RXRX

It has been about a month since the last earnings report for Recursion Pharmaceuticals (RXRX). Shares have added about 8.2% in that time frame, outperforming the S&P 500. Will the recent positive trend continue leading up to its next earnings release, or is Recursion Pharmaceuticals due for a pullback? Before we dive into how investors and analysts have reacted as of late, let's take a quick look at the most recent earnings report in order to get a better handle on the important drivers. Recursion reported a loss of 25 cents per share in the second quarter of 2026, wider than the Zacks Consensus Estimate of a loss of 23 cents. The company had incurred a loss of 41 cents per share in the year-ago quarter. In the absence of an approved product, Recursion primarily recognizes collaboration and grant revenues. Total revenues were $7.67 million, which declined 60% year over year and missed the Zacks Consensus Estimate of $14 million. Lower Roche collaboration revenues hurt the top line. The reduction followed the successful completion of certain project phases during the prior-year period. Operating revenues totaled $7.3 million in the second quarter, down 62% from $19.1 million in the year-ago quarter. Grant revenues rose significantly to $0.37 million from $0.12 million a year earlier. Research and development expenses decreased 30% year over year to $89.6 million. The decline primarily reflected lower platform costs due to the timing of Tempus record purchases and improved operating efficiency. The reported quarter included $3.1 million in non-cash expenses related to the use of Tempus’ patient-centric multimodal oncology data compared with $22.7 million a year earlier. General and administrative expenses declined 11% year over year to $41.5 million, primarily due to lower salary expenses following headcount reductions. Cost of revenues fell 43% to $11.5 million from $20.2 million in the prior-year quarter. Recursion Pharmaceuticals had cash, cash equivalents and restricted cash of $556.8 million as of June 30, 2026, compared with $665.2 million as of March 31, 2026. Based on its current operating plan and without additional financing, RXRX expects its cash reserves to support operations into early 2028. In the past month, investors have witnessed a flat trend in estimates review. The consensus estimate has shifted 6.51% due to these changes. At this time, Recursion Pharmaceuticals has a average Growth Score of C, a grade with the same score on the momentum front. However, the stock was allocated a grade of F on the value side, putting it in the fifth quintile for value investors. Overall, the stock has an aggregate VGM Score of F. If you aren't focused on one strategy, this score is the one you should be interested in. Recursion Pharmaceuticals has a Zacks Rank #3 (Hold). We expect an in-line return from the stock in the next few months. Recursion Pharmaceuticals belongs to the Zacks Medical - Biomedical and Genetics industry. Another stock from the same industry, Moderna (MRNA), has gained 176.4% over the past month. More than a month has passed since the company reported results for the quarter ended June 2026. Moderna reported revenues of $145 million in the last reported quarter, representing a year-over-year change of +2.1%. EPS of -$1.97 for the same period compares with -$2.13 a year ago. For the current quarter, Moderna is expected to post a loss of $1.36 per share, indicating a change of -166.7% from the year-ago quarter. The Zacks Consensus Estimate has changed +26.1% over the last 30 days. Moderna has a Zacks Rank #3 (Hold) based on the overall direction and magnitude of estimate revisions. Additionally, the stock has a VGM Score of B. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Recursion Pharmaceuticals, Inc. (RXRX) : Free Stock Analysis Report Moderna, Inc. (MRNA) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research

Image source: The Motley Fool. Wednesday, Aug. 5, 2026 at 8:00 a.m. ET Chief Executive Officer - Najat Khan Director of Structure-based Technology - Chris Radoux Management - Vicki Goodman Management - Ben Taylor Najat Khan: Good morning, everyone, and thank you for joining us. Before we begin, I'd like to remind everyone that today's discussion will include forward-looking statements. Next slide. Please refer to today's press release and our SEC filings for additional details. At Recursion, our mission is to decode biology to radically improve patient lives. And we do this by building transformational medicines with an AI-native product engine. Over the past year, we have reached an important inflection point. We are no longer just discussing the potential of our platform. We are demonstrating the ability of our AI-native product engine to generate differentiated programs and medicines. Just as a reminder, the engine you see on the left-hand side is built as a continuous learning system. Proprietary multimodal data created in our data factory powers Frontier AI models. And these models can generate new hypotheses where every single prediction is tested experimentally. Each cycle strengthens both the engine and the products it creates. Ultimately, though, the measure of any engine is its output. So let's talk about that. First, our internal pipeline continues to mature. We now have 5 clinical stage programs, including REC-4881 in FAP, where we have generated some of the most promising clinical data in the company's history. Remember, in a disease with no approved therapy and a TAM of almost $10 billion. Second, we continue to make significant progress in our partnerships while learning from the best in the industry and also while validating our engine externally. Together with leading biopharma partners, we have generated more than $500 million in realized inflows while advancing differentiated programs with Sanofi and Roche, Genentech. So today, I'll share how we continue to strengthen our product engine and how we take these advances and are translating it into differentiated medicines, differentiated partnerships and ultimately better outcomes for patients. So the question that naturally comes up, what makes our product engine different? There are many companies applying AI to drug discovery. We believe our advantage isn't AI alone. It's a combination of 3 capabilities that reinforce one another. First, we generate our own proprietary multimodal biological and molecular data at scale. This matters because AI can only learn well from high-quality data and much of the most valuable biology has never been measured systematically. Our 50 petabytes of data is designed specifically to train models, discover new biological relationships and improve over time as new algorithms emerge. Second, we connect these models directly to experimentation through a Lab-in-the-Loop system, spanning biology, design and increasingly the clinic. Every prediction, as I mentioned before, is validated experimentally. Every result feeds back into those models. It is that recursive loop that helps us to move faster, improve our decision quality and systematically build confidence in our programs. And third, and most importantly, we convert these capabilities into differentiated assets. That includes both our internal clinical programs such as REC-4881 in FAP, REC-1245, RBM39 in solid tumors as well as our partnered programs with Sanofi, Roche-Genentech. So how are we doing? Let's look at the progress we've made over the year to-date. As we look back over the first half or so of the year, I'm very pleased with the progress we're making across all 3 dimensions of our business: our internal pipeline, our partnerships and the continued advancement of our AI-native product engine. On the internal pipeline, we advanced REC-4881 with our initial FDA engagement following encouraging Phase II data and additional Phase II data coming later this year that Vicki will talk about shortly. We have continued to build confidence in REC-1245 with early clinical safety and pharmacokinetic data. And we just received IND clearance for REC-7735, positioning it to enter the clinic later this year. At the same time, our partnerships are also making progress. As you'll remember from earlier this year, we achieved another milestone with Sanofi, our fifth to-date on developing a novel lead series for a very challenging first-in-class oncology target. But I'd like to pause on a new milestone in particular that we're announcing today. Together with Roche-Genentech, we are thrilled to announce that Genentech advanced the collaboration's first neuroscience target, a new unexplored target in neuroscience into a joint early discovery program, providing early evidence that Recursion's platform can generate novel biologically-validated targets for drug discovery. To me, this represents much more than another partnership milestone. In an area where progress has been slow for decades, it provides early evidence that a fundamentally different approach, combining proprietary disease-relevant Atlases, purpose-built foundation models and that rigorous computational and experimental assays that we use to build confidence that these targets are actually causal. And of course, last but definitely not the least, the deep collaboration, scientific and technical with the partner can uncover previously unexplored therapeutic targets. While it's still early, I believe this is an important proof point for both Recursion and the broader field. It suggests that an AI-native engine can move beyond optimizing known biology to discovering new biology, compelling enough to advance into drug discovery with one of the world's leading neuroscience organizations. So that's just the left-hand side, but we have a lot more coming ahead. For REC-4881, we will present additional Phase II data at the CGA-IGC Conference, a premier medical congress for inherited GI disorders, our specific target audience for FAP. And we will also provide an update on our FDA interactions as well as continue advancing what we believe could become a transformational therapy for patients with FAP. Remember, nothing approved to-date, no approved therapies. For REC-1245, we are continuing our dose escalation and generating additional Phase I data, and we'll have a more wholesome update later this year. With Sanofi, we expect the potential nomination of an oral I&I development candidate, a very important milestone that would further validate our ability to design differentiated small molecules against challenging targets with the potential to impact multiple immune-mediated diseases. And finally, we expect to initiate the Phase I study for REC-7735, further expanding our clinical oncology pipeline with another precision design program from our engine. Taking together, these milestones reflect a company that is delivering ambitious proof points that matter while executing with focus and discipline. But equally important, we continue to strengthen the engine itself. Let me show you a few examples of how that innovation across biology, chemistry and clinical development is making our engine faster and smarter. Let's start with biology. One of the biggest challenges in the industry is that much of human biology remains unexplored. We believe the answer isn't simply building larger AI models. It's generating proprietary disease-relevant data that these models can actually learn from. To do that, we have generated and aggregated more than 50 petabytes of multimodal biological data, creating what we believe is one of the largest proprietary data sets in the industry. And as that data set grows, our models become better at discovering novel biology and every new discovery further strengthens the engine. That learning then carries into design. Because our biology models generate higher confidence hypotheses, our chemistry platform focuses on designing better molecules more efficiently. There's much to share here, but one thing I'll mention is we are advancing candidates using roughly 330 compounds over approximately 1.5 years. So going from target to candidate in 1.5 years compared with industry benchmarks for small molecules of roughly 2,500 compounds over 4 years. That's a meaningful improvement in both speed and capital efficiency. And finally, we extend that same philosophy into the clinic. But clinical development is where a lot of value is ultimately created and where also a lot of programs fail. By bringing AI into trial design, picking the right patients, I can't enforce that enough and site selection, we're already seeing improvements in enrollment, speed and patient matching, helping us to run smarter and more efficient studies. But one more important point, this isn't 3 different capabilities. It's one continuous learning system. Every experiment improves our data, better data improves our models, better models make better molecules and then clinical data is fed back into the system to make the next generation of products even stronger. Perhaps the best example of the flywheel in action is what we have demonstrated with Roche-Genentech, and we're announcing today where our biology engine discovered a previously unexplored and new neuroscience target. I'd like to spend a few minutes just to take you behind the scenes as to how we got there and why we believe this represents an important new approach to discovery medicines. Together with Roche-Genentech, as we worked in this area to discover a new unexplored target from our AI-driven map of biology, we focused on a few specific elements. Why does that matter? First, this wasn't about finding another target within a well-studied biology. It was about uncovering previously unexplored biology and building enough evidence experimentally to advance it into drug discovery with one of the leading neuroscience organizations in the world. Second, we believe this validates something bigger than a single target. It provides early evidence that when you combine the right data, build the right models, do very rigorous computational and experimental validation and pair that with the right complementary collaboration, you can actually systematically uncover novel biology. And we believe this is just the beginning. The underlying biological maps are reusable. This is a really important point with the potential to generate many more therapeutic opportunities over time. Finally, across our collaboration with Roche-Genentech, we've now achieved more than $260 million in upfront and milestone payments with the opportunity for more than $300 million in additional development, commercialization and sales milestones for each future small molecule program. All right. So let me show you how we built this engine. To understand why this milestone matters, the question is why neuroscience. It's worth stepping back and asking that question. Neuroscience remains one of the greatest unmet needs in medicine. More than 3 billion people worldwide are affected by neurological diseases. And yet CNS drugs, as we know, continue to have amongst the lowest approval rates in industry. Neuroscience is particularly challenging because the biology is extraordinarily complex, difficult to model, and we have repeatedly returned to the same small set of well-understood targets with only incremental success. We believe meaningful progress will require discovering new biology, not just simply optimizing what is already known. And that's exactly what this collaboration was designed to do. So the next question comes, what does it actually take to discover a target that people will have confidence in? And before I go into the details, just a huge, huge thank you to Roche-Genentech for this deep shoulder-to-shoulder collaboration. It's one of the few rare ones that I've seen where the teams are looking at the same data, the same models, going through what validation needs to be done. So that joint collaboration is critical here. So everything starts with disease-relevant biology. We asked ourselves a simple question. What -- are we setting neurons in a context that actually reflects human disease? In our case, that meant creating iPSC-derived neuronal cells, both neuronal and microglial cells at an unprecedented scale, more than 1 trillion neurons and hundreds of billions of microglia. What this does is it creates a rich disease-relevant Atlas that can be reused again and again to discover multiple future targets. We view this Atlas as one of the most important long-term competitive advantages. But generating proprietary data, while important, isn't enough. The next challenge is making sense of it. Before asking the models to find something new, we grounded every analysis in causal biology that we understand today. So really grounding it in genetics. We introduced hundreds of disease-causing perturbations and anchored our searches around well-established drivers of neurological disease. That matters because it gives every subsequent prediction of biology from a causal target from the very beginning. Rather than switching blindly across the genome, we are searching from a foundation grounded in causal genetics and disease biology. Now as that's established, AI can help us on our foundation models ask a much more interesting question. What is not seen? What can be unexplored biology that we don't know of today. This is where our foundation models come in. Instead of evaluating one hypothesis at a time, the models compare the biological signatures of more than 17,000 genes across tens of millions of data points. They build relationships across the entire genome and identify genes that consistently behave like known disease drivers even if they have never been implicated in that disease before. That allows data and foundation models, not pre-conceived hypotheses to compile a prioritized list of new novel potential targets. Now AI can generate hypotheses, but medicines and programs require evidence. Together with Roche and Genentech, we predicted every target -- we looked at every predicted target and then put that through a rigorous experimental validation cascade. We built confidence in layers. First, we established that the target actually sits in the right biological pathway. Second, we show that changing the target actually can improve cellular function, for instance, neurons or microglia. And finally, very critical. We demonstrate that this target and modulating it can meaningfully affect disease-relevant biology using multiple orthogonal assays. These assays are very robust, but they also include other multi-omic data layers such as proteomics, transcriptomics, et cetera. While no single experiment tells the story, what we do here is build a body of causal evidence before advancing the target. So putting it all together, our collaboration combines 4 capabilities, generating disease-relevant biology at unprecedented scale and it's challenging to do to actually have a trillion iPSC-derived neuronal cells that are high quality, standardized, viable. It takes a lot of specialized protocols and know-how to do that. Second, we use foundation models to systematically explore that biology. Third, we navigate from well-understood disease mechanisms towards previously unexplored new biology. And finally, a very important step is validating all of these predictions experimentally before we advance it. So our first neuroscience target, as I mentioned before, have now advanced into a jointly developed small molecule discovery program supported by our design platform. And again, what excites us most is, of course, this target, but the fact that this kind of data is highly reusable, the potential to mine it over and over again for unexplored targets and also that this wasn't the result of one algorithm or one experiment. It's the result of a new operating model for discovering medicines. Before I hand it over to Vicki, I would like to highlight as we move on to our internal programs, the pipeline. As you can see here, we have multiple programs in the clinic. We're constantly looking at the data to make data-driven decisions for REC-4881 and FAP, where there's no approved therapies today and REC-1245 targeting RBM, a novel first-in-class target first-in-class degrader with limited clinical competition to-date. Combined with additional internal and partner assets, we believe this creates a diversified portfolio with multiple opportunities to create value in the coming years. With that, I'm going to turn it to Vicki to walk you through the internal pipeline in more detail. Vicki Goodman: Thank you, Najat. I'll start off this morning by talking about our REC-4881 program in FAP. FAP is a rare disease that requires lifelong management. Patients with FAP develop hundreds to thousands of adenomatous polyps in their GI tract and require colectomy to reduce the risk of colorectal cancer. Following colectomy, polyps may continue to develop and grow, both in the residual lower GI tract as well as in the duodenum in the upper GI tract. Patients require ongoing endoscopic surveillance, may require additional surgeries, and they continue to be at risk for GI cancers. With over 50,000 post-colectomy patients in the U.S. and EU5, there are no approved systemic therapies to alter the course of disease. This represents an over $10 billion potential addressable market. REC-4881 is an oral MEK1/2 inhibitor with a differentiated dual mechanism of action in FAP with the potential to inhibit both new polyp formation via cross-talk inhibition of the beta-catenin pathway as well as to directly interrupt signaling of the MAP-kinase pathway, which is a key signaling pathway in advanced disease. So again, blocking potentially both new polyp formation as well as the existing polyps within the GI tract. So with that, I'd like to take a minute to discuss the impact of this disease on patients through a story of a woman named Jenny, who lives with FAP. Like approximately 70% of FAP patients, Jenny inherited the genetic mutation responsible for FAP from a parent, in her case, her mother. Seeing what her mother experienced had profound psychological impacts on Jenny, who knew from the young age of 8 that she also carried this mutation. She has since had to endure multiple surgeries, which have led to chronic and life-altering complications, including frequent bowel movements, malabsorption and dehydration, chronic abdominal pain and anxiety with medical PTSD from all of the surgeries and procedures. We have heard from both patients like Jenny as well as their treating physicians an interest in a pharmaceutical intervention that can prevent polyp growth and disease progression and ultimately lead to a reduction in the need for repeat surgical procedures. REC-4881 has shown promising clinical data in the ongoing Phase II TUPELO study. Patients who had undergone colectomy for FAP receiving REC-4881 showed a median polyp burden reduction of 43% after 3 months of treatment. That treatment effect was durable with sustained reductions after 3 months off treatment. Additionally, reductions in polyp burden were seen in both duodenal disease in the upper GI tract as well as the lower GI tract. The upper GI tract in particular, is an area of high unmet need as approximately 90% of FAP patients will develop upper GI polyps. When removal of these upper GI polyps becomes necessary, the thin mucosal wall of the upper GI tract increases the likelihood of complications, including bleeding and perforation. REC-4881 has a manageable safety profile with predominantly mild to moderate adverse events, consistent with the safety profile of other MEK inhibitors. We continue to enroll patients on the Phase II TUPELO trial, including patients 18 years of age and older as well as a dose optimization cohort. We are pleased to share that additional REC-4881 data will be presented during the Presidential Plenary session at the CGA-IGC Conference in November. As Najat mentioned earlier, this conference is focused specifically on inherited GI cancer syndromes with a target audience, which includes physicians who treat FAP patients. We also look forward to providing an update on FDA discussions later this year. Now I'll move on to REC-7735. PI3-kinase is frequently mutated in several cancers and is a clinically validated therapeutic target. Lack of selectivity for the mutated form over the wild type is a key challenge for existing agents as inhibition of wild-type PI3-kinase drives hyperglycemia. Increases in blood glucose are both a safety issue, which often limits dosing and an efficacy issue as the resulting hyperinsulinemia can reactivate signaling through the PI3-kinase pathway, undercutting the efficacy of less selective drugs. REC-7735 is precision designed to be 100-fold selective -- greater than 100-fold selective for the H1047R mutation, which is the most frequent activating mutation in PI3-kinase. Recursion's AI-native platform identified a previously unpublished binding site and delivered a development candidate in 10 months with no identified off-target liabilities. As hyperglycemia and the resultant hyperinsulinemia are driven by inhibition of wild-type PI3K, the selectivity of REC-7735 is expected to result in an improved safety profile with respect to hyperglycemia and may allow expansion into patients such as diabetic and prediabetic patients who are unable to tolerate current PI3-kinase targeting options. An improved therapeutic index, as I have described, may allow us to expand treatable patient populations, both within existing PI3-kinase alpha inhibitor indications as well as in