Good morning, and thank you so much for joining us. I want to start by briefly framing where Recursion Pharmaceuticals, Inc. is today in its journey and evolution. Over the past decade, Recursion Pharmaceuticals, Inc. has built something truly special: a differentiated platform pioneering the integration of large-scale biological data generation, machine learning, and compute to better understand the complexity of biology. We have also deliberately strengthened the foundation in chemistry and AI through the acquisitions of Excientia, Valens, and Cyclica, creating a truly powerful foundation. Today, we are at an important inflection point. We are harnessing everything that we have built to date to do two things. Number one, translating insights into evidence—evidence that this platform, the use of AI end to end, can generate medicines that matter—and we are doing this both across our wholly owned portfolio and through our partnerships. With strong momentum across both fronts, I am excited to share some of the updates today. In parallel, we are also continuing to advance. Today, we have what I like to call a trifecta that is required to make impactful medicines: AI-driven biology, AI-enabled chemistry, and AI applied to clinical development. We continue to invest to ensure we are defining the standard for how AI is applied across the full life cycle of R&D. As we look across the sector, we are encouraged by the broader momentum in the field—new models, flares, partnerships being announced—but the industry is clearly entering a new phase where value is being defined not only by the models you build and the collaborations that are announced, but by actually translating those into capabilities, into real application, and measurable impact. The important question now is not only what you build, but what you can unlock, and that is the chapter Recursion Pharmaceuticals, Inc.…

Thanks, Najat. 2025 was a year of financial transformation for the company. As a part of the integration, we decided to rebuild all of our corporate systems from the ground up. This was really important because we wanted to be able to apply the same level of discipline and rigor to our strategic decision-making that we do to all of our scientific decision-making. We looked at how every dollar in the company goes toward a specific quantifiable outcome, and that is how we were able to achieve the efficiencies that we did over the last year while still advancing a portfolio of five clinical programs, hitting different partners’ milestones, and really investing behind the growth in our platform as well. All of that comes back to focusing on those investments across our pipeline and technology portfolio that have the best risk/return and that are going to give us the most impact for the investment that we are making. That is how we were able to come back and have a 35% year-over-year reduction from pro forma 2024 to 2025 and even come in 10% below the guidance that we originally provided in May. We ended the year with $754 million in cash. Looking forward, operating expenses—our 2026 cash—are expected to be under $390 million. Cash operating expenses is a non-GAAP measure that we are going to be using to give you guidance. We have a lot of noncash expenses in our P&L, and so we wanted to provide something that showed what our cash profile might look like going forward. This is coming directly off of our cash flow statement. If you look at operational cash flow and then you add back our inflows from partnerships and transaction costs, you will be able to get directly to this guidance number. In addition, last year it was really exciting to see that we crossed $500 million in cumulative partner inflows. We expect to continue to achieve those going forward. In fact, we hit our first milestone earlier this month already, and so we do include probability weighting of some of those milestones in our cash flow projections going forward. The really exciting part is not only were we able to exceed our efficiency expectations, but that actually means we are extending our cash runway. We are updating our guidance to early 2028 as of now. With that, I will hand it back over to Najat.

Thank you so much, Ben. We will wrap it up by saying, looking ahead, we have a very broad set of catalysts coming up, and it is going to be a busy next 18 to 24 months. This year, we are on track for our initial engagement with the FDA on REC-481. We are looking forward to that, and also initial data—early safety and PK—for RBM39. We have go/no-go decisions for PI3K and ENPP1, which are both in IND-enabling. We will also have additional data for REC-4881 early next year, and then combo data expected for our CDK7 program, as well as more early safety and PK data from MALT1 and LSD1. Recall for both of those, we designed the assets to be more tolerable, so these are going to be important. Partner catalysts will be very important: our partnerships with Sanofi across multiple programs progressing into more later-stage development candidate and other milestones, and in addition, these maps of novel biology extracting into new programs with Roche Genentech. We continue to invest and push the boundaries in our platform, defining what industry standard really looks like for making medicines using AI, and as Ben mentioned, pairing that important work with disciplined execution. We have pivoted toward an outcomes-based budget where we test what value creation every dollar can drive—doing more with less. I will close by saying thank you so much for the time. Our focus will always remain on value creation for patients—they are the ones we ultimately serve—and also our shareholders. Thank you again for listening. We will now open for questions. I will also have our CSO, Dave Hallett, joining us as well, in addition to Ben Taylor. We have questions from Sean at Morgan Stanley and Priyanka at JPMorgan, and from Brendan at Cowen. There…

Sure. Happy to. Yeah. Thanks, Alex. I agree with your data. It is really about efficiency more than cost cuts. We have hit a point where we have gone through all of the integration. I would assume that is all complete. There are no big one-offs on the system side. We come in with the attitude that we want to continue to find ways for every dollar to make more of an impact in the following years and months than it did previously. When you come in with that attitude, you start to find ways to do more with less. That is where we expect to be able to continue growing our pipeline, investing heavily behind our platform, and moving things forward while still hitting those cost targets that we put out there.

Great. Thank you, Ben. The only thing I will add is the piece around rapid go/no-go decisions and how we are doing that—the mentality and the mindset—and also understanding the variety of areas we are working on and what the value proposition across the different areas is, which evolves as you generate more data. Thinking like an investor is really important—being agile around capital allocation—and that is what we will continue to do, driven by data. Next question: NVIDIA—what was the rationale in terms of the divestment? Do you plan to seek other technology partners? Does NVIDIA now have proprietary insights from the models you have trained, etc.? It is important to decouple two parts. One is the investment from NVIDIA, and one is our collaboration—our technical collaboration—with NVIDIA. The technical collaboration with NVIDIA continues. Some of you might have just seen we are going to be highlighted in a lightning round for NVIDIA’s upcoming GTC presentation with HyRes, with Recursion Pharmaceuticals, Inc. being a pioneer in how to leverage automation. This wet and dry lab is not just words; this is actually in action. This is how we do millions of experiments a week. Our collaboration with NVIDIA “Runner 2,” one of the fastest supercomputers in life sciences, underpins examples from PI3K—using machine learning and molecular dynamics. Our partnership with NVIDIA could not be any stronger. In terms of the divestment, if you look at the public 13F filings from 2025, it is really a shift in NVIDIA’s investment portfolio to more larger on-strategy supercomputer data center efforts. It is a portfolio shift, and we were not the only company; other decisions were made as well. It is a collective shift to more on-strategy investments—large, billion-dollar-plus investments. On seeking other technology partners: we have a strategic partnership with Google in cloud compute. We have a partnership with NVIDIA on machine learning, models, and on-prem compute. We have always been one of the pioneers in bridging the world of tech and science, and we will continue to do that. One more question from Georgia: with the recent positive preliminary efficacy data for REC-481 in FAP and the achievement of your fifth milestone with Sanofi, what specific metrics or historical comparison from your current clinical portfolio best demonstrate that Recursion Pharmaceuticals, Inc. is improving the probability of clinical success or speed of development compared to traditional discovery methods? I am going to hand it over to Dave Hallett to get us started, and I am sure we can add more comments as well.

Thank you, Najat, and good morning and good afternoon to those of us in Europe. I will start from the discovery perspective. During the last presentation, Najat highlighted a number of themes: repeatability of delivery, specifically highlighted in the burgeoning Sanofi pipeline we are building together. This is a repeatable platform that is delivering both best-in-class and first-in-class solutions for challenging targets. As we highlighted above at JPMorgan and again in this presentation, the speed of delivery—if you look at the metrics in terms of the numbers of novel compounds that we synthesize and test and the speed that we are getting to these development candidates—further demonstrates the role technology plays in accelerating delivery. The proof is ultimately in the clinic, and we are very excited for patients in terms of FAP. This is the first example from our platform where we have been able to demonstrate that a compound that came from Recursion Pharmaceuticals, Inc. has shown clinical proof of concept, and the goal over the coming months and years is to show repeatability in that frame as well.

Thank you, Dave. To add a broader perspective, looking at Recursion Pharmaceuticals, Inc., we have five-plus clinical programs, a diversified portfolio on the clinical side, and a diversified portfolio on the discovery side. It takes time and effort to build a platform. These datasets did not exist; the models did not exist. We are not a one- or two-asset biotech; we are a tech-bio for a reason, which is what Dave mentioned: we are focusing on repeatability and scalability, making this more engineering-focused, using agents or automation to do things better and faster, taking toil out of systems to supercharge our scientists to do the hard work of drug discovery and development. Drug discovery and development is inherently probabilistic—most things do not work. We have a 90% failure rate. Multiple shots on goal are important. Two worlds—tech and bio—have not really come together before, and we are not just building models that are interesting, but actually applying models that unlock value. We constantly look at metrics and stats—the team knows I call them green shoots—whether it is the number of compounds we synthesize (90% less than industry), the speed, the cost of our INDs. We do the same in the biology platform and in clinical development, where we are seeing improvement in enrollment. There is much work to be done, but this is what gets us excited. It is hard, but incredibly challenging and rewarding work. Thank you to our partners and shareholders, and most importantly to patients who are willing to take a bet on us and our programs and who are waiting. We are working as hard as possible to forge a new era of how medicines are made for patients who are waiting. Thank you again for joining us today, and we look forward to sharing more.