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Recursion

@RecursionPharma • 17,681 subscribers

Decoding biology to radically improve lives. The industrial revolution of drug discovery is here.

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Today, Recursion reports its second quarter financial results and business updates, showing demonstrated progress across partnerships, clinical programs, and financial goals. 🚀 Highlights include: ▪️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 <$375 million (from <$390 million) "Recursion has reached a pivotal point where our AI-native engine is translating unique data into potential first-in-class therapeutic opportunities," said Recursion CEO Najat Khan, PhD. "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." 💠 Recursion will host an Earnings Call today, August 5, 2026, at 8:00 am ET / 6:00 am MT / 1:00 pm BST. Join on: ▪️X: ▪️YouTube: ▪️LinkedIn: Analysts, investors, and the public have the opportunity to ask questions of the Company by submitting questions here:

Today, Recursion reports its second quarter financial results and business updates, showing demonstrated progress across partnerships, clinical programs, and financial goals. 🚀 Highlights include: ▪️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 <$375 million (from <$390 million) "Recursion has reached a pivotal point where our AI-native engine is translating unique data into potential first-in-class therapeutic opportunities," said Recursion CEO Najat Khan, PhD. "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." 💠 Recursion will host an Earnings Call today, August 5, 2026, at 8:00 am ET / 6:00 am MT / 1:00 pm BST. Join on: ▪️X: ▪️YouTube: ▪️LinkedIn: Analysts, investors, and the public have the opportunity to ask questions of the Company by submitting questions here:

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🚀 A better, faster co-folding-based binding affinity model. Predicting how tightly a drug candidate binds to its target is critical in drug discovery. It also requires massive computational resources. State-of-the-art models can take 20 seconds to a minute per prediction, impractical for the demands of large scale early-stage programs . 💠 Today, Recursion’s Valence Labs is releasing Nesso-1: the fastest open-source co-folding-based binding affinity model available. At 1 second per prediction, it’s roughly 20x faster than our previous collaboration on Boltz-2 while matching or surpassing its accuracy across public and internal benchmarks. By leveraging NVIDIA Healthcare cuEquivariance, we’ve been able to further accelerate both training and inference by an additional 2-3x. We look forward to continuing to improve Nesso-1 in collaboration with NVIDIA. Weights and code are fully open-sourced. The core architectural ideas behind Nesso-1 build on the insight that coarse-grained co-folding representations can match full-atom models for affinity prediction at a fraction of the cost. Nesso-1 is the first open implementation of this approach with no proprietary dependencies, trained entirely on public data, built to be reproducible and extensible. We’re already using Nesso-1 internally in active drug discovery programs. Fast, reliable affinity prediction at scale is foundational to the kind of autonomous design loops that define our vision for Autonomous Precision Design and Nesso-1 is a meaningful step toward that. 👉 Report: 👉 Github: 👉 HF:

🚀 A better, faster co-folding-based binding affinity model. Predicting how tightly a drug candidate binds to its target is critical in drug discovery. It also requires massive computational resources. State-of-the-art models can take 20 seconds to a minute per prediction, impractical for the demands of large scale early-stage programs . 💠 Today, Recursion’s Valence Labs is releasing Nesso-1: the fastest open-source co-folding-based binding affinity model available. At 1 second per prediction, it’s roughly 20x faster than our previous collaboration on Boltz-2 while matching or surpassing its accuracy across public and internal benchmarks. By leveraging NVIDIA Healthcare cuEquivariance, we’ve been able to further accelerate both training and inference by an additional 2-3x. We look forward to continuing to improve Nesso-1 in collaboration with NVIDIA. Weights and code are fully open-sourced. The core architectural ideas behind Nesso-1 build on the insight that coarse-grained co-folding representations can match full-atom models for affinity prediction at a fraction of the cost. Nesso-1 is the first open implementation of this approach with no proprietary dependencies, trained entirely on public data, built to be reproducible and extensible. We’re already using Nesso-1 internally in active drug discovery programs. Fast, reliable affinity prediction at scale is foundational to the kind of autonomous design loops that define our vision for Autonomous Precision Design and Nesso-1 is a meaningful step toward that. 👉 Report: 👉 Github: 👉 HF:

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"Our integrated system narrows millions of molecules down to a short list that's synthetically accessible. Not just promising in silico, but actually makeable before a single one is sent to the labs." Traditional drug design often leans on decades of precedent and familiar chemistry. In Part 6 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., explains how Recursion breaks that mold by getting a full computational design cycle up and running in about a day. Our AI-native engine vastly increases the aperture for our chemists. Instead of relying solely on known binding pockets, they can efficiently explore entirely novel and complex chemical space. By leveraging our integrated data, the team can forecast non-obvious design hypotheses and predict how to synthesize molecules even when nothing like them currently exists. This process begins by scoring binding affinity using advanced 3D structural models like Nesso-1. From there, the team runs hundreds of integrated models covering ADME, potency, advanced simulations, and AI retrosynthesis. This unified system rapidly filters millions of potential molecules down to a precise shortlist of high-quality candidates that are physically ready for the lab. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning
1:21
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"Our integrated system narrows millions of molecules down to a short list that's synthetically accessible. Not just promising in silico, but actually makeable before a single one is sent to the labs." Traditional drug design often leans on decades of precedent and familiar chemistry. In Part 6 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., explains how Recursion breaks that mold by getting a full computational design cycle up and running in about a day. Our AI-native engine vastly increases the aperture for our chemists. Instead of relying solely on known binding pockets, they can efficiently explore entirely novel and complex chemical space. By leveraging our integrated data, the team can forecast non-obvious design hypotheses and predict how to synthesize molecules even when nothing like them currently exists. This process begins by scoring binding affinity using advanced 3D structural models like Nesso-1. From there, the team runs hundreds of integrated models covering ADME, potency, advanced simulations, and AI retrosynthesis. This unified system rapidly filters millions of potential molecules down to a precise shortlist of high-quality candidates that are physically ready for the lab. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning

Recursion

1,091,744 views • 29 days ago

"Across our programs, we've advanced quality novel candidates after synthesizing only around 300 compounds, roughly 90% fewer than the industry average." Now that we have mapped the biology, we need to design the exact molecule to target it. In Part 5 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., and VP of Pharmacology Martin Redhead, Ph.D., break down how we transition from biological target discovery to navigating complex chemical space. Just like our approach to biology, we solve chemistry problems through a continuous feedback loop between computation and experimentation. Before a single molecule is ever synthesized in the lab, our team uses Centaur, our integrated drug design environment. By combining hundreds of machine learning and physics-based models into a single platform, we can iteratively design novel molecular structures starting directly from target properties. This generative de novo design approach automatically updates our models so they improve with every single cycle. Our AI-native product engine has already produced over 10 development candidates. By holding our chemistry to the same rigorous standards as our biology, we can synthesize a fraction of the traditional compound volume while delivering superior novel molecules. We believe this focus on quality and novelty over sheer volume will define the true impact of AI on drug development. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #AIDrugDiscovery #DrugDiscovery #Chemistry
1:41
RecursionPharma's profile picture

"Across our programs, we've advanced quality novel candidates after synthesizing only around 300 compounds, roughly 90% fewer than the industry average." Now that we have mapped the biology, we need to design the exact molecule to target it. In Part 5 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., and VP of Pharmacology Martin Redhead, Ph.D., break down how we transition from biological target discovery to navigating complex chemical space. Just like our approach to biology, we solve chemistry problems through a continuous feedback loop between computation and experimentation. Before a single molecule is ever synthesized in the lab, our team uses Centaur, our integrated drug design environment. By combining hundreds of machine learning and physics-based models into a single platform, we can iteratively design novel molecular structures starting directly from target properties. This generative de novo design approach automatically updates our models so they improve with every single cycle. Our AI-native product engine has already produced over 10 development candidates. By holding our chemistry to the same rigorous standards as our biology, we can synthesize a fraction of the traditional compound volume while delivering superior novel molecules. We believe this focus on quality and novelty over sheer volume will define the true impact of AI on drug development. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #AIDrugDiscovery #DrugDiscovery #Chemistry

Recursion

1,018,443 views • 1 month ago

"A hypothesis from a model isn't a discovery yet. So, it goes back into the lab. The biology the model predicted is the biology we saw at the bench." A computational prediction alone does not cure a disease. In Part 4 of our platform series, Associate Principal Scientist Celia Fernandez explains how Recursion closes the loop to turn AI generated hypotheses into validated biological targets. Once our foundation models point to a potential target, we run the lab in the opposite direction. The hypothesis enters a validation cascade that becomes progressively more demanding and highly specific to the disease. This physical testing allows us to aggressively derisk our computational discoveries directly at the bench. We test these targets against the exact same high bar that our global pharma partners hold their own internal programs to. When the loop finally closes, we can confidently prove that the biology the machine learning model predicted matches the physical reality we see in the lab. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AIdrugdiscovery #AI #drugdiscovery
0:42
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"A hypothesis from a model isn't a discovery yet. So, it goes back into the lab. The biology the model predicted is the biology we saw at the bench." A computational prediction alone does not cure a disease. In Part 4 of our platform series, Associate Principal Scientist Celia Fernandez explains how Recursion closes the loop to turn AI generated hypotheses into validated biological targets. Once our foundation models point to a potential target, we run the lab in the opposite direction. The hypothesis enters a validation cascade that becomes progressively more demanding and highly specific to the disease. This physical testing allows us to aggressively derisk our computational discoveries directly at the bench. We test these targets against the exact same high bar that our global pharma partners hold their own internal programs to. When the loop finally closes, we can confidently prove that the biology the machine learning model predicted matches the physical reality we see in the lab. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AIdrugdiscovery #AI #drugdiscovery

