8 million brain cells. 32 minutes. A new frontier in medicine. In less than a year, PerturbAI built a proprietary AI-native drug discovery engine, created 6 genomic maps, revealing how genes influence health and disease in living systems. Now, together with @OpenAI and @ScrippsResearch, we've uncovered 11,000 biological insights and ~100 promising leads using frontier AI in just 32 minutes. We're expanding our partnership into drug-target discovery, bringing us closer to understanding disease and developing new medicines. Better biology. Better targets. Better medicines. Learn more: perturb.ai/news/perturbai-la… Read the full blog here: openai.com/index/scaling-ai-…

RIP to cancer we literally just had a cancer drug that could eliminate surgery, radiation and chemo get FDA approved the drug is dostarlimab, an immunotherapy for one genetic subtype of rectal cancer in the trial, 47% of evaluable patients had no detectable tumor a year after treatment (independent review) colorectal is one of the top cancer killers of men under 50 the acceleration in frontier bio in 2026 is genuinely mindblowing bio/acc

BREAKING: FDA approves first functional cure for chronic Hepatitis B. The cure is currently approved for patients without cirrhosis.

Meet X-Scientist: our step toward a self-improving virtual drug hunter! Today, we’re introducing Xaira’s agentic AI platform for drug discovery: 🧠 Beats Codex using the same Astra model by 7.4 percentage points on DrugDiscoveryBench. 🧬 Nominates targets ~10× faster than human curation, with a comparable wet-lab hit rate. 🔁 Conducts autonomous research, outperforming AutoResearch and AutoScientists in the PerturbQA benchmark. Here’s what we built, what we tested, and where we’re going. 🧵

People who cured / are curing their own cancer on X: 1/ @sytses - bone cancer, billionaire founder of Gitlab, developed 10+ personalized therapies for himself. 2/ @paul_conyngham - shrank his dog Rosie's mast cell cancer tumors after chemo and surgery weren't enough. Now backed by YC and Founders Fund 3/ @miriamgonp - stage 4 breast cancer, tumor sequenced, searching for vaccine manufacