What can AI do for drug discovery today, and what can’t it do yet? This week on his podcast, The Long Run, @ldtimmerman asked @DaphneKoller for a reality check, and she gave him one.
Daphne explains why AI companies are building wet labs and how human genetics links experiments s in people. She walks through the programs insitro is advancing in liver disease, ALS and brown fat, and closes with the case for public and philanthropic investment in richer human data.
Luke calls it a conversation worth listening to “for a balanced view from someone in the trenches who is both optimistic and realistic.”
🎧Apple Podcasts: podcasts.apple.com/us/podcast/ep2…
🎧Spotify: open.spotify.com/episode/3uv72l…
#DrugDiscovery #AI #Biotech
Daphne explains why AI companies are building wet labs and how human genetics links experiments s in people. She walks through the programs insitro is advancing in liver disease, ALS and brown fat, and closes with the case for public and philanthropic investment in richer human data.
Luke calls it a conversation worth listening to “for a balanced view from someone in the trenches who is both optimistic and realistic.”
🎧Apple Podcasts: podcasts.apple.com/us/podcast/ep2…
🎧Spotify: open.spotify.com/episode/3uv72l…
#DrugDiscovery #AI #Biotech
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insitro retweeted
What if the future of medicine isn't about finding better drugs, but understanding disease differently?
At the 10th Anniversary of World Summit AI Amsterdam, we had the privilege of welcoming Daphne Koller, Founder & CEO of insitro, Co-founder of Coursera and former Stanford Profg conversation on how AI is transforming drug discovery.
Joined by Niall Firth, Executive Editor at MIT Technology Review, Daphne explored From data to targets: Causal AI for better medicines, challenging one of the biggest assumptions in pharmaceutical research.
What if the reason so many drugs fail isn't the chemistry, but our incomplete understanding of what actually causes disease?
From patient-derived cells and machine learning to human genetics and precision AI phenotypes, Daphne shared how insitro is combining biology and AI to identify the mechanisms behind disease and improve the chances of developing successful treatments.
With applications spanning ALS and metabolic health, the conversation offered a compelling glimpse into a future where AI could help us understand human biology at an entirely new level.
This is where AI moves beyond possibility and towards meaningful human impact.
A huge thank you to Daphne Koller and Niall Firth for bringing such an important conversation to our 10th Anniversary stage. 💜
For a decade, World Summit AI has brought together the minds pushing the boundaries of what's possible, while asking how innovation can deliver real-world benefits for humanity.
10 years of defining AI. Shaping what comes next.
#WorldSummitAI #WSAI #AIForHealth #DrugDiscovery #AIForHumanity #HealthcareAI
At the 10th Anniversary of World Summit AI Amsterdam, we had the privilege of welcoming Daphne Koller, Founder & CEO of insitro, Co-founder of Coursera and former Stanford Profg conversation on how AI is transforming drug discovery.
Joined by Niall Firth, Executive Editor at MIT Technology Review, Daphne explored From data to targets: Causal AI for better medicines, challenging one of the biggest assumptions in pharmaceutical research.
What if the reason so many drugs fail isn't the chemistry, but our incomplete understanding of what actually causes disease?
From patient-derived cells and machine learning to human genetics and precision AI phenotypes, Daphne shared how insitro is combining biology and AI to identify the mechanisms behind disease and improve the chances of developing successful treatments.
With applications spanning ALS and metabolic health, the conversation offered a compelling glimpse into a future where AI could help us understand human biology at an entirely new level.
This is where AI moves beyond possibility and towards meaningful human impact.
A huge thank you to Daphne Koller and Niall Firth for bringing such an important conversation to our 10th Anniversary stage. 💜
For a decade, World Summit AI has brought together the minds pushing the boundaries of what's possible, while asking how innovation can deliver real-world benefits for humanity.
10 years of defining AI. Shaping what comes next.