Recursion

1,014,580 views • 1 month ago

Recursion Announces New Clinical Data Across Two Potential First-in-Class Programs, Sanofi Partnership Milestone, and Oversubscribed $200M Offering Today, we announced important progress across our clinical pipeline, partnerships, and capital position—reflecting growing evidence of what our integrated AI-enabled drug discovery platform can deliver. 🚀 REC-4881 | Deep, durable polyp reductions in FAP In an expanded adult population (18+), 87% of patients achieved polyp burden reductions after 12 weeks (47% median), with 85% remaining below baseline after 12 weeks off treatment. In the upper GI—the area of greatest unmet need—92% achieved reductions (55% median), including two patients with near-complete reductions (≥98%). Of those with reductions, 92% remained below baseline after 12 weeks off treatment. With no approved pharmacologic therapies for FAP, we are targeting registrational trial initiation in 2H 2027, pending FDA discussions. Full data will be presented November 2 at CGA-IGC. 🚀 REC-1245 | Encouraging early activity in heavily pretreated cancer patients Our potential first-in-class oral RBM39 degrader demonstrated three partial responses (two confirmed in endometrial cancer; one unconfirmed in liver cancer) and 91.7% disease control (11/12) at doses ≥45 mg. No dose-limiting toxicities or treatment-related serious adverse events were observed at the selected 45 mg expansion dose. 🚀 Sanofi | First development candidate optioned Two challenging targets, one oral molecule. A potential first-in-class candidate for inflammatory disease, enabled by Recursion’s AI platform and small-molecule chemistry capabilities alongside Sanofi’s expertise. Phase 1 expected in 2027, marking the sixth progress-based milestone across our collaboration. 🚀 $200M Oversubscribed Follow-On Offering | Extending Runway Into 2029 Broad demand from leading healthcare specialists, long-only institutions, and growth investors, including Janus Henderson Investors, Invus, Longaeva Partners, ARK Invest, and Driehaus Capital Management. The financing supports advancement of our clinical pipeline, continued AI engine innovation, and strategic partnerships. Multiple independent proof points. Across diseases, programs, and partnerships. Powered by one integrated AI-enabled engine. Thank you to our employees, collaborators, clinical investigators, patients, and investors who make this progress possible. Links below 👇 Business Update: Sanofi announcement: Public offering:
0:55
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Recursion Announces New Clinical Data Across Two Potential First-in-Class Programs, Sanofi Partnership Milestone, and Oversubscribed $200M Offering Today, we announced important progress across our clinical pipeline, partnerships, and capital position—reflecting growing evidence of what our integrated AI-enabled drug discovery platform can deliver. 🚀 REC-4881 | Deep, durable polyp reductions in FAP In an expanded adult population (18+), 87% of patients achieved polyp burden reductions after 12 weeks (47% median), with 85% remaining below baseline after 12 weeks off treatment. In the upper GI—the area of greatest unmet need—92% achieved reductions (55% median), including two patients with near-complete reductions (≥98%). Of those with reductions, 92% remained below baseline after 12 weeks off treatment. With no approved pharmacologic therapies for FAP, we are targeting registrational trial initiation in 2H 2027, pending FDA discussions. Full data will be presented November 2 at CGA-IGC. 🚀 REC-1245 | Encouraging early activity in heavily pretreated cancer patients Our potential first-in-class oral RBM39 degrader demonstrated three partial responses (two confirmed in endometrial cancer; one unconfirmed in liver cancer) and 91.7% disease control (11/12) at doses ≥45 mg. No dose-limiting toxicities or treatment-related serious adverse events were observed at the selected 45 mg expansion dose. 🚀 Sanofi | First development candidate optioned Two challenging targets, one oral molecule. A potential first-in-class candidate for inflammatory disease, enabled by Recursion’s AI platform and small-molecule chemistry capabilities alongside Sanofi’s expertise. Phase 1 expected in 2027, marking the sixth progress-based milestone across our collaboration. 🚀 $200M Oversubscribed Follow-On Offering | Extending Runway Into 2029 Broad demand from leading healthcare specialists, long-only institutions, and growth investors, including Janus Henderson Investors, Invus, Longaeva Partners, ARK Invest, and Driehaus Capital Management. The financing supports advancement of our clinical pipeline, continued AI engine innovation, and strategic partnerships. Multiple independent proof points. Across diseases, programs, and partnerships. Powered by one integrated AI-enabled engine. Thank you to our employees, collaborators, clinical investigators, patients, and investors who make this progress possible. Links below 👇 Business Update: Sanofi announcement: Public offering:

Recursion

636,399 views • 27 days ago

"This is only possible because we control the design, make, and test steps within one connected system rather than handing off between disconnected tools and teams." Once molecules are designed in silico, they must be synthesized and tested in the real world. In Part 7 of our platform series, VP of Pharmacology Martin Redhead, Ph.D., explains how these candidate designs move directly into our automated DMTL (Design, Make, Test, Learn) labs. Recursion’s automated chemistry platform goes far beyond simple one-pot reactions. We execute complex, multi-step medicinal chemistry at scale. Advanced automation handles the workup, purification, and digital sample tracking for thousands of compounds, creating a digital record of every single experiment. Our in-house AI agents take this a step further by actively helping scientists plan efficient synthetic routes. Because we control the entire design, make, and test lifecycle within one fully integrated system, we completely eliminate the friction and time lost handing off data between disconnected teams. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning
1:08
RecursionPharma's profile picture