additional solid tumors in which PIK3CA mutations are prevalent including potentially triple-negative breast cancer, ovarian cancer and endometrial cancer, just to name a few. Additionally, the improved therapeutic index may allow expansions into earlier stages of disease within oncology as well as non-oncology populations such as PI3-kinase-driven vascular anomalies. With the IND now cleared by FDA, we intend to initiate the Phase I ZINNIA trial later this year. Dose escalation will begin in patients with PIK3CA-H1047R mutant solid tumors. Once tolerability is confirmed at an active dose, we intend to expand into the hyperglycemia vulnerable patient cohort to confirm the improved tolerability in this patient population. Dose optimization of 2 active and tolerated doses will then be performed in ER-positive HER2-negative breast cancer patients. We may also expand into additional tumor types based on emerging data. We expect to share the first data from this dose escalation part of the trial in the first half of 2028. And with that, I'll turn it back over to Najat. Najat Khan: Thanks, Vicki. And shifting gears a bit, we often get asked about whether advances in Frontier AI can reduce or increase Recursion's competitive advantage. We believe we have a truly competitive -- unique competitive edge. As reasoning models and agents continue to improve. Next slide, they become dramatically more powerful when paired with proprietary data, automated labs and real experimental feedback. That's exactly the system we've been building for years. Now we are deploying agents across biology, chemistry and clinical development across the engine and also alongside our scientists. In biology, here are some very quick examples. Our target discovery connector is helping patients -- is helping scientists interrogate our proprietary biological maps in hours rather than weeks. These are the large maps that we just talked about earlier in our partnership with Roche-Genentech, but also the internal maps that Recursion has built over years, accelerating the discovery of novel targets. In chemistry, our design agent reasons across structure, SAR and experimental data to prioritize the next design hypothesis, critical inflection points in programs. This helps our scientists decide what to make next and compress design cycles from roughly 4 hours of structural analysis to about 30 minutes. And in clinical development, the Agentic workflows are already improving patient enrollment, contributing to about 1.3 to 1.6-fold improvement over historical benchmarks. That's significant. These are still early examples, but I will have Chris Radoux, our Director of Structure-based Technology, who is in this day in and day out, walk you through a real example in practice. Chris? [Presentation] Najat Khan: What you just saw wasn't a chatbot answering a question. It was an AI agent reasoning across our proprietary experimental data, our in silico data, our historical project knowledge and structural biology to surface insights that would otherwise require scientists long time, but then also nonobvious insights. That's because in drug discovery, the bottleneck is really just generating ideas. It's finding the right idea quickly enough to keep the make, test, learn cycle moving. As these agents continue to improve alongside Frontier models, we believe they will become an incredibly powerful multiplier of what we have already built. And finally, I'd like to highlight another aspect of our AI strategy. AI is advancing incredibly quickly, and no single model will remain state of art forever. Our strategy isn't to depend on any one model. It's to build an AI-native product engine that can rapidly develop and adopt the best advances, whether they're developed at Recursion or by the broader Open Source community. Nesso-1 is a great example. We developed an open source this model. This is a binding affinity model that delivers Boltz-2 level accuracy with 10 to 20x faster inference, helping advance the field while enabling dramatically faster design cycles. But look, the real advantage is in the model itself. It's our operating system. It's our operating model. It's our ability to rapidly integrate these models into our proprietary data. That increases prediction performance, accelerates the make, test, learn loop and allows us to evaluate many more compounds at a lower cost. And finally, great technology only creates value if you have the right people to translate it into medicine. We firmly believe that. And that's why we have strengthened our leadership team in 2 critical areas. First, Dr. Hoifung Poon joins us as Chief AI Officer. Hoifung is one of the world's leading AI researchers with more than 15 years at Microsoft Research, where he led pioneering work in biomedical foundation models and AI for health care. Importantly, though, he's not just a researcher. He has repeatedly translated Frontier AI into real-world applications and deployed that at scale. At Recursion, he will unify our end-to-end AI strategy, bringing together Frontier research and Applied AI across biology, chemistry and the clinic. Second, Dr. Donovan Chin joins us to head up drug design. Donovan has spent more than 2 decades solving some of the hardest problems in drug discovery from small molecules and RNA-targeted therapeutics to proximity-based medicines and peptide modalities. Across Parabilis, Arrakis, and Novartis, he repeatedly helps unlock targets that were previously considered difficult or even impossible to drug. That breadth across modalities and that depth and experience of translating computational design into medicines is exactly the kind of capability we need to continue building at Recursion. Together, Hoifung and Donovan strengthened the 2 engines that will continue to define our future, world-class AI and world-class scientific design. Now I'm going to turn it over to Ben to give us a financial update. Ben Taylor: Thank you, Najat. As I've said in the past, we want to continuously increase the impact of every dollar we spend. We are demonstrating this today by lowering our 2026 full year cash operating expense guidance to $375 million. In total, our revised 2026 guidance represents a nearly 40% reduction from comparable 2024 pro forma expenses. Through disciplined data-driven management, we have been able to continue lowering OpEx while still advancing our differentiated internal pipeline, achieving a series of partnership milestones and maintaining a leadership position in AI-powered drug discovery. We have been able to increase our return on investment through multiple levers across the company. In our clinical pipeline, we use our Cleantech platform to drive more efficient enrollment and planning of our clinical trials, reducing the time and cost to reach important data. Najat and Chris described some of the systems that we use to make our internal discovery both more efficient and more effective. We also focus our technologies on predicting and answering the hard questions first so that we can prioritize those programs with clear potential clinical and commercial differentiation as early as possible. Because we deliver outcomes that are truly novel and differentiated, like our Roche-Genentech milestone today, our partnerships have achieved over $500 million in cash inflows, including more than a dozen successful discovery milestones. All of our partnerships are designed to be breakeven or profitable on a direct cost basis from the start with substantial value growth as we achieve milestones. In our product engine, we are able to build, test and integrate AI models on real projects using the scale of our internal pipeline and partnerships. We know not only if the model benchmarks well, but if it matters when it's applied to a drug program. This direct application allows us to determine early which technology investments are likely to have real-world impact. We apply the same disciplined management style to our corporate operations. We have been able to maintain G&A at a relatively low percentage of total cost, which helps us maximize the scientific ROI of every dollar we spend. We ended the quarter with approximately $557 million in cash and equivalents, which we believe provides us with an operating runway through early 2028. And with that, I'll turn it back over to Najat. Najat Khan: Thanks, Ben. I'll close by looking ahead. We have built an AI-native product engine. Now the focus is expanding its impact while continuing to translate its capabilities into the right programs and repeatable proof points. So on our wholly-owned portfolio, you should expect to see continued progress across multiple programs, additional Phase II data for REC-4881and a regulatory update before year-end, continued advancement of REC-1245 with a more wholesome update later this year, the initiation of REC-7735, that Vicki just mentioned, and progress across the broader pipeline. We are on track across those multiple fronts. With our partners, we expect to build on this year's momentum. Following the advancement of the first previously unexplored neuroscience target with Genentech, we see the potential for additional programs to emerge from our [ maps ]. And with Sanofi, we expect the potential to continue the progression of AI designed molecules towards development candidates and later-stage milestones. We're entering an exciting period with multiple opportunities to demonstrate the power of our engine. With that, thank you again for the time today, and I'd be happy to take your questions. Najat Khan: Great. So I'm just going to go through some of the questions. The first question coming from Alec from BofA and Sean from Morgan Stanley. How does the collaboration with Roche-Genentech form a template for how you can leverage your platform with other partners? Maybe 2 to 3 aspects that you think are transferable and provide proof points. Yes. I mean it's a great question. Thank you, both. Big picture, the way we develop our novel data sets for creating novel maps, and then we take those novel targets and design compounds all the way into the clinic, that sort of Lab-in-the-Loop is something we use for both our internal programs and for our partner programs. So that template is something that will only get better and faster as we go on and we can -- in terms of new partners or current partners, we will continue to scale that. As I mentioned before, our differentiation really lies in 3 areas. One is that data factory. I mean, especially in biology, given so much of it is not known well, having access to great biology and data is incredibly important. And that takes years to build. I want to emphasize that, understanding how to generate that data, validate that data, develop the models and also have a supercomputer, which we have in a hidden location in Salt Lake City, having that entire stack to make sense of that data back into the lab and validated. I think that is something we are one of the very few companies that can do that, and we continue to drive momentum there. Next question. Can you provide -- and this is a question from Sean from Morgan Stanley, Gil from Needham and Brendan from Cowen. Can you provide an update on FDA engagement on REC-4881 in FAP, the registrational pathway and the data coming up at CGA-IGC? Vicki, do you want to start it? Vicki Goodman: Sure. I'd be happy to. Maybe I'll start with the upcoming data at CGA-IGC. So we presented data from the Phase II TUPELO trial for the first time back in December of last year via a webinar. We do think it's really important to put these data in front of the physicians who treat patients with FAP. And so this will be an updated data set, again, presented in an oral presentation at the Presidential Plenary session at that meeting, which occurs in November where you may see additional analyses that help contextualize the clinical relevance of the data as well as potentially additional patients in that analysis as well. So we look forward to sharing those details with the FAP treating community later this year. With respect to the FDA engagement, as we've said, these are ongoing. I think it's important to remember, there's very limited regulatory precedent in FAP. And so our engagement here really is around making sure that we derisk the study design from a regulatory standpoint, including things like what is the appropriate primary endpoint to demonstrate clinical benefit. And I would say, as somebody who worked at FDA many years ago, those discussions, those conversations have been productive and I think are helping us get to a better point in terms of the study design. So nothing out of the ordinary there. Again, this is just a rare disease with limited precedent, and we continue to have a productive dialogue with FDA and look forward to sharing -- once we have sort of something more concrete to share, look forward to sharing more details on that later this year. Najat Khan: Thank you, Vicki. All right. I'll move on to the next question. Ben, this is for you from Priyanka, JPM and Gil from Needham. Can you provide more color on what operating efficiencies were done to reduce the OpEx guidance? Is there potential for further belt tightening on OpEx in second half of 2026? Ben Taylor: Yes. Great question. And I think as you saw in the presentation Najat covered, we haven't changed any of our full year guidance on what outcomes we're trying to achieve over the course of the year. And I think that's really important to remember because this reduction in guidance is actually from doing the same amount or more with less. And so what we've really tried to focus on is how can we get to the most important answer first. You heard some of the description of the technologies that Chris took us through that Najat took us through. And that really makes a difference on how we can operate and how we can deliver those outcomes. So I think we started the year and we had some ideas of where we could go. What we've seen is they actually have impact. We are actually getting to the answers faster and more cheaply. I think the numbers that everyone should use are the numbers that we give in guidance, which is the $375 million. That is our expectation of where we will be operating. But at our core, we are always looking for a better and faster way to do everything that we do. We are a technology company, and we should be getting more and more efficient over time. So we will keep looking and update you as we know more. Thanks, Ben. Yes. And just to maybe reiterate that, we have -- we always have a commitment in order to ensure that every dollar goes further with some of the improvements we're seeing in our engine. You saw some of the examples around the fact that we design 90%. We make -- physically make 90% less compounds for the one that goes into the clinic. We took about 1.5 years versus 4 years versus industry. Those are meaningful improvements in the velocity that we see in our engine, and we ensure that, that actually parlays into our spend. We mentioned earlier this year that we changed our budget to an outcomes-based budget so that every single aspect like Alec and Sean going back to your question, when we do a partnership, we know exactly the fully loaded cost of building a map of a program and so forth. And that really helps us to ensure that those efficiencies are realized. The other thing I'll also say, we continue to focus on our G&A and ensure that every single dollar is actually going to our programs and our partnerships. So we will continue to put pressure. That's our commitment, just like our commitment is to deliver on proof points from what can be really a value inflection point for the broader community in terms of programs and the use of AI to create value. Najat Khan: Okay. With that, I'll go to the next question, a platform question from Alec from BofA and many others, okay. With multiple tech companies entering drug development and as Generative AI becomes increasingly available, how does Recursion differentiate itself today and in the future? And what do you believe remains Recursion's durable competitive advantage competitors will find hardest to replicate over the next 5 years? Great question, Alec, and everyone else who asked that. I think that's why you saw the second slide in the presentation was really around our durable moat and our differentiation, and that evolves over time. I think number one is the data factory. Look, you just said Generative AI is becoming increasingly available, maybe some would say even commoditized. Where does the differentiation come from? If 80%, 90% of biology, as I've known, it has to come from high-quality data generation. Models depend on good quality data to be trained on. And you saw with the example with Roche-Genentech that we shared today, but also across the board, starting with disease-relevant data sets also matters. That just doesn't exist. So in order to build that 1 trillion iPSC-derived neuronal cells, that's a cell manufacturing capacity that we have in our Salt Lake City Labs. Over years, we have gone through the pain and suffering of what works and what doesn't work. So think about it as a really mature and increasingly validated capability. So that's one on the data factory. And that's not just for biology. You heard from Chris Radoux, 10 years of actually doing small molecule design, millions to billions of virtual cells -- virtual molecules that have been generated also gives us a lot of rich data, not just in areas that are known to the world like kinases, but actually other targets that are less known and not as available in the protein database, PDB, for instance, and others. So that's one big pillar. Second, I can't emphasize enough is that Lab-in-the-Loop, that operating model because it's one thing to have great data. It's another thing to have great models. But really important, we need to validate these predictions. The only way we get this to be useful, utility at the end of the day to make a drug is if you're validating it back into the lab and that feedback, good or bad goes back into the models to make them better and smarter. We do the same thing with AI agents. The more you engage with them, the more you give them feedback, they get better. I think that integrated Lab-in-the-Loop is [indiscernible]. It's hard to build for 2 reasons. It takes a lot of technical expertise, yes. It takes a lot of years of knowing what works, what doesn't works, yes. It takes tons of reps and with partners that are some of the best in the industry, we learn faster. But so much of it is also culture. It's culture. I've always mentioned the piece that we have bilingual scientists that understand -- better understand, I would say, both science and tech that have appreciation of the challenges and opportunities of both, that open-mindedness where an agent gives you a different hypothesis from what you started, when you're in medicinal chemistry that's worked in that space for decades, that takes a different mindset, and I cannot emphasize that enough. And then the third piece is what are we actually making from the agent? FAP, first-in-class oral for a disease where nothing has been approved. It's a stand-alone high-value asset. RBM39, first-in-class target, first-in-class degrader built from this platform with limited competition. So what you'll see in our pipeline is an incremental improvement but any 1 or 2 drugs that can actually be a stand-alone differentiated asset in its own right. And we all know that takes time. So I think those are the 3 big areas that are not just an advantage for today, but continues because with every week, we're doing 2 more -- 2 million more experiments in our labs, the data moat grows. With every week, we actually have people turning through that lab and learning, that grows. And as you can see, with every week, month, we're making progress in our pipeline. And that takes time, resilience, focus and discipline, and that's what we're doing. Okay. One more question for Vicki. PI3K questions from Brendan at Cowen and Dennis at Jefferies. Looks like REC-7735 passed your internal criteria for go/no-go decision with the Phase I to start for second half of 2026. Can you tell us a bit more about the go/no-go process? What it is about the preclinical profile that gives you confidence that this is the right candidate? And also, what the Recursion AI platform has told you about the best development path forward in terms of study design, patient selection, et cetera? And then there's another sub-question, but I'll start with that. Vicki Goodman: Sure. So first, maybe to start off by saying we believe that there's room for improvement in the PI3-kinase space. So again, this is a very common mutation in certain malignancies, including hormone receptor positive breast cancer, but also extending beyond breast cancer into other GYN malignancies as well as head and neck cancer and colon cancer and others. So important target still remaining unmet need in terms of maximizing the therapeutic index and ultimately, the efficacy that patients see. So the go/no-go process really involved a rigorous evaluation and confidence building in our preclinical data set. So the selectivity that allows us to hit the target hard without seeing additional toxicity. So again, both in terms of the efficacy that we're seeing in preclinical models that look similar to -- at least similar, if not improved upon competitor profiles, the safety profile, including the lack of hyperglycemia, but also, of course, our GLP tox studies. These all helped us build confidence that this was the right molecule to move forward with into clinical trials. Of course, ultimately, after evaluating these data, we made the decision to go forward. We've submitted the IND and that IND is now cleared, and we look forward again to initiating that study this year. In terms of the AI platform, I think one of the key pieces from a clinical perspective is these patients are going to be selected based on the H1047R mutation, so a biomarker, which will require a diagnostic. And one of the key areas where I think the platform is helping us is in terms of our ability to find these patients, look for the right geographies and sites in which to conduct our clinical trial and help us accelerate the development -- sorry, the enrollment of this patient population. Najat Khan: Thank you, Vicki. Maybe just a couple of things to add. We talked about this early on, which is for this compound specifically, it is over 100x in activity of wild-type. So it's wild-type sparing. Why is that important? Important from a perspective of can we actually have the patients stay on increased dose intensity, dose duration, as Vicki mentioned, to really try to improve the outcomes from patients in the [ TI ]. But also even with grade 1/2 increase in -- for instance hyperglycemia, et cetera, we have seen elements that it can lead to reactivating the exact pathway, PI3K pathway that you're trying to suppress. And that has the potential for also compromising some of the efficacy that can be seen. So there are multiple elements to why as we look at this compound, what we want to test in the clinic is, is it actually giving us a better safety profile and in turn, can it give us a better efficacy profile that would improve the therapeutic index. The other thing I would just say from the AI platform as well as Vicki mentioned, one is recruitment. We know this is a competitive area. We're starting in with solid tumors, as Vicki mentioned, but it gives us optionality given based on what we will see in the profile to either go in onc or non-onc indications as well. And that's also another area where the platform can help. We're really thinking about what are the right patient groups and indications that we might select that others haven't maybe explored to-date. So a lot more work to come, but step one is to go into the clinic and ensure that we are seeing the elements, the compound was really designed for. And recall, the compound was designed in 10 months, 242 compounds synthesized, 13 cycles and the pocket was a previously unpublished pocket. So we're not going after the same areas, which is why you see almost 130x selectivity over wild-type, super precise, super precision based. H1047R is the most -- one of the most frequent mutations you see in this space, one of the ones that's tied to disease causality and progression the most. So we're excited. But again, it's part of multiple different programs that we're looking at. And based on data, we'll make the right go/no-go decisions as well. One maybe just sub-question. When should we expect initial monotherapy data? I think Vicki had mentioned first half of 2028. So stay tuned. And with that, I'm not seeing any more questions on the screen. Thank you again so much for joining us today. Looking forward to the progress over the next set of weeks and months. And as always, we'll talk to you soon. Before you buy stock in Recursion Pharmaceuticals, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Recursion Pharmaceuticals wasn’t one of them. The 10 stocks that made the cut are built for long-term growth and could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $403,337!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $1,334,946!* That performance is why people listen. With a track record of beating the S&P 500 by 4x, Stock Advisor offers a distinct advantage. Don't miss the latest top 10 list, available with Stock Advisor, and join an investing community built for the long haul. See the 10 stocks » *Stock Advisor returns as of August 12, 2026. This article is a transcript of this conference call produced for The Motley Fool. While we strive for our Foolish Best, there may be errors, omissions, or inaccuracies in this transcript. As with all our articles, The Motley Fool does not assume any responsibility for your use of this content, and we strongly encourage you to do your own research, including listening to the call yourself and reading the company's SEC filings. Please see our Terms and Conditions for additional details, including our Obligatory Capitalized Disclaimers of Liability. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a disclosure policy. Recursion (RXRX) Q2 2026 Earnings Call Transcript was originally published by The Motley Fool

Recursion Pharmaceuticals, Inc. reported its Q2 2026 results, with revenue falling to US$7.67 million from US$19.22 million a year earlier, while its net loss narrowed to US$131.01 million and loss per share improved to US$0.25. Alongside these figures, the company highlighted progress on its AI-enabled drug discovery platform, including Genentech advancing a neuroscience target into joint early discovery and updates on REC-4881 Phase 2 data and the upcoming REC-7735 clinical trial. With these earnings and Genentech’s neuroscience program advancement now public, we’ll examine how they reshape Recursion’s AI-driven investment narrative. Uncover the next big thing with 20 elite penny stocks that balance risk and reward. To own Recursion, you need to believe its AI-enabled platform can turn heavy R&D spending and deep pharma partnerships into drug assets that matter, before the cash runway runs out. This quarter’s sharp revenue drop to US$7.67 million but narrower net loss of US$131.01 million does not materially change the near term catalyst focus on clinical data readouts and partnership progress, while reinforcing the ongoing risk around cash burn and funding. Among the recent updates, Genentech advancing the first collaboration neuroscience target into a joint early discovery program is most relevant here, because it directly tests whether Recursion’s AI-native approach can consistently generate targets that partners choose to move forward. Alongside upcoming clinical milestones like REC-4881 Phase 2 data and the REC-7735 trial start, this kind of partner progression sits at the heart of the company’s near term proof points. Yet beneath this platform progress, investors should also be aware of the risk that persistent cash burn and a runway only through Q4 2027 could... Read the full narrative on Recursion Pharmaceuticals (it's free!) Recursion Pharmaceuticals' narrative projects $220.9 million revenue and $35.5 million earnings by 2028. Uncover how Recursion Pharmaceuticals' forecasts yield a $7.00 fair value, a 111% upside to its current price. Before this earnings miss, the most pessimistic analysts were already modeling revenue shrinking about 29.5% a year and ongoing losses, a far harsher view than the catalyst driven story you just read about, and one that may shift again as this quarter’s numbers and the Genentech update feed into new expectations. Explore 7 other fair value estimates on Recursion Pharmaceuticals - why the stock might be worth 40% less than the current price! Don't just follow the ticker - dig into the data and build a conviction that's truly your own. A great starting point for your Recursion Pharmaceuticals research is our analysis highlighting 2 key rewards and 2 important warning signs that could impact your investment decision. Our free Recursion Pharmaceuticals research report provides a comprehensive fundamental analysis summarized in a single visual - the Snowflake - making it easy to evaluate Recursion Pharmaceuticals' overall financial health at a glance. Right now could be the best entry point. These picks are fresh from our daily scans. Don't delay: Capitalize on the AI infrastructure supercycle with our selection of the 55 best 'picks and shovels' of the AI gold rush converting record-breaking demand into massive cash flow. Find 52 companies with promising cash flow potential yet trading below their fair value. AI is about to change healthcare. These 41 stocks are working on everything from early diagnostics to drug discovery. The best part - they are all under $10b in market cap - there's still time to get in early. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Companies discussed in this article include RXRX. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email [email protected]

Genentech advanced the collaboration's first neuroscience target into a joint early discovery program, providing early evidence that Recursion's platform can generate novel, biologically validated targets for drug discovery REC-4881 (MEK1/2 inhibitor): Additional Phase 2 data in Familial Adenomatous Polyposis (FAP) to be presented at the Presidential Plenary session at leading hereditary GI annual meeting in November 2026 REC-7735 (PI3Kα H1047R inhibitor): IND cleared, Phase 1/2 trial start in 2H26; a >100× mutant-selective PI3Kα H1047R inhibitor designed to improve therapeutic index by enabling deep suppression of the most common activating PI3Kα mutation while sparing wild-type PI3Kα Reduced 2026 cash operating expense guidance to SALT LAKE CITY, Aug. 05, 2026 (GLOBE NEWSWIRE) -- Recursion (Nasdaq: RXRX) a leading clinical stage TechBio company decoding biology to radically improve lives, today reported business updates highlighting strong continued pipeline execution, clinical progress and platform advancement, as well as financial results for its second quarter ended June 30, 2026. Recursion will host an Earnings Call on August 5, 2026 at 8:00 am ET / 6:00 am MT / 1:00 pm BST from Recursion’s X, LinkedIn, and YouTube accounts giving analysts, investors, and the public the opportunity to ask questions of the Company by submitting questions here: Question Form. "Recursion has reached a pivotal point where our AI-native platform is translating unique data into potential first-in-class therapeutic opportunities," said Najat Khan, Ph.D., Chief Executive Officer of Recursion. "The advancement of the first unexplored neuroscience target from our collaboration with Roche and Genentech into an early discovery program is an important proof point. Finding new targets in neuroscience has historically been challenging, and this milestone highlights our ability to uncover novel biology in areas where conventional approaches have struggled. We believe that combining disease-relevant data at scale, foundation models, an end-to-end learning system, and deep scientific collaboration can uncover new biology in ways that were not previously possible." Business Highlights Genentech Advances First Neuroscience Target into Early Discovery Program Genentech has exercised the first Validated Target Option under the companies' neuroscience collaboration, advancing a previously unexplored neuroscience target into a small molecule early discovery program. The milestone provides additional early evidence that Recursion's AI-native platform can both discover and play a key role experimentally validating novel therapeutic targets in neuroscience, one of medicine's most challenging therapeutic areas, where decades of research have largely focused on a limited number of well-studied targets. In partnership with Roche and Genentech, Recursion built the first whole-genome CRISPR knockout map generated from a subset of over 1 trillion internally manufactured iPSC-derived neuronal cells. Predictions generated from the Maps were experimentally evaluated through a rigorous validation process developed jointly with Genentech. Candidate targets advanced through successive stages of pathway validation, functional validation, and disease validation to determine whether modulating the target altered neurological disease phenotype. Only targets that consistently demonstrated compelling evidence across each stage advanced into a validation package. To learn more about how we collaborated to build disease-relevant whole genome maps of biology, see our blog here Next steps will include advancing the target through small molecule design, hit generation and validation using Recursion's AI-native chemistry platform. More broadly, the neuronal and microglial maps of biology remain reusable assets capable of being utilized with biological, genetics, and computational expertise to generate and experimentally validate additional therapeutic hypotheses. To date, Recursion has achieved $216 million in upfront and milestones payments from the Roche and Genentech collaboration. The collaboration includes up to 40 potential small molecule discovery programs, each carrying the potential for more than $300 million in development, commercialization, and net sales milestones as well as tiered royalties up to high single digits per small molecule program for Recursion. Advancing joint portfolio with Sanofi across I&I and oncology Recursion, in collaboration with Sanofi, made significant progress toward development candidate milestones over the past 12 months. Recursion and Sanofi are advancing a joint portfolio of differentiated molecules for challenging targets in I&I and oncology. To date, Recursion has achieved $134 million in upfront and milestone payments from the Sanofi collaboration and has the potential for $343 million in milestone payments per program plus tiered double digit royalties. Potential upcoming milestones across partnered discovery: Potential for differentiated AI-enabled oral molecules to reach development candidate and late-stage discovery milestones with Sanofi over the next 6-12 months Translating AI-driven insights from maps of biology into new potentially novel targets from reusable high-dimensional data/maps Using Recursion’s Chemistry Platform to design a potential first-in-class molecule​ for the collaboration's neuroscience target announced today with Genentech Continuing to combine our phenomics dataset with Genentech’s proprietary transcriptomics data to build multi-modal maps designed to explore potential novel targets and pathways by systematically linking gene perturbations to cellular phenotypes Internal Pipeline Updates Continued Momentum for REC-4881 (MEK1/2): REC-4881, Recursion’s MEK1/2 inhibitor, is a potential first-in-class drug designed to address both known drivers of FAP polyp growth: the Wnt/β-catenin initiation pathway and the MAPK evolution pathway. This dual mechanism differentiates REC-4881 from other investigational FAP therapies, which to date have targeted only a single pathway. REC-4881 is being developed for FAP, an orphan disease affecting an estimated >50,000 diagnosed patients across the US and EU5, representing a >$10 billion total addressable market opportunity. FAP is a serious, lifelong chronic disease with no approved medicines today. REC-4881 has received both Orphan Drug Designation and Fast Track Designation from the US FDA. REC-4881 has demonstrated meaningful activity across the GI tract, including the Upper GI, an area of particularly high unmet need. Key updates: Discussions with FDA were initiated in 1H26 and an update to define the registrational path is expected in 2H26 TUPELO now enrolling patients ages 18 and older, as well as a cohort with an alternative dosing schedule Additional Phase 2 safety and efficacy data from the TUPELO clinical trial contextualized with real world data will be presented at the Collaborative Group of the Americas on Inherited Gastrointestinal Cancer (CGA-IGC) Annual Meeting in November. CGA-IGC is a leading annual meeting dedicated specifically to hereditary GI cancer syndromes including FAP. Phase 1/2 Trial Initiation for REC-7735 expected in 2H26: REC-7735, Recursion’s AI-designed PI3Kα H1047R inhibitor, was built to improve therapeutic index for a validated oncology target REC-7735 was precision designed to show >100-fold selectivity for the H1047R mutant over wild type in order to drive high, sustained target inhibition while avoiding hyperinsulinemia-driven reactivation The differentiated development candidate was delivered in 10 months and 242 compounds from first novel hit through Recursion’s AI-native design platform, demonstrating the Company’s ability to rapidly translate platform insights into optimized clinical candidates With the IND cleared, the Phase 1/2 ZINNIA clinical study for patients with select PIK3CA H1047R-mutant solid tumors ​will be initiated in the second half of 2026 For the rest of the portfolio, programs continue to progress as planned. Additional expected upcoming milestones across Recursion’s internal pipeline: REC-1245 (RBM39): Additional Phase 1 dose escalation data expected in 2H26 