#WorldSummitAI #WSAI #AIForHealth #DrugDiscovery #AIForHumanity #HealthcareAI
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insitro retweeted
1/2 Always such a pleasure to listen to @DaphneKoller think, not to mention call BS on AI hyperbole while embracing oppy; @ldtimmerman is a particularly good interviewer - deeply knowledgable, thoughtful, not rushed. Wonderful ep of "The Long Run" - podcasts.apple.com/us/podcast/ep2…
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Out now: “Getting Data to Grow in a Dish,” the third issue of Deep Phenotype, insitro’s Substack on scaled biology and deep causality.
Generating biological data at scale is one challenge. Ensuring that data is reliable, reproducible and meaningful enough to power AI-driven drug In our third installment, insitro founder and CEO @DaphneKoller and insitro director of integrated technology exploration, @ATGmsalickTAG, take readers behind the scenes of building insitro's biological data factory, where automation, AI, and human expertise come together to generate high-quality data and deepen our understanding of disease biology.
Through the evolution of our Pooled Optical Screening in Human cells (POSH) platform, Daphne explores the extensive scientific and engineering advances required to turn complex cellular experiments into scalable, reproducible workflows.
Along the way, the share of cells we could match to their genetic perturbation more than doubled, from 34% to above 71%, and developing a new cell-segmentation model went from six to twelve months to about a month.
“The most important thing we have built is not any single platform. It is the ability to build the next one.”
╰┈➤ Read the latest installment of Deep Phenotype: deepphenotype.substack.com/p/getting-data…
#DrugDiscovery #AI #Biology #CausalBiology
Generating biological data at scale is one challenge. Ensuring that data is reliable, reproducible and meaningful enough to power AI-driven drug In our third installment, insitro founder and CEO @DaphneKoller and insitro director of integrated technology exploration, @ATGmsalickTAG, take readers behind the scenes of building insitro's biological data factory, where automation, AI, and human expertise come together to generate high-quality data and deepen our understanding of disease biology.
Through the evolution of our Pooled Optical Screening in Human cells (POSH) platform, Daphne explores the extensive scientific and engineering advances required to turn complex cellular experiments into scalable, reproducible workflows.
Along the way, the share of cells we could match to their genetic perturbation more than doubled, from 34% to above 71%, and developing a new cell-segmentation model went from six to twelve months to about a month.
“The most important thing we have built is not any single platform. It is the ability to build the next one.”
╰┈➤ Read the latest installment of Deep Phenotype: deepphenotype.substack.com/p/getting-data…
#DrugDiscovery #AI #Biology #CausalBiology
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insitro retweeted
The Moment in AI Drug Discovery. @DaphneKoller of @insitro is the latest guest on The Long Run. Sponsors: @AlphaSenseInc and Dash Bio. timmermanreport.com/2026/11/the-ai…
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At insitro, we proved again we don't spook easy at our annual Halloween costume contest last week. Every team that participated shared the same stretch goal: win.
Protein Sciences modeled the central dogma of molecular biology with paper bases and arrows. Read the costumes from could follow the path from DNA to RNA to protein. MASH rounded up the classic monsters, Op Ex and EH&S suited up as the OSHA-Busters, and our distributed LIMS team grew a field of broccoli one video tile at a time.
The fiercest rivalry was between the Legal and People teams. Legal’s take on “The Wizard of Oz” and “Wicked” featured an AI-generated Tin Man inspired by pooled optical screening and cellular perturbation. The People team deployed Ted Lasso and AFC Richmond, setting off a wave of spirited banter and tactical maneuvering. Then came the twist. As “Ted Lasso” writer and actor Brett Goldstein has explained, the show is a retelling of “The Wizard of Oz,” with Ted as Dorothy and Roy Kent as the Tin Man.
The competition was intense, but when the yellow brick road met the pitch, camaraderie was the real winner.
#Halloween #Halloween2026 #costume #sciencepuns #insitro
Protein Sciences modeled the central dogma of molecular biology with paper bases and arrows. Read the costumes from could follow the path from DNA to RNA to protein. MASH rounded up the classic monsters, Op Ex and EH&S suited up as the OSHA-Busters, and our distributed LIMS team grew a field of broccoli one video tile at a time.
The fiercest rivalry was between the Legal and People teams. Legal’s take on “The Wizard of Oz” and “Wicked” featured an AI-generated Tin Man inspired by pooled optical screening and cellular perturbation. The People team deployed Ted Lasso and AFC Richmond, setting off a wave of spirited banter and tactical maneuvering. Then came the twist. As “Ted Lasso” writer and actor Brett Goldstein has explained, the show is a retelling of “The Wizard of Oz,” with Ted as Dorothy and Roy Kent as the Tin Man.
The competition was intense, but when the yellow brick road met the pitch, camaraderie was the real winner.
#Halloween #Halloween2026 #costume #sciencepuns #insitro
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Pattern recognition tells you what’s associated with disease, not what drives it. At #AIDDD2026, insitro CSO Philip Tagari presents “Generative AI for Target Hypothesis Design: Moving Beyond Pattern Recognition,” plus Workshop 5 on building techbio at scale, Oct 27.
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insitro retweeted
AstraZeneca Strikes Up to $1.5 Billion AI Drug Discovery Deal With Insitro on.wsj.com/4B96TET
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insitro retweeted
AstraZeneca is collaborating with machine learning biotech Insitro. in a deal worth as much as $1.86 billion bloomberg.com/news/articles/…
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insitro retweeted
Today, @insitro announces our new collaboration with @AstraZeneca worth up to $1.5 billion.
The partnership pairs insitro's AI and causal human biology platform with AstraZeneca's drug development expertise to pursue new medicines for cardiometabolic diseases.
This is what sciences is all about: the opportunity to understand what drives a disease and turn those insights into medicines that make a difference for patients.
Congrats to @DaphneKoller, @im_dlight, @mmrozenman, Sharon Barr, Aradhana Sarin, and the entire insitro and AstraZeneca teams.
The partnership pairs insitro's AI and causal human biology platform with AstraZeneca's drug development expertise to pursue new medicines for cardiometabolic diseases.
This is what sciences is all about: the opportunity to understand what drives a disease and turn those insights into medicines that make a difference for patients.
Congrats to @DaphneKoller, @im_dlight, @mmrozenman, Sharon Barr, Aradhana Sarin, and the entire insitro and AstraZeneca teams.
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insitro retweeted
AstraZeneca bets $40M on AI to crack liver and heart diseases it's struggled to crack alone: AstraZeneca is partnering with AI startup insitro — handing over $40 million upfront and up to $1.5 billion in milestones — to hunt for drug targets in… dlvr.it/TVwbT9 #AstraZeneca #AI
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Today, insitro announced a strategic collaboration with @AstraZeneca for the AI-enabled discovery of novel therapeutics for metabolic dysfunction-associated steatohepatitis (MASH) and cardiomyopathies.
insitro will receive $40 million upfront and is eligible for up to lion in potential, discovery, development and commercial milestones, plus tiered royalties.
Both diseases are defined by the problem the collaboration is built to address. In each case, a single diagnostic label spans patients whose underlying biology differs. The heterogeneity across these diseases has made them difficult to treat, and the condition under which insitro’s machine learning capabilities on human data is most useful.
Under the agreement, insitro will identify causal disease biology in both indications and advance AstraZeneca-nominated targets from discovery through to development candidate; AstraZeneca will lead clinical development, regulatory work, and commercialization.