"This is only possible because we control the design, make, and test steps within one connected system rather than handing off between disconnected tools and teams." Once molecules are designed in silico, they must be synthesized and tested in the real world. In Part 7 of our platform series, VP of Pharmacology Martin Redhead, Ph.D., explains how these candidate designs move directly into our automated DMTL (Design, Make, Test, Learn) labs. Recursion’s automated chemistry platform goes far beyond simple one-pot reactions. We execute complex, multi-step medicinal chemistry at scale. Advanced automation handles the workup, purification, and digital sample tracking for thousands of compounds, creating a digital record of every single experiment. Our in-house AI agents take this a step further by actively helping scientists plan efficient synthetic routes. Because we control the entire design, make, and test lifecycle within one fully integrated system, we completely eliminate the friction and time lost handing off data between disconnected teams. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning

Recursion

167,691 views • 22 days ago

“This is the part that turns this from just a cell factory into a data factory. This high-dimensional data is the raw material our foundation models learn from. And because it’s this rich, the data is reusable, mined again and again across programs rather than generated once and thrown away.” Growing disease-relevant cells at scale is only the beginning. In Part 2 of our series on our end-to-end platform, VP of Neuroscience Chris Winrow breaks down how we run genome-scale perturbations and quantify the resulting changes in cellular state. 🔬Using acoustic liquid handlers, we move 2.5-nanoliter droplets of CRISPR-Cas9 reagents into 1,536-well plates, up to 2 million times a week. Crucially, we intentionally randomize these experiments so our machine learning models learn true biology rather than experimental artifacts. By imaging and sequencing these exact cells, we capture thousands of measurements from a single experiment. This creates a rich, reusable dataset that feeds our AI foundation models today and stays future-proofed for tomorrow. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #drugdesign #biology #AIdrugdiscovery
2:16
RecursionPharma's profile picture

“This is the part that turns this from just a cell factory into a data factory. This high-dimensional data is the raw material our foundation models learn from. And because it’s this rich, the data is reusable, mined again and again across programs rather than generated once and thrown away.” Growing disease-relevant cells at scale is only the beginning. In Part 2 of our series on our end-to-end platform, VP of Neuroscience Chris Winrow breaks down how we run genome-scale perturbations and quantify the resulting changes in cellular state. 🔬Using acoustic liquid handlers, we move 2.5-nanoliter droplets of CRISPR-Cas9 reagents into 1,536-well plates, up to 2 million times a week. Crucially, we intentionally randomize these experiments so our machine learning models learn true biology rather than experimental artifacts. By imaging and sequencing these exact cells, we capture thousands of measurements from a single experiment. This creates a rich, reusable dataset that feeds our AI foundation models today and stays future-proofed for tomorrow. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #drugdesign #biology #AIdrugdiscovery

Recursion

224,658 views • 1 month ago

On last week’s episode of TechBio Talks, CEO of Recursion, Najat Khan and Morgan Cheatham, MD, Partner and Head of Healthcare and Life Sciences at Breyer Capital connected for a conversation spanning biotech value creation, building data moats, and the future of medicine. They unpacked: 🎯 Collapsing target ID and early patient selection to treat the root biological cause 🧬 Unlocking decades of tissue and diagnostic data sitting in clinical biobanks 🩺 Extracting hidden knowledge and research-grade insights from the routine clinical data we already collect every day Catch up on their full conversation here: YouTube: Spotify: Apple: #AI #TechBio #drugdiscovery #AIdrugdiscovery #drugdesign #Biology
0:54
RecursionPharma's profile picture

On last week’s episode of TechBio Talks, CEO of Recursion, Najat Khan and Morgan Cheatham, MD, Partner and Head of Healthcare and Life Sciences at Breyer Capital connected for a conversation spanning biotech value creation, building data moats, and the future of medicine. They unpacked: 🎯 Collapsing target ID and early patient selection to treat the root biological cause 🧬 Unlocking decades of tissue and diagnostic data sitting in clinical biobanks 🩺 Extracting hidden knowledge and research-grade insights from the routine clinical data we already collect every day Catch up on their full conversation here: YouTube: Spotify: Apple: #AI #TechBio #drugdiscovery #AIdrugdiscovery #drugdesign #Biology

Recursion

208,384 views • 1 month ago

🧠 “To build this genome-wide map, we had to create over 1 trillion neurons, roughly the equivalent of 12 human brains. There was no blueprint for this.” To truly study a disease, you have to work with cells that actually resemble it. In Part 1 of our new series breaking down our end-to-end platform, CEO Najat Khan shares the unprecedented engineering required to map biology at an industrial scale. Starting in 2021, we set out to grow human neurons at scale – executing systematic genome-wide perturbations, and capturing high-dimensional imaging. Using specialized proprietary protocols developed in partnership with Roche and Genentech, we kept these iPSC-derived neurons alive, consistent, and biologically representative. We are already seeing the impact of this work, with Genentech having optioned the first neuroscience target from the collaboration into a joint early discovery program. This is the foundation of high-dimensional target discovery. 🚀 Make sure to follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery.
1:19
RecursionPharma's profile picture

🧠 “To build this genome-wide map, we had to create over 1 trillion neurons, roughly the equivalent of 12 human brains. There was no blueprint for this.” To truly study a disease, you have to work with cells that actually resemble it. In Part 1 of our new series breaking down our end-to-end platform, CEO Najat Khan shares the unprecedented engineering required to map biology at an industrial scale. Starting in 2021, we set out to grow human neurons at scale – executing systematic genome-wide perturbations, and capturing high-dimensional imaging. Using specialized proprietary protocols developed in partnership with Roche and Genentech, we kept these iPSC-derived neurons alive, consistent, and biologically representative. We are already seeing the impact of this work, with Genentech having optioned the first neuroscience target from the collaboration into a joint early discovery program. This is the foundation of high-dimensional target discovery. 🚀 Make sure to follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery.