REC-617 (CDK7): Early Phase 1 safety and PK combination data expected in 1H27 REC-3565 (MALT1): Early Phase 1 safety and PK monotherapy data expected in 1H27 REC-4539 (LSD1): Early Phase 1 safety and PK monotherapy data expected in 2H27 Agentic AI is compounding Recursion's advantage across Biology, Design, and ClinTech: Target Discovery Agent pairs frontier AI reasoning with Recursion's proprietary multimodal maps to surface novel drug targets, enabling scientists to mine and extract insights from proprietary maps in hours rather than weeks. Drug Design Agents reason across Recursion's full set of structure-activity relationship (SAR) and structural data to identify what to solve next and how, with structural analysis time reduced from 4 hours to 30 minutes and agent-generated hypotheses now driving design cycles in active programs. Clinical Strategy Orchestration Agent coordinates patient, site, operational, CMC, and biometrics data to inform clinical development decisions, with agent-supported enrollment strategies contributing to a 1.3 to 1.6x increase in enrollment rates versus historical benchmarks. Continuing to strengthen our leadership team: Hoifung Poon, Ph.D., appointed Chief AI Officer: Poon brings more than 15 years of experience at Microsoft, where he led groundbreaking work in biomedical AI, including foundation models in digital pathology and spatial omics published in Nature and Cell. His open-weight models have been downloaded tens of millions of times and deployed at major health systems. Donovan Chin, Ph.D., appointed Senior Vice President, Drug Design: Chin brings more than 20 years of experience spanning small molecules, RNA-targeted therapeutics, proximity approaches and novel peptide modalities. At Parabilis Medicines, he led the AI and physics-based computational drug discovery strategy behind Helicons, a novel class of constrained ⍺-helical peptides. Earlier, at Arrakis Therapeutics, he pioneered computational approaches for RNA-targeted drug discovery, unlocking small-molecule engagement of previously inaccessible RNA structures. Second Quarter 2026 Financial Results Cash Position: Cash, cash equivalents and restricted cash were $556.8 million as of June 30, 2026 compared to $753.9 million as of December 31, 2025. Based on current operating plans with no additional financing, the Company continues to expect its cash runway to extend into early 2028. Revenue: Total revenue, consisting primarily of revenue from collaboration agreements, was $7.7 million for the second quarter of 2026, compared to $19.2 million for the second quarter of 2025. Roche and Genentech revenue recognized was less in the current period due to the successful completion of certain project phases in the prior period. Research and Development Expenses: Research and development expenses decreased to $89.6 million for the second quarter of 2026, from $128.6 million for the second quarter of 2025. The decrease was primarily due to lower platform costs resulting from the timing of Tempus record purchases as well as lower costs due to improved operating efficiency. Specifically, the second quarter of 2025 included $22.7 million in non-cash expenses for the use of Tempus’ patient-centric multimodal oncology data within the Company’s R&D pipeline, compared to $3.1 million in the second quarter of 2026. General and Administrative Expenses: General and administrative expenses were $41.5 million for the second quarter of 2026 compared to $46.7 million for the second quarter of 2025. The decrease of $5.1 million compared to the prior period was primarily driven by a decrease in salaries of $4.9 million as a result of headcount reductions in the year. Net Loss: Net loss was $131.0 million for the second quarter of 2026, compared to a net loss of $171.9 million for the second quarter of 2025. Operational Cash Flows: Net cash used in operating activities was $105.9 million for the three months ended June 30, 2026, compared to net cash used in operating activities of $76.4 million for the three months ended June 30, 2025. The increase in cash used in operating activities was primarily driven by working capital movements, during the three months ended June 30, 2025, the Company received a $28.6 million inflow related to a UK R&D tax credit. Cash Operating Expense: Cash operating expense, excluding partnership inflows and transaction costs, for the six months ended June 30, 2026 was $191.0 million compared to $199.1 million for the six months ended June 30, 2025. The Company is lowering its cash operating expense guidance for the full year 2026 by $15 million to $375 million based on additional identified operating efficiencies. About RecursionRecursion (NASDAQ: RXRX) is a clinical stage TechBio company decoding biology to radically improve lives. Recursion is advancing a portfolio of differentiated investigational medicines across its wholly owned and partnered pipeline in oncology, rare disease, neuroscience, immunology, and other therapeutic areas with significant unmet need. Enabling its mission is the Recursion OS, an AI-native, end-to-end drug discovery and development platform integrating biology, chemistry, and clinical development into a unified intelligence system. Powered by proprietary multimodal data, purpose-built AI models, and bilingual teams fluent in both science and AI, the Recursion OS is designed to translate complex science into medicines that matter — faster, better, and at scale — for patients who are waiting. Recursion’s platform infrastructure is anchored in Salt Lake City, Utah and Milton Park, Oxfordshire, where its automated biology and chemistry laboratories generate proprietary data at industrial scale. Recursion also maintains offices in New York, Montréal, and London, three global hubs for talent and leadership at the intersection of AI and scientific innovation. Learn more at www.recursion.com, or connect on X and LinkedIn. Media [email protected] Investor [email protected] Non-GAAP Financial Measure The reconciliation of operating cash expense to net cash used in operating activities is provided in the following tables: *This is from the Recursion Inc Consolidated Statement of Cash Flows for the six months ended June 30, 2026 (see above) *This is from the Recursion Inc Consolidated Statement of Cash Flows for the six months ended June 30, 2025 (see above) To supplement our financial statements prepared in accordance with U.S. GAAP, we monitor and consider operating cash expense, which is a non-GAAP financial measure. We define operating cash expense as the net cash used in operating activities, excluding non-ordinary course transaction costs and partnership cash inflows. This non-GAAP financial measure is not based on any standardized methodology prescribed by U.S. GAAP and is not necessarily comparable to similarly-titled measures presented by other companies. We believe operating cash expense to be a liquidity measure that provides useful information to management and investors about the amount of cash consumed by the operations of the business. A limitation of using this non-U.S. GAAP measure is that operating cash expense does not represent the total change in cash and cash equivalents for the period because it excludes cash provided by or used for other investing and financing activities. We account for this limitation by providing information about our capital expenditures and other investing and financing activities in the statements of cash flows in our financial statements. Additionally, we reconciled operating cash expense above to net cash used in operating activities, the most directly comparable U.S. GAAP financial measure. In addition, it is important to note that other companies, including companies in our industry, may not use operating cash expense, may calculate operating cash expense in a different manner than we do or may use other financial measures to evaluate their performance, all of which could reduce the usefulness of operating cash expense as a comparative measure. Because of these limitations, operating cash expense should not be considered in isolation from, or as a substitute for, financial information prepared in accordance with U.S. GAAP. Forward-Looking Statements This document contains information that includes or is based upon “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995, including, without limitation, those regarding the occurrence or realization of potential milestones; the timing of data readouts and other milestones; the impact of Genentech’s option of the neuroscience target on future development of that or other potential targets; the impact of preclinical data from our programs on the future success of those programs or trials; the timing and outcome of anticipated engagement with the FDA, including the definition of a registrational path for REC-4881; financial position, cash runway, cash burn, and cash operating expense guidance; Recursion’s ability to translate platform insights into validated targets and optimized development candidates; the reusability of our maps of biology and the potential to generate and experimentally validate additional therapeutic hypotheses, including through multi-modal maps combining our phenomics data with partner-provided data; Recursion’s future as a leader in TechBio and ability to deliver better treatments to patients faster; expectations relating to early and late stage discovery, preclinical, and clinical programs, including timelines for commencement of and enrollment in studies, data readouts, meetings with regulators, and progression toward IND-enabling studies; expectations and developments with respect to licenses and collaborations, including option exercises by partners and the amount and timing of potential milestone payments, and the acceleration of progress across multiple partnered programs; prospective products and their potential future indications, differentiated profiles, and market opportunities, including estimates of diagnosed patient populations and total addressable market, and the potential for REC-7735 to limit metabolic liabilities relative to legacy inhibitors and to expand the treatable population through an improved therapeutic index; developments with Recursion OS, including the ability to discover and develop new medicines; the anticipated benefits of our agentic AI tools, including expected improvements in scientific productivity, design and analysis cycle times, and clinical trial enrollment rates; and all other statements that are not historical facts. Forward-looking statements may or may not include identifying words such as “plan,” “will,” “may,” “could,” “should,” “expect,” “anticipate,” “intend,” “believe,” “estimate,” “project,” “designed to,” “potential,” “continue,” and similar terms. These statements are subject to known or unknown risks and uncertainties that could cause actual results to differ materially from those expressed or implied in such statements, including but not limited to: challenges inherent in pharmaceutical research and development, including the timing and results of preclinical and clinical programs, where the risk of failure is high and failure can occur at any stage prior to or after regulatory approval due to lack of sufficient efficacy, safety considerations, or other factors; our ability to leverage and enhance our drug discovery platform; the performance and limitations of our artificial intelligence and machine learning models and the data on which they are trained; our reliance on third parties, including collaborators, contract research organizations, and manufacturers; our ability to initiate clinical trials and enroll patients on expected timelines; competition from other therapies and platforms; our ability to obtain financing for development activities and other corporate purposes; the success of our collaboration activities and our collaborators’ discretion over option exercises, program advancement, and funding; our ability to obtain regulatory approval of, and ultimately commercialize, drug candidates; our ability to obtain, maintain, and enforce intellectual property protections; cyberattacks or other disruptions to our technology systems; our ability to attract, motivate, and retain key employees and manage our growth; inflation and other macroeconomic issues; and other risks and uncertainties such as those described under the heading “Risk Factors” in our filings with the U.S. Securities and Exchange Commission, including our Annual Report on Form 10-K and our subsequent Quarterly Reports on Form 10-Q. All forward-looking statements speak only as of the date of this document and are based on management’s current estimates, projections, and assumptions, and Recursion undertakes no obligation to correct or update any such statements, whether as a result of new information, future developments, or otherwise, except to the extent required by applicable law. A chart accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/7cdc7541-d4d9-4b3a-b724-710fc20ee86b