“Partnering with AstraZeneca allows us to pair our deep biological precision with their deep pharmaceutical expertise and scale with potential for accelerated advancement of novel programs through development and to patients.” — @DaphneKoller, founder and CEO of insitro
Sharon Barr, Executive Vice President and Head of BioPharmaceuticals R&D, AstraZeneca: "Partnering with insitro, we are using AI to identify the biological drivers of disease to support the rapid discovery of high-quality novel molecules, advancing our ambition to deliver the next generation of medicines to patients faster.”
Read the announcement: insitro.com/news/insitro-a…
More on our approach to causal biology: deepphenotype.substack.com
#AIDrugDiscovery #MASH #Cardiomyopathies
insitro will receive $40 million upfront and is eligible for up to lion in potential, discovery, development and commercial milestones, plus tiered royalties.
Both diseases are defined by the problem the collaboration is built to address. In each case, a single diagnostic label spans patients whose underlying biology differs. The heterogeneity across these diseases has made them difficult to treat, and the condition under which insitro’s machine learning capabilities on human data is most useful.
Under the agreement, insitro will identify causal disease biology in both indications and advance AstraZeneca-nominated targets from discovery through to development candidate; AstraZeneca will lead clinical development, regulatory work, and commercialization.
“Partnering with AstraZeneca allows us to pair our deep biological precision with their deep pharmaceutical expertise and scale with potential for accelerated advancement of novel programs through development and to patients.” — @DaphneKoller, founder and CEO of insitro
Sharon Barr, Executive Vice President and Head of BioPharmaceuticals R&D, AstraZeneca: "Partnering with insitro, we are using AI to identify the biological drivers of disease to support the rapid discovery of high-quality novel molecules, advancing our ambition to deliver the next generation of medicines to patients faster.”
Read the announcement: insitro.com/news/insitro-a…
More on our approach to causal biology: deepphenotype.substack.com
#AIDrugDiscovery #MASH #Cardiomyopathies
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@insitro is proud to announce that biotech companies in the Lilly TuneLab™ network can now deploy advanced machine learning models built by insitro with @EliLillyandCo to predict in vitro and, critically, in vivo properties of small molecules — representing collective progress AI drug discovery on behalf of patients.
We're discussing the news live at SF Tech Week today, where @mmrozenman, insitro CFO and CBO, joins Aliza Apple, PhD, Vice President of Catalyze360 AI/ML and Global Head of Lilly TuneLab, at the @a16zBioHealth & Lilly TuneLab biotech breakfast.
In advance of the discussion, Mary explained, “We built insitro to make biology an AI problem, with scaled data and models at the frontier. Our in-house data scaling helps us predict which biology we should target to impact disease in vivo. Today’s announcement with Lilly takes the next step. Now we’re predicting how a molecule will behave in vivo so we can make better decisions earlier in R&D by trading upfront compute for downstream conviction. We are thrilled to ship these models on TuneLab to enable this way of working across their ecosystem.”
Trained on multi-species preclinical data that Lilly generated over decades of research from hundreds of thousands of unique molecules, the models offer a powerful alternative to today’s industry standard method of extrapolation from in vitro assays, providing an enterprise-grade capability traditionally available only to organizations with the scale to generate such data volumes themselves. The models will be updated as the dataset continues to expand.
"The question of a molecule's in vivo behavior has been an empirical question, answered experimentally, slowly, one compound at a time. These models make it a computational question first," said @DaphneKoller, PhD, founder and CEO of insitro.
The in vivo PK models are a critical component of our TherML™ platform for small molecule discovery, alongside machine learning and physics-based in silico screening, affinity models powered by proprietary DNA-encoded libraries, and an active-learning medicinal chemistry engine.
→ Read our official announcement: insitro.com/news/insitro-d…
→ Learn more about how the models work: insitro.com/news/insitro-l…
#SFTechWeek #AI #ML #LillyTuneLab #drugdiscovery
We're discussing the news live at SF Tech Week today, where @mmrozenman, insitro CFO and CBO, joins Aliza Apple, PhD, Vice President of Catalyze360 AI/ML and Global Head of Lilly TuneLab, at the @a16zBioHealth & Lilly TuneLab biotech breakfast.
In advance of the discussion, Mary explained, “We built insitro to make biology an AI problem, with scaled data and models at the frontier. Our in-house data scaling helps us predict which biology we should target to impact disease in vivo. Today’s announcement with Lilly takes the next step. Now we’re predicting how a molecule will behave in vivo so we can make better decisions earlier in R&D by trading upfront compute for downstream conviction. We are thrilled to ship these models on TuneLab to enable this way of working across their ecosystem.”
Trained on multi-species preclinical data that Lilly generated over decades of research from hundreds of thousands of unique molecules, the models offer a powerful alternative to today’s industry standard method of extrapolation from in vitro assays, providing an enterprise-grade capability traditionally available only to organizations with the scale to generate such data volumes themselves. The models will be updated as the dataset continues to expand.
"The question of a molecule's in vivo behavior has been an empirical question, answered experimentally, slowly, one compound at a time. These models make it a computational question first," said @DaphneKoller, PhD, founder and CEO of insitro.
The in vivo PK models are a critical component of our TherML™ platform for small molecule discovery, alongside machine learning and physics-based in silico screening, affinity models powered by proprietary DNA-encoded libraries, and an active-learning medicinal chemistry engine.
→ Read our official announcement: insitro.com/news/insitro-d…
→ Learn more about how the models work: insitro.com/news/insitro-l…
#SFTechWeek #AI #ML #LillyTuneLab #drugdiscovery
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Three panel discussions, one week. At @SFTechWeek 2026, insitro will take part in critical industry conversations focused on moving from predictive models to medicines that work.
1️⃣ Monday, 4:00–6:30 PM — Molecules, Models & Agents
→ Dave Light, insitro's VP, Strategy & Corporate panel "Beyond the Demo: AI Capabilities That Actually Deliver in Early R&D," alongside FutureHouse, Tempus AI, and @10xGenomics, moderated by @LEK_Consulting. The event is hosted by @GitHub with @Microsoft, @NVIDIA, and @Baird.
2️⃣ Tuesday, 8:30 AM — Advancing Collaborative AI Drug Discovery
→ @mmrozenman, insitro's CFO & CBO, presents at a breakfast convened by @a16z and @EliLillyandCo's TuneLab team, alongside BigHat Biosciences and Flex Therapeutics.
3️⃣ Tuesday, 5:00–8:00 PM — Models to Medicine Series: From AI Drug Discovery to Patient Engagement
→ Mary joins the Models to Medicine panel, hosted by the @awscloud for Startups team, alongside Xaira Therapeutics, Abridge, and @a16zBioHealth.
📅 Full SF Tech Week calendar: lnkd.in/ekqySxCX
#techweeksf #AI #drugdiscovery #sf
1️⃣ Monday, 4:00–6:30 PM — Molecules, Models & Agents
→ Dave Light, insitro's VP, Strategy & Corporate panel "Beyond the Demo: AI Capabilities That Actually Deliver in Early R&D," alongside FutureHouse, Tempus AI, and @10xGenomics, moderated by @LEK_Consulting. The event is hosted by @GitHub with @Microsoft, @NVIDIA, and @Baird.
2️⃣ Tuesday, 8:30 AM — Advancing Collaborative AI Drug Discovery
→ @mmrozenman, insitro's CFO & CBO, presents at a breakfast convened by @a16z and @EliLillyandCo's TuneLab team, alongside BigHat Biosciences and Flex Therapeutics.
3️⃣ Tuesday, 5:00–8:00 PM — Models to Medicine Series: From AI Drug Discovery to Patient Engagement
→ Mary joins the Models to Medicine panel, hosted by the @awscloud for Startups team, alongside Xaira Therapeutics, Abridge, and @a16zBioHealth.
📅 Full SF Tech Week calendar: lnkd.in/ekqySxCX
#techweeksf #AI #drugdiscovery #sf
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insitro retweeted
What will the next 3–5 years of AI in health and life sciences actually look like?
At World Summit AI Amsterdam, Daphne Koller, Founder & CEO of insitro, Co-founder of Coursera and former Stanford Professor, will lead an exclusive 60-minute executive masterclass on AI for Health and traditional keynote.
It's an interactive conversation with one of the pioneers of modern AI, built around the questions senior leaders are actually wrestling with as AI reshapes human biology, healthcare and drug discovery.
The conversation will explore:
→ What comes beyond foundation models
→ Where AI is creating real value in biology and healthcare, and where the hype breaks down
→ The next wave of AI companies: what to build, what to buy and how to tell the difference
→ What health and life sciences executives most often get wrong about AI
→ How regulation, capital and data will influence what wins
→ A candid look at the next 3–5 years, including which bets could pay off and which fashionable ideas may not age well
One hour. A limited room. Direct access to one of the people who has helped define modern AI.
📅 Thursday 8 October 2026
⏰ 2:30–3:30 pm
📍 Taets Art & Event Park
🎟️ €199 | Registration required
⚠️ Attendees must hold a valid World Summit AI Expo & Content ticket.
Places are limited and booking closes 25 September.
Register now: hubs.li/Q04x6yjH0
#WorldAIWeek #WorldSummitAI #DaphneKoller #AIForHealth #HealthcareAI #DrugDiscovery
At World Summit AI Amsterdam, Daphne Koller, Founder & CEO of insitro, Co-founder of Coursera and former Stanford Professor, will lead an exclusive 60-minute executive masterclass on AI for Health and traditional keynote.
It's an interactive conversation with one of the pioneers of modern AI, built around the questions senior leaders are actually wrestling with as AI reshapes human biology, healthcare and drug discovery.
The conversation will explore:
→ What comes beyond foundation models
→ Where AI is creating real value in biology and healthcare, and where the hype breaks down
→ The next wave of AI companies: what to build, what to buy and how to tell the difference
→ What health and life sciences executives most often get wrong about AI
→ How regulation, capital and data will influence what wins
→ A candid look at the next 3–5 years, including which bets could pay off and which fashionable ideas may not age well
One hour. A limited room. Direct access to one of the people who has helped define modern AI.
📅 Thursday 8 October 2026
⏰ 2:30–3:30 pm
📍 Taets Art & Event Park
🎟️ €199 | Registration required
⚠️ Attendees must hold a valid World Summit AI Expo & Content ticket.
Places are limited and booking closes 25 September.
Register now: hubs.li/Q04x6yjH0
#WorldAIWeek #WorldSummitAI #DaphneKoller #AIForHealth #HealthcareAI #DrugDiscovery
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insitro retweeted
Biopharma is rapidly embracing AI-native drug discovery, which is opening up some interesting new avenues for collaboration.
We @a16z are co-hosting an #SFTechWeek breakfast with @EliLillyandCo to dig into what this looks like in practice.
We’ll hear from leaders at Lilly TuneLab, @insitro, @BigHatBio, Flex Therapeutics, and a16z about how federated learning, biology foundation models, generative design, and closed-loop experimentation can help our industry make better predictions and accelerate drug discovery.
Come hang out with us! @Techweek_ @VanessaBraunst
partiful.com/e/ccQ8p5st5UNp…
We @a16z are co-hosting an #SFTechWeek breakfast with @EliLillyandCo to dig into what this looks like in practice.
We’ll hear from leaders at Lilly TuneLab, @insitro, @BigHatBio, Flex Therapeutics, and a16z about how federated learning, biology foundation models, generative design, and closed-loop experimentation can help our industry make better predictions and accelerate drug discovery.
Come hang out with us! @Techweek_ @VanessaBraunst
partiful.com/e/ccQ8p5st5UNp…
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