Recursion

199,917 views • 1 month ago

In our newest episode of TechBio Talks, we explore how AI and clinical data are converging to reshape the future of medicine. CEO of Recursion, Najat Khan, PhD talks with Dr. Morgan Cheatham, Partner and Head of Healthcare and Life Sciences at Breyer Capital. As a physician, medical geneticist, and investor, Morgan brings a unique perspective, having spent nearly a decade backing category-defining companies spanning diagnostics, therapeutics, and care delivery. We unpack: 🚀How AI is reshaping the fundamentals of biotech value creation 💊Why “modality market fit” is crucial for matching treatments to patient tolerance 🔬Closing the loop between the wet lab, dry lab, and the clinic 🧬Recasting medicine as an information science to close the gap between discovery and care Listen and follow on: YouTube: Spotify:
0:49
RecursionPharma's profile picture

In our newest episode of TechBio Talks, we explore how AI and clinical data are converging to reshape the future of medicine. CEO of Recursion, Najat Khan, PhD talks with Dr. Morgan Cheatham, Partner and Head of Healthcare and Life Sciences at Breyer Capital. As a physician, medical geneticist, and investor, Morgan brings a unique perspective, having spent nearly a decade backing category-defining companies spanning diagnostics, therapeutics, and care delivery. We unpack: 🚀How AI is reshaping the fundamentals of biotech value creation 💊Why “modality market fit” is crucial for matching treatments to patient tolerance 🔬Closing the loop between the wet lab, dry lab, and the clinic 🧬Recasting medicine as an information science to close the gap between discovery and care Listen and follow on: YouTube: Spotify:

Recursion

122,162 views • 1 month ago

“The data is used to train our models. The models point to the targets. That’s lab-in-the-loop.” Generating millions of data points is only the first step. You need immense computational power to make sense of it (and maybe a good pair of headphones, because BioHive-2 is loud). In Part 3 of our series on our end-to-end platform, Chief Technology Officer Ben Mabey explains how Recursion turns raw data into a novel view of biology. 🖥️Using BioHive-2, one of the fastest supercomputers in the world, we train state-of-the-art foundation models to process every image and sequence we generate. These models create a unique embedding, or fingerprint, for every cellular perturbation we have ever performed. All of this high-dimensional data is compiled into a single massive dataset to form a comprehensive map of biology. By comparing known disease fingerprints against this map, we can find other genetic manipulations that create similar effects. This allows us to identify targets that drive or rescue a disease state, generating new hypotheses and pointing us towards potential novel discoveries. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #AIdrugdiscovery #biology
1:28
RecursionPharma's profile picture

“The data is used to train our models. The models point to the targets. That’s lab-in-the-loop.” Generating millions of data points is only the first step. You need immense computational power to make sense of it (and maybe a good pair of headphones, because BioHive-2 is loud). In Part 3 of our series on our end-to-end platform, Chief Technology Officer Ben Mabey explains how Recursion turns raw data into a novel view of biology. 🖥️Using BioHive-2, one of the fastest supercomputers in the world, we train state-of-the-art foundation models to process every image and sequence we generate. These models create a unique embedding, or fingerprint, for every cellular perturbation we have ever performed. All of this high-dimensional data is compiled into a single massive dataset to form a comprehensive map of biology. By comparing known disease fingerprints against this map, we can find other genetic manipulations that create similar effects. This allows us to identify targets that drive or rescue a disease state, generating new hypotheses and pointing us towards potential novel discoveries. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #AIdrugdiscovery #biology

Recursion

59,744 views • 1 month ago

🔹 AI drug discovery, validated. Recursion recently announced the first clinical validation of its AI-enabled drug discovery platform – positive Phase 1b/2 data for the ongoing TUPELO study evaluating its AI-identified drug, REC-4881, in Familial Adenomatous Polyposis (FAP). This progressive rare disease affects more than 50,000 people in the U.S. and EU and has no FDA-approved treatments. It results in hundreds to thousands of polyps developing in the colon, and requires a lifetime of invasive surveillance and surgery. Recursion used AI not only to deliver the first potential treatment for this disease but also to quantify – for the first time at scale – the true natural progression of polyp burden in the trial-relevant population. It demonstrates the incredible breakthroughs that can come from merging proprietary data and AI – and the tangible impact on patient lives. 👉 See the full study results here:
1:29
RecursionPharma's profile picture

🔹 AI drug discovery, validated. Recursion recently announced the first clinical validation of its AI-enabled drug discovery platform – positive Phase 1b/2 data for the ongoing TUPELO study evaluating its AI-identified drug, REC-4881, in Familial Adenomatous Polyposis (FAP). This progressive rare disease affects more than 50,000 people in the U.S. and EU and has no FDA-approved treatments. It results in hundreds to thousands of polyps developing in the colon, and requires a lifetime of invasive surveillance and surgery. Recursion used AI not only to deliver the first potential treatment for this disease but also to quantify – for the first time at scale – the true natural progression of polyp burden in the trial-relevant population. It demonstrates the incredible breakthroughs that can come from merging proprietary data and AI – and the tangible impact on patient lives. 👉 See the full study results here:

Recursion

255,879 views • 10 months ago

🚀 Reshaping drug discovery – and the future of medicine – with AI. Recursion CFO Ben Taylor joined the Opto Sessions podcast from CMC Aureon to share how Recursion uses AI, lab automation, biological data, and machine learning to improve the way new medicines are discovered and developed. 💠 They discuss: ▪️How pairing AI with lab automation across biology, chemistry, and clinical technology allows us to move beyond the ~10–12% of the genome currently addressed by approved or in-trial medicines and explore the vast realm of untapped biology. ▪️How Recursion is advancing REC-4881 for patients with familial adenomatous polyposis (FAP) — a progressive condition with no approved medical therapies — after achieving Phase 2 proof-of-concept and demonstrating meaningful reductions in polyp burden. ▪️How Recursion is compressing timelines and improving efficiency with high-quality, ML-ready data to design better molecules with ~90% fewer experimental chemistries and to run smarter, faster clinical trials. 👉 Check out the full conversation:
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🚀 Reshaping drug discovery – and the future of medicine – with AI. Recursion CFO Ben Taylor joined the Opto Sessions podcast from CMC Aureon to share how Recursion uses AI, lab automation, biological data, and machine learning to improve the way new medicines are discovered and developed. 💠 They discuss: ▪️How pairing AI with lab automation across biology, chemistry, and clinical technology allows us to move beyond the ~10–12% of the genome currently addressed by approved or in-trial medicines and explore the vast realm of untapped biology. ▪️How Recursion is advancing REC-4881 for patients with familial adenomatous polyposis (FAP) — a progressive condition with no approved medical therapies — after achieving Phase 2 proof-of-concept and demonstrating meaningful reductions in polyp burden. ▪️How Recursion is compressing timelines and improving efficiency with high-quality, ML-ready data to design better molecules with ~90% fewer experimental chemistries and to run smarter, faster clinical trials. 👉 Check out the full conversation:

Recursion

98,892 views • 4 months ago

Meet Dean Li, M.D., Ph.D. — Recursion co-founder & board member, President of Merck Research Labs. In the first episode of our new #Recursionauts series, Dean shares his perspective on how the convergence of #biology, #computation & #tech is shifting the industry.
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Meet Dean Li, M.D., Ph.D. — Recursion co-founder & board member, President of Merck Research Labs. In the first episode of our new #Recursionauts series, Dean shares his perspective on how the convergence of #biology, #computation & #tech is shifting the industry.

Recursion

363,721 views • 3 years ago

Today, we announce our Q1 2026 business updates and financial results – demonstrating continued momentum across our internal portfolio and partnered programs, with multiple value-driving milestones on track. 🚀 Key proof points include: ▪️ REC-1245 (RBM39 degrader): Early clinical data demonstrate a well-tolerated safety profile and predictable, dose-dependent PK (n=16); dose escalation ongoing with no dose-limiting toxicities observed to date. ▪️ REC-4539 (LSD1 inhibitor): First patient dosed in Phase 1; platform-derived, selective, brain-penetrant profile with a reversible mechanism and shorter predicted half-life aimed at reducing on-target platelet toxicity, supporting differentiation in solid tumors and AML. ▪️ REC-4881 (MEK1/2 inhibitor): Strong Phase 2 efficacy signals and a safety profile consistent with the MEK inhibitor class, with FDA engagement initiated to define a potential registrational pathway and an update expected in 2H26. ▪️ Our joint programs with Sanofi continue advancing towards development candidate designation and earlier stage program milestones in the next 12 months, and we expect to continue to translate biological insights from maps delivered to Roche and Genentech into potential target validation milestones over the next 12 months. As CEO and President Najat Khan says, this “represents a growing set of proof points that demonstrate our ability to translate platform insights into clinical programs. This progress reflects the strength of both our internal pipeline and partnerships, with multiple differentiated programs advancing through our end-to-end AI platform.” Our Q1 Earnings report also highlights our disciplined capital execution: reiterating the 2026 guidance of <$390M operational cash burn, and supporting runway into early 2028 without additional financing. 👉 Join our Earnings Call on Wed., May 6 at 8:00 am ET / 6:00 am MT / 1:00 pm BST, here on X and on: ▪️ YouTube: ▪️ LinkedIn: 👉 Analysts, investors, and the public can submit questions here: 👉 Read the full report:
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RecursionPharma's profile picture

Today, we announce our Q1 2026 business updates and financial results – demonstrating continued momentum across our internal portfolio and partnered programs, with multiple value-driving milestones on track. 🚀 Key proof points include: ▪️ REC-1245 (RBM39 degrader): Early clinical data demonstrate a well-tolerated safety profile and predictable, dose-dependent PK (n=16); dose escalation ongoing with no dose-limiting toxicities observed to date. ▪️ REC-4539 (LSD1 inhibitor): First patient dosed in Phase 1; platform-derived, selective, brain-penetrant profile with a reversible mechanism and shorter predicted half-life aimed at reducing on-target platelet toxicity, supporting differentiation in solid tumors and AML. ▪️ REC-4881 (MEK1/2 inhibitor): Strong Phase 2 efficacy signals and a safety profile consistent with the MEK inhibitor class, with FDA engagement initiated to define a potential registrational pathway and an update expected in 2H26. ▪️ Our joint programs with Sanofi continue advancing towards development candidate designation and earlier stage program milestones in the next 12 months, and we expect to continue to translate biological insights from maps delivered to Roche and Genentech into potential target validation milestones over the next 12 months. As CEO and President Najat Khan says, this “represents a growing set of proof points that demonstrate our ability to translate platform insights into clinical programs. This progress reflects the strength of both our internal pipeline and partnerships, with multiple differentiated programs advancing through our end-to-end AI platform.” Our Q1 Earnings report also highlights our disciplined capital execution: reiterating the 2026 guidance of <$390M operational cash burn, and supporting runway into early 2028 without additional financing. 👉 Join our Earnings Call on Wed., May 6 at 8:00 am ET / 6:00 am MT / 1:00 pm BST, here on X and on: ▪️ YouTube: ▪️ LinkedIn: 👉 Analysts, investors, and the public can submit questions here: 👉 Read the full report:

Recursion

23,615 views • 6 months ago

The future of drug discovery is here. LOWE (LLM-Orchestration Workflow Engine) is a cutting-edge software designed to perform complex #drugdiscovery tasks using a natural language interface. 🎥 Discover what LOWE can do ⬇️ Learn more: #JPM24 #TechBio
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The future of drug discovery is here. LOWE (LLM-Orchestration Workflow Engine) is a cutting-edge software designed to perform complex #drugdiscovery tasks using a natural language interface. 🎥 Discover what LOWE can do ⬇️ Learn more: #JPM24 #TechBio

Recursion

56,613 views • 2 years ago

“This is a once-in-a-lifetime opportunity.” In a Fireside Chat w/ Chris Gibson, Jensen Huang shared his vision for the future of healthcare – driven by #AI, #supercomputers, and a data-driven approach to #biology. #downloadday
13:46
RecursionPharma's profile picture

“This is a once-in-a-lifetime opportunity.” In a Fireside Chat w/ Chris Gibson, Jensen Huang shared his vision for the future of healthcare – driven by #AI, #supercomputers, and a data-driven approach to #biology. #downloadday

Recursion

32,009 views • 2 years ago

Last week we announced that with NVIDIA, we've built the largest #supercomputer in pharma and 35th in the world. Yesterday, CEO, Jensen Huang, referenced the opportunity the $RXRX supercomputer presents in #techbio.
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Last week we announced that with NVIDIA, we've built the largest #supercomputer in pharma and 35th in the world. Yesterday, CEO, Jensen Huang, referenced the opportunity the $RXRX supercomputer presents in #techbio.

Recursion

32,882 views • 2 years ago

Today, Recursion reported our 4Q/FY25 business updates and financial results. As CEO and President Najat Khan said, “Recursion has reached an inflection point: moving from proving that AI can participate in drug discovery to demonstrating that an AI-native operating system can generate clinical proof and durable value.” This includes: 🚀 A 5th milestone with Sanofi for a first-in-class Sanofi-partnered oncology program against a historically difficult and novel biological space. This brings the total upfront and progress-based milestones to $134 million to date. Five Recursion discovery program packages have been accepted to date, establishing a growing joint portfolio of novel AI-driven small molecules for immunology and oncology. 🚀 The first AI-enabled clinical validation of the Recursion OS platform in our FAP program, demonstrating translation from AI-driven biological insight to meaningful patient outcomes. We also have multiple clinical and preclinical programs advancing with defined milestones. 🚀 New preclinical efficacy data for REC-7735, a potential best-in-class PI3K⍺ H1047R inhibitor, precision designed with 242 compounds synthesized from first novel hit to REC-7735 in 10 months using the Recursion OS platform. REC-7735 demonstrates >100-fold selectivity for the H1074R mutation over WT PI3K⍺ suggesting potential improved tolerability over current inhibitors and is currently in IND-enabling studies. 🚀 $754 million of cash and cash equivalents. We exceeded our original cost savings guidance and now expect runway into early 2028, without additional financing. 👉 Read the full business updates here: 🔹 Tune in to our Earnings Call today, February 25, 2026 at 8:00 am ET / 6:00 am MT / 1:00 pm GMT, here on X, or on: ▪️ YouTube: ▪️ LinkedIn:
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RecursionPharma's profile picture

Today, Recursion reported our 4Q/FY25 business updates and financial results. As CEO and President Najat Khan said, “Recursion has reached an inflection point: moving from proving that AI can participate in drug discovery to demonstrating that an AI-native operating system can generate clinical proof and durable value.” This includes: 🚀 A 5th milestone with Sanofi for a first-in-class Sanofi-partnered oncology program against a historically difficult and novel biological space. This brings the total upfront and progress-based milestones to $134 million to date. Five Recursion discovery program packages have been accepted to date, establishing a growing joint portfolio of novel AI-driven small molecules for immunology and oncology. 🚀 The first AI-enabled clinical validation of the Recursion OS platform in our FAP program, demonstrating translation from AI-driven biological insight to meaningful patient outcomes. We also have multiple clinical and preclinical programs advancing with defined milestones. 🚀 New preclinical efficacy data for REC-7735, a potential best-in-class PI3K⍺ H1047R inhibitor, precision designed with 242 compounds synthesized from first novel hit to REC-7735 in 10 months using the Recursion OS platform. REC-7735 demonstrates >100-fold selectivity for the H1074R mutation over WT PI3K⍺ suggesting potential improved tolerability over current inhibitors and is currently in IND-enabling studies. 🚀 $754 million of cash and cash equivalents. We exceeded our original cost savings guidance and now expect runway into early 2028, without additional financing. 👉 Read the full business updates here: 🔹 Tune in to our Earnings Call today, February 25, 2026 at 8:00 am ET / 6:00 am MT / 1:00 pm GMT, here on X, or on: ▪️ YouTube: ▪️ LinkedIn:

Recursion

11,878 views • 8 months ago

🚀 How Recursion used AI to identify a novel approach for potentially treating the rare disease Familial Adenomatous Polyposis (FAP). A new video shares the story of Recursion’s investigational drug REC-4881 for the rare disease FAP which affects more than 50,000 people in the US and EU5 and has no approved medicines. Patients with this disease develop hundreds to thousands of polyps in their early teens to 20s that, if left untreated, have a nearly 100% risk of developing into colon cancer. ⬇️ Here’s how we did it: ▪️ Using the Recursion OS platform to analyze cell morphology, we tested thousands of compounds to find drugs that restored FAP-diseased cells to a healthy state. ▪️ This led us to REC-4881 — a drug that blocks a biological pathway called MEK1/2 – a new approach for treating FAP that had not been investigated clinically before. ▪️ Now, we’re using the full Recursion OS 2.0 platform — including our ClinTech real-world evidence – to fully understand disease burden and guide our clinical strategy, allowing us to expand patient eligibility for our trial. 💡 The takeaway: This program is the first clinical validation of the Recursion OS, and demonstrates our ability to translate unbiased phenotypic insights into potentially differentiated treatments for diseases with high unmet need. 👉 Read the full summary data in our December 8, 2025 press release here:
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RecursionPharma's profile picture

🚀 How Recursion used AI to identify a novel approach for potentially treating the rare disease Familial Adenomatous Polyposis (FAP). A new video shares the story of Recursion’s investigational drug REC-4881 for the rare disease FAP which affects more than 50,000 people in the US and EU5 and has no approved medicines. Patients with this disease develop hundreds to thousands of polyps in their early teens to 20s that, if left untreated, have a nearly 100% risk of developing into colon cancer. ⬇️ Here’s how we did it: ▪️ Using the Recursion OS platform to analyze cell morphology, we tested thousands of compounds to find drugs that restored FAP-diseased cells to a healthy state. ▪️ This led us to REC-4881 — a drug that blocks a biological pathway called MEK1/2 – a new approach for treating FAP that had not been investigated clinically before. ▪️ Now, we’re using the full Recursion OS 2.0 platform — including our ClinTech real-world evidence – to fully understand disease burden and guide our clinical strategy, allowing us to expand patient eligibility for our trial. 💡 The takeaway: This program is the first clinical validation of the Recursion OS, and demonstrates our ability to translate unbiased phenotypic insights into potentially differentiated treatments for diseases with high unmet need. 👉 Read the full summary data in our December 8, 2025 press release here:

Recursion

11,994 views • 9 months ago

If you’re working in AI, you most likely saw the just-released 2025 State of AI Report from Nathan Benaich, Founder and General Partner at Air Street Capital. The annual report is a must-read deep dive into the state of the industry, with this year’s highlights including: reasoning going mainstream; AI models becoming active co-scientists; and serious commercial traction, with 44% of US businesses now paying for AI tools. Tomorrow, get the behind-the-scenes story on the report and much more in a new episode of TechBio Talks, featuring Nathan in conversation with Chris Gibson. In it, Nathan shares what it means to be an “AI-first investor” and how his approach has evolved over time with the rapid acceleration of technology. As he says in the clip, he’s interested in companies where “The AI is the product.” 🎙️ Subscribe to TechBio Talks on: ▪️ Spotify: ▪️ YouTube: ▪️ Apple:
1:07
RecursionPharma's profile picture

If you’re working in AI, you most likely saw the just-released 2025 State of AI Report from Nathan Benaich, Founder and General Partner at Air Street Capital. The annual report is a must-read deep dive into the state of the industry, with this year’s highlights including: reasoning going mainstream; AI models becoming active co-scientists; and serious commercial traction, with 44% of US businesses now paying for AI tools. Tomorrow, get the behind-the-scenes story on the report and much more in a new episode of TechBio Talks, featuring Nathan in conversation with Chris Gibson. In it, Nathan shares what it means to be an “AI-first investor” and how his approach has evolved over time with the rapid acceleration of technology. As he says in the clip, he’s interested in companies where “The AI is the product.” 🎙️ Subscribe to TechBio Talks on: ▪️ Spotify: ▪️ YouTube: ▪️ Apple:

Recursion

13,947 views • 1 year ago