For me, I think it's about kind of how we made a lot of predictions about the targeting candidate profile. We've got preclinical data that suggests say, targeting kind of IC80 coverage, for about 8 to 10 hours over the course of 24 is about optimal. Any less than that, then you lose efficacy in kind of preclinical models. Any more than that, and you drive so drive -- start to drive side effects. So what [indiscernible] for me were not likely, as we said, we are trying to kind of show a modest half-life in humans, how do we do against that? As we've dose-escalated, are we getting anywhere near what we think might be biologically effective dose. And as we dose escalate what are the -- what's the adverse event profile like? Because remember, it's highly likely that this is a drug that will be used in combination. Indeed, to [indiscernible] study will pivot towards a combination study in breast cancer. And so looking at CDK4/6 refractory patients together with fulvestrant. But there are other indications looking as well where we might combine this agent we say a checkpoint inhibitor. And so trying to kind of find a thread the needle as you said, a relatively benign kind of safety profile for the therapeutic index to allow us obviously to dose as high as possible. So yes, watch this space, I'll be in Toronto in 2 to 3 weeks, and we'll provide an update then.

December 9. Awesome. All right. Let's -- next -- it looks like we've got a couple of questions from [ Cory Solidad ] and Brendan that are all pretty related. So in terms of platform capabilities, what are the most salient points of synergy with the new combined platform? What are the most important capabilities of the new integrated tech will now be able to do provide that either was not able to do separately. And for that, I'll turn it over to you, Najat.

Great. Thanks, Chris. Thank you, Brendan, for the question. very, very excited about the new end-to-end platform. So what are the points of synergy? On the biology front, as I was saying, Recursion started with Phenomics, but really the last year, 1.5 years has been the era of multiomics, and being able to really stack that phenomics clinical genomic data, transcriptomic proteomics, those layers really help us do 2 things: number one, first-in-class targets. Number two, also new insights around best-in-class markets and potential polypharmacology you want to avoid. That is a great addition to what Exscientia is bringing to the table, which is really around precision design using their central platform, generative AI and QMMP dynamics in order to really understand what are the hotspots that exist for we have structure. And next, using active learning, for one of the challenges -- biggest challenges in the pharma space, which is lead optimization. The 2 are highly complementary. So what we expect to see, and you'll see in our earlier, Chris mentioned 10-plus advanced discovery programs, you're seeing more and more first-in-class novel targets is really coming from the multiomic era from Recursion, coupled with high rigorous and efficient approaches to precision design, an average of 200 compounds to the size in order to get to your lead series versus a couple of thousand, which is the industry standard today. And I'd be remiss to say the third part, which is not so much as a points of synergy from this combination, but a point of growth and evolution for Recursion as well. 10 clinical/preclinical programs mean we want to be best-in-class in discovery and in development. So also watch out for some of the investments we are making to develop the development space, no pun intended, leveraging real-world evidence in AI for smarter trial design, to drive precision medicine and then thirdly, also in order to recruit patients much faster.

If I can maybe just add a little soundbite to that. The way I think about this, think about the first slide that Chris presented, so about Recursion decoding biology. Exscientia was about encoding chemistry and I think the combination here is about -- on the one hand, how do you deliver insights from large data sets that have either been kind of generated experimentally or procured. But in some cases, the data sets are small, the data sets are sparse and you have to learn them into a problem. The combination actually allows the go-forward company Recursion to actually bring both those powerful elements together.

Thanks, Dave. And I think that builds on to a question that Alec from BMA asked, which is just talking about where do -- does the deal complement or enhance Recursion capabilities beyond just the pipeline and the partnerships. And I think both of you mentioned here, but at the end of the day, biology and chemistry are extraordinarily complex. And the interplay between these 2 is just such a magnificent and challenging problem to try and understand. And I think we are better positioned than almost anyone in the world with the scale of the data we've generated in-house between the 2 companies. The scale of the data we are building into our pipeline from partners like Tempus and Helix, perhaps more in the future. And then the incredible teams and algorithms that we're building on the world model side that are allowing us to turn all of that data into a computational understanding of how biology and chemistry are working. And we're both decoding and encoding, biology and chemistry, as you said, Dave. And this is one of the greatest challenges that I think humans are facing, is trying to get to a place where we can demonstrate the biology and chemistry are deterministic where we can get to a place where we can truly industrialize drug discovery. And we are just a little over a decade into that mission, now together as one company. I think the most compelling company in this space. And I think in many ways, we're just getting started. We'll go back into the board for one more. We got a quick question from Roman. Previously, it was mentioned and written in several places that Recursion was on track to deliver 25 unique data packages to Bayer within Q3. Can you give us an update? I can, done. All right. Let's see. Let's go to...

I just want to add one thing because there's a broader theme around the progress we're making from a partnership perspective. So if you look at Sanofi, we've achieved 3 out of the 3 milestones this year on programs across oncology and immunology. In Bayer, for instance, we're moving rapidly with 2 programs in the oncology space, to lead series nomination and on track with additional 5 or a full set of 7. And one other thing I just want to say -- I can't help but go back to the prior question. There's a platform piece, there's a pipeline piece, but actually having the right talent is incredibly important. This is a -- I think it's the secret sauce in terms of how do you get 2 disciplines to come together and drive value from it, not experiments for the sake of it. But actually drive value, whether it's the programs and the platform. And I think that's what you have with both Exscientia and Recursion coming together. Our respect and humility, understanding both biology chemistry science world and AI machine learning. And then the next is, look, 10,10,10, which is the theme that we started of with is ambitious, yet it's also being disciplined. So you'll see in our slides also some of the choices and trade-offs we have made because it's going to be complex to execute on everything. And as Chris said before, we're really doubling down in areas where we have a differentiated right to win.

Thanks, Najat. I think we're going to go to the last question here. We're going to talk a little bit about the path to revenue for the Recursion OS and explaining -- this looks like a summary of multiple people's questions, explaining what that is for those who are new to the company. If you are new to the company, thanks for joining us. I think, ultimately, the path to revenue for the Recursion OS is going to be making medicines that make a difference for patients. On the way there, there's lots of ways that we can continue to help subsidize the incredible mission and adventure that we're on to trying to decode biology. One of those through our partnerships, as I shared earlier, we've already earned upfronts and milestones to date, nearly $0.5 billion in economics from our partners. That is before a potential $20 billion in additional economics and royalties that we can earn on some of the programs that we have just coming with the 4 companies that we have partnered with already today. Beyond that, we have the opportunity to leverage tools that we're building, potentially software tools like LOWE as part of partnerships or even potentially as a stand-alone tools with partners. And that's part of the business experiment that we continue to do. We love the feedback we're getting from our colleagues, at Bayer in terms of their usage of LOWE. We continue to open source a number of different models and tools that we're building at Recursion as well, and I think you can continue to see us leading there. But at the end of the day, a company like us will be successful when we drive medicines to patients. We are well on our way there with many programs in the clinic today, many programs leading to important readouts in the coming 18 months. And I am as excited as I have ever been about the future of Recursion. I'm so thankful to be joined by both of you today to be joined by the incredible teams at Recursion at Exscientia, now all going forward together as Recursion. And the future looks really bright from here in Oxford from Salt Lake City, and we look forward to talking to you again very, very soon. Thanks, everybody.

Thank you.

Thank you.