Find your next quality investment with Simply Wall St's easy and powerful screener, trusted by over 7 million individual investors worldwide. Recursion Pharmaceuticals stock has had a difficult run over the past several years, and the current valuation checks lean toward the shares looking expensive rather than like a clear bargain. Over the last 5 years, Recursion Pharmaceuticals has declined about 87%, which puts a clear focus on whether the current share price is aligned with the business outlook. The upcoming August 5 earnings call and business update can help shape expectations around Recursion Pharmaceuticals' ability to grow revenue and manage its cash needs, while any signs of higher funding requirements or slower commercial progress may weigh on how investors assess the stock. Recursion Pharmaceuticals only passes 2 of 6 valuation checks, which suggests the broader set of metrics currently leans toward the shares being on the expensive side rather than clearly undervalued. The issue now is whether Recursion Pharmaceuticals' recent share price still leaves enough upside potential to justify that relatively weak value score. Find out why Recursion Pharmaceuticals' -39.6% return over the last year is lagging behind its peers. P/S is a useful yardstick for Recursion Pharmaceuticals because the company is still building toward profitability, so investors tend to anchor more on revenue than on earnings. On this measure, the stock currently trades on a P/S of 26.5x, which is more than double the Biotechs industry average of 11.0x and also above the broader peer group average of 11.8x. The fair P/S ratio from the model sits at 0.0x, which is extremely low compared with the current 26.5x. This reflects how heavily the framework is penalising Recursion Pharmaceuticals for its losses, risk profile and current revenue base. As a result, the number is better read as a warning signal that the shares screen as very expensive rather than a precise target. Even with the upcoming 5 August 2026 earnings update on the calendar, the present P/S gap already implies that a lot of optimism is embedded in the share price. On the preferred P/S multiple, Recursion Pharmaceuticals stock currently screens as clearly overvalued. See what the numbers say about this price — find out in our valuation breakdown. Simply Wall St Narratives for Recursion Pharmaceuticals aim to connect that stretched looking P/S ratio with the assumptions that would need to hold on growth, margins and earnings for the stock to be worth materially more or less than today’s price. These Narratives sit on the company’s Community page. Each Narrative links a clear fair value estimate to a specific story about Recursion Pharmaceuticals' potential catalysts and risks, allowing you to see over time which version of events is unfolding. Community views on Recursion Pharmaceuticals could hardly be further apart, with one side seeing a transformed TechBio platform and the other focusing on past setbacks and insider behaviour. Bull case: 61% undervalued Read the full Bull Case to see why Recursion Pharmaceuticals could be undervalued Bear case: 68% overvalued Read the full Bear Case to see why Recursion Pharmaceuticals could be overvalued Do you think there's more to the story for Recursion Pharmaceuticals? Head over to our Community to see what others are saying! Recursion Pharmaceuticals currently screens as overvalued on the preferred P/S multiple, with a wide gap between its valuation and sector averages. That gap reflects very high expectations around future revenue and execution, while the broader set of valuation checks remains weak. From here, the key question is whether Recursion Pharmaceuticals can deliver enough commercial progress and justify those expectations before funding needs or slower growth assumptions start to matter more in how the market prices the stock. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Companies discussed in this article include RXRX. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email [email protected]

Interested in Recursion Pharmaceuticals, Inc.? Here are five stocks we like better. Recursion advanced its pipeline, moving its first neuroscience target from the Roche/Genentech collaboration into joint early drug discovery and receiving FDA clearance to begin the Phase I ZINNIA trial for REC-7735, a selective PI3K inhibitor. In the Phase II TUPELO study, REC-4881 produced a median 43% reduction in FAP polyp burden after three months, with effects observed in both upper and lower gastrointestinal tracts; additional data are expected in November. The company lowered 2026 cash operating expense guidance to $375 million and said its approximately $557 million cash balance supports an operating runway through early 2028, while partnerships have generated more than $500 million in realized cash inflows. 2 Reasons Absci Could Be the Future of AI Biotech, and 1 Risk Recursion Pharmaceuticals (NASDAQ:RXRX) outlined progress across its clinical pipeline, drug-discovery partnerships and AI-enabled research platform, while lowering its 2026 cash operating expense guidance to $375 million and reaffirming expectations for an operating runway through early 2028. The company said it now has five clinical-stage programs and has generated more than $500 million in realized cash inflows through partnerships. Management emphasized that its drug-discovery approach combines proprietary biological data, AI models and experimental validation in a continuous “lab-in-the-loop” system. → SpaceX’s First Earnings Report Could Decide Whether Shorts or Bulls Have Control These Are the Only 6 Stock Stocks in NVIDIA's 13F Portfolio A central update was the advancement of the first neuroscience target from Recursion’s collaboration with Roche and Genentech into a joint early drug-discovery program. The company described the target as previously unexplored biology that was identified using disease-relevant cellular data, foundation models and experimental validation. According to Recursion, the neuroscience effort used induced pluripotent stem cell-derived neuronal and microglial cells at scale, including more than 1 trillion neurons and hundreds of billions of microglia. The company said its models evaluated biological signatures across more than 17,000 genes and tens of millions of data points, generating potential targets that were subsequently assessed through multiple experimental assays. → 3 Drone Stocks That Should Soar After the Summer Slump Sudden Ascent: Is Recursion Pharmaceuticals NVIDIA’s AI Favorite? Management said the collaboration with Roche Genentech has produced more than $216 million in upfront and milestone payments to date. Recursion also cited the potential for more than $300 million in additional development, commercialization and sales milestones for each future small-molecule program under the collaboration. The company said the milestone provides early evidence that its platform can identify and validate new biological targets rather than solely optimize work on known biology. It added that the underlying datasets could potentially be reused to identify additional neuroscience opportunities. → The Bitcoin Comeback May Already Be Underway—2 ETFs for Exposure Chief Medical Officer Vicki Goodman highlighted REC-4881, an oral MEK1/2 inhibitor being evaluated in familial adenomatous polyposis, or FAP. The disease causes patients to develop hundreds or thousands of polyps in the gastrointestinal tract and often requires colectomy and continued surveillance or additional procedures. Goodman said there are no approved systemic therapies to alter the course of FAP in post-colectomy patients. Recursion estimates there are more than 50,000 such patients in the U.S. and EU5 and cited a potential addressable market exceeding $10 billion. In the ongoing Phase II TUPELO study, patients receiving REC-4881 after colectomy showed a median 43% reduction in polyp burden after three months of treatment, Goodman said. She added that reductions were sustained after three months off treatment and were observed in both the upper and lower gastrointestinal tract. The company characterized the safety profile as manageable, with predominantly mild-to-moderate adverse events consistent with other MEK inhibitors. Recursion is continuing enrollment in TUPELO, including a dose-optimization cohort. Additional data are scheduled for presentation at the CGA-IGC Conference in November, and the company expects to provide an update on FDA discussions later this year. Goodman said regulatory discussions have focused on reducing uncertainty around study design, including the appropriate primary endpoint, in a disease with limited regulatory precedent. Recursion also said the FDA cleared its investigational new drug application for REC-7735, a precision-designed PI3K inhibitor for cancers with the PIK3CA H1047R mutation. The company intends to initiate the Phase I ZINNIA trial later this year. Goodman said REC-7735 was designed to be more than 100-fold selective for the H1047R mutation relative to wild-type PI3K. Existing PI3K inhibitors can inhibit wild-type PI3K and cause hyperglycemia, which can limit dosing and potentially lead to hyperinsulinemia that reactivates the PI3K signaling pathway, she said. The initial dose-escalation portion of ZINNIA will enroll patients with PIK3CA H1047R-mutant solid tumors. Recursion plans to evaluate a cohort of patients vulnerable to hyperglycemia after establishing tolerability at an active dose, followed by dose optimization in ER-positive, HER2-negative breast cancer. The company said it may expand to additional tumor types based on emerging data and expects first dose-escalation data in the first half of 2028. Management said REC-7735 was delivered as a development candidate in 10 months, following the synthesis of 242 compounds across 13 design cycles. The company said its platform identified a previously unpublished binding pocket and found no identified off-target liabilities in its preclinical work. Recursion said it has generated and aggregated more than 50 petabytes of multimodal biological data. Management said its chemistry platform has advanced candidates using roughly 330 compounds over about a year and a half, compared with an industry benchmark cited by the company of roughly 2,500 compounds over four years for small-molecule discovery. The company also described AI agents being deployed in biology, chemistry and clinical development. It said a target-discovery tool can help scientists interrogate biological maps in hours rather than weeks, while a chemistry design agent has reduced structural-analysis work from roughly four hours to about 30 minutes. In clinical development, management said agentic workflows have contributed to enrollment improvements of approximately 1.3 to 1.6 times historical benchmarks. Recursion named Dr. Hoifung Poon as chief AI officer and Dr. Donovan Chin to lead drug design. Management said Poon will oversee the company’s end-to-end AI strategy, while Chin brings experience across small molecules, RNA-targeted therapeutics, proximity-based medicines and peptide modalities. CFO Ben Taylor said the company lowered its 2026 full-year cash operating expense guidance to $375 million, representing a nearly 40% reduction from comparable 2024 pro forma expenses. He said Recursion ended the quarter with approximately $557 million in cash and equivalents and believes that balance provides operating runway through early 2028. Recursion Pharmaceuticals, Inc (NASDAQ: RXRX) is a biopharmaceutical company that combines advanced automation, artificial intelligence and high-throughput biology to discover and develop novel therapeutics. The company's proprietary platform integrates deep-learning algorithms with large-scale cellular imaging and chemical biology, enabling the rapid identification of potential drug candidates across a range of indications. By automating complex laboratory workflows and leveraging computational models, Recursion aims to accelerate the drug discovery process and expand the scope of targets that can be addressed. At the core of Recursion's offering is its digital biology platform, which captures billions of cell images under varying chemical and genetic perturbations. This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected]. The article "Recursion Pharmaceuticals Q2 Earnings Call Highlights" was originally published by MarketBeat. View MarketBeat's top stocks for August 2026.

Our analysts just identified a stock with the potential to be the next Nvidia. Tell us how you invest and we'll show you why it's our #1 pick. Tap here. Management characterizes the current period as a critical inflection point where the AI-native engine is now generating differentiated clinical programs rather than just theoretical potential. The collaboration with Roche-Genentech has successfully identified a previously unexplored neuroscience target, validating the platform's ability to discover novel biology beyond optimizing known targets. Performance attribution is tied to a 'Lab-in-the-Loop' system where 50 petabytes of proprietary multimodal data and foundation models are validated by 2 million weekly experiments. Operational efficiency is highlighted by the ability to move from target to candidate in 1.5 years using approximately 330 compounds, compared to industry benchmarks of 4 years and 2,500 compounds. Strategic positioning focuses on high-unmet-need areas like FAP and RBM39, where the company aims to deliver first-in-class therapies in markets with limited or no current competition. The company is increasingly deploying AI agents to compress design cycles and improve clinical trial enrollment speed by 1.3 to 1.6-fold over historical benchmarks. Management lowered 2026 full-year cash operating expense guidance to $375 million, representing a nearly 40% reduction from 2024 pro forma expenses through improved ROI on technology. Additional Phase II data for REC-4881 in FAP is scheduled for presentation in November, with a subsequent update on FDA regulatory interactions expected before year-end. The company expects to initiate the Phase I ZINNIA trial for REC-7735 later this year, with initial monotherapy data anticipated in the first half of 2028. Guidance assumes continued milestone achievement with Sanofi, specifically the potential nomination of an oral I&I development candidate. Current cash reserves of approximately $557 million are projected to provide an operating runway through early 2028. Management acknowledges limited regulatory precedent in FAP, necessitating ongoing, productive dialogue with the FDA to define appropriate primary endpoints for clinical benefit. The appointment of a new Chief AI Officer and Head of Drug Design signals a structural shift toward unifying frontier research with applied scientific design. The neuroscience target milestone with Genentech triggered a portion of the $260 million in realized inflows, with potential for $300 million in additional milestones per future program. The strategy emphasizes model agnosticism, utilizing open-source models like Nesso-1 to ensure the platform remains state-of-the-art regardless of specific AI industry shifts. One stock. Nvidia-level potential. 30M+ investors trust Moby to find it first. Get the pick. Tap here. Management is focused on de-risking study design through ongoing FDA engagement, specifically regarding the primary endpoint to demonstrate clinical benefit in a rare disease with no precedent. Updated Phase II data at the CGA-IGC conference will include additional analyses to contextualize clinical relevance for the treating physician community. The 'durable moat' is defined by the proprietary data factory and the difficulty of replicating a trillion-cell iPSC-derived neuronal manufacturing capacity. Management argues that while Generative AI is commoditizing, the integration of experimental feedback loops and a 'bilingual' culture of tech-science experts is the primary differentiator. The reduction in 2026 guidance is driven by 'doing more with less'—specifically achieving the same outcomes through faster, cheaper AI-driven answers. Management transitioned to an outcomes-based budget to ensure every dollar is tied to specific program or partnership value inflection points. The candidate is designed to be over 100-fold selective for the H1047R mutation, aiming to avoid the hyperglycemia and hyperinsulinemia that limit current wild-type inhibitors. The platform identified a previously unpublished binding pocket, allowing for a precision-based approach that may expand the treatable population to diabetic or prediabetic patients.

Company to host public Earnings call on August 5th at 8:00 am ET / 6:00 am MT / 1:00 pm BST Salt Lake City, UT, July 29, 2026 (GLOBE NEWSWIRE) -- Salt Lake City, UT, July 29, 2026 (GLOBE NEWSWIRE) – Recursion (Nasdaq: RXRX), a leading clinical stage TechBio company decoding biology to radically improve lives, announced today it will provide business updates and report its second quarter 2026 financial results on Wednesday, August 5, 2026, before the open of the financial markets. Recursion will host an earnings call on Aug 5, 2026 at 8:00 AM ET / 6:00 AM MT / 1:00 PM BST. The company will broadcast the live stream from Recursion’s X, LinkedIn, and YouTube accounts. Investors, analysts, and the public will be able to ask questions of the company by submitting questions here: https://forms.gle/wusHaT8fSqSYF71W9 About RecursionRecursion (NASDAQ: RXRX) is a clinical stage TechBio company decoding biology to radically improve lives. Recursion is advancing a portfolio of differentiated investigational medicines across its wholly owned and partnered pipeline in oncology, rare disease, neuroscience, immunology, and other therapeutic areas with significant unmet need. Enabling its mission is the Recursion OS, an AI-native, end-to-end drug discovery and development platform integrating biology, chemistry, and clinical development into a unified intelligence system. Powered by proprietary multimodal data, purpose-built AI models, and bilingual teams fluent in both science and AI, the Recursion OS is designed to translate complex science into medicines that matter — faster, better, and at scale — for patients who are waiting. Recursion’s platform infrastructure is anchored in Salt Lake City, Utah and Milton Park, Oxfordshire, where its automated biology and chemistry laboratories generate proprietary data at industrial scale. Recursion also maintains offices in New York, Montréal and London, three global hubs for talent and leadership at the intersection of AI and scientific innovation. Learn more at www.recursion.com, or connect on X and LinkedIn. Forward-Looking StatementsThis document contains information that includes or is based upon “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995, including, without limitation, those regarding the timing of the filing of quarterly earnings; the occurrence and timing of an investor call; early and late stage discovery, preclinical, and clinical programs; licenses and collaborations; prospective products and their potential future indications and market opportunities; Recursion OS and other technologies; business and financial plans and performance; and all other statements that are not historical facts. Forward-looking statements may or may not include identifying words such as “anticipate,” “believe,” “continue,” “could,” “estimate,” “expect,” “forecast,” “goal,” “intend,” “may,” “plan,” “potential,” “project,” “seek,” “should,” “target,” “will,” “would,” and similar terms, or the negative of these terms. These statements are subject to known and unknown risks and uncertainties that could cause actual results to differ materially from those expressed or implied in such statements, including but not limited to: challenges inherent in pharmaceutical research and development, including the timing and results of preclinical and clinical programs, where the risk of failure is high and failure can occur at any stage prior to or after regulatory approval due to lack of sufficient efficacy, safety considerations, or other factors; our ability to leverage and enhance our drug discovery platform; risks related to our development and use of artificial intelligence and machine learning models, including the quality, sufficiency, and integrity of the data on which such models are trained and evolving laws and regulations governing artificial intelligence; our reliance on third parties, including contract research and contract manufacturing organizations, for the conduct of preclinical studies, clinical trials, and manufacturing; competition from other companies pursuing similar technologies or drug candidates; our ability to obtain financing for development activities and other corporate purposes; the success of our collaboration activities; our ability to obtain regulatory approval of, and ultimately commercialize, drug candidates; our ability to obtain, maintain, and enforce intellectual property protections; cyberattacks or other disruptions to our technology systems; our ability to attract, motivate, and retain key employees and manage our growth; inflation and other macroeconomic issues; and other risks and uncertainties such as those described under the heading “Risk Factors” in our filings with the U.S. Securities and Exchange Commission, including our Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. All forward-looking statements are based on management’s current estimates, projections, and assumptions and speak only as of the date of this document. Recursion undertakes no obligation to correct or update any such statements, whether as a result of new information, future developments, or otherwise, except to the extent required by applicable law. Media [email protected] Investor [email protected] CONTACT: Ryan Kelly Recursion Pharmaceuticals [email protected]

A month has gone by since the last earnings report for Allogene Therapeutics (ALLO). Shares have lost about 12.2% in that time frame, underperforming the S&P 500. But investors have to be wondering, will the recent negative trend continue leading up to its next earnings release, or is Allogene Therapeutics due for a breakout? Well, first let's take a quick look at its latest earnings report in order to get a better handle on the recent drivers for Allogene Therapeutics, Inc. before we dive into how investors and analysts have reacted as of late. Allogene incurred a first-quarter 2026 loss of 18 cents per share, narrower than the Zacks Consensus Estimate of a loss of 19 cents. In the year-ago period, the company reported a loss of 28 cents. The company did not report any sales during the quarter, as it lacks a marketed product in its portfolio. Research & development (R&D) expenses totaled $32 million, down 36% from the year-ago quarter’s level. General and administrative (G&A) expenses declined 6% to $14.1 million. As of March 31, 2026, Allogene had $266.9 million in cash and cash equivalents compared with $258.3 million in the previous quarter. After the company completed a public offering last month that generated gross proceeds of $200.4 million, management expects the existing cash runway to extend into the first quarter of 2029. Allogene now anticipates full-year operating expenses of around $225 million (previously $210 million), including non-cash stock-based compensation expense of nearly $35 million (unchanged). Cash burn for the full year is now expected to be around $165 million (previously: $150 million). In the past month, investors have witnessed a upward trend in estimates review. The consensus estimate has shifted 5.75% due to these changes. At this time, Allogene Therapeutics has a strong Growth Score of A, a grade with the same score on the momentum front. However, the stock was allocated a score of F on the value side, putting it in the fifth quintile for value investors. Overall, the stock has an aggregate VGM Score of C. If you aren't focused on one strategy, this score is the one you should be interested in. Estimates have been broadly trending upward for the stock, and the magnitude of these revisions looks promising. Interestingly, Allogene Therapeutics has a Zacks Rank #3 (Hold). We expect an in-line return from the stock in the next few months. Allogene Therapeutics is part of the Zacks Medical - Biomedical and Genetics industry. Over the past month, Recursion Pharmaceuticals (RXRX), a stock from the same industry, has gained 3.6%. The company reported its results for the quarter ended March 2026 more than a month ago. Recursion Pharmaceuticals reported revenues of $6.47 million in the last reported quarter, representing a year-over-year change of -56.1%. EPS of -$0.22 for the same period compares with -$0.50 a year ago. For the current quarter, Recursion Pharmaceuticals is expected to post a loss of $0.25 per share, indicating a change of +39% from the year-ago quarter. The Zacks Consensus Estimate remained unchanged over the last 30 days. The overall direction and magnitude of estimate revisions translate into a Zacks Rank #3 (Hold) for Recursion Pharmaceuticals. Also, the stock has a VGM Score of C. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Allogene Therapeutics, Inc. (ALLO) : Free Stock Analysis Report Recursion Pharmaceuticals, Inc. (RXRX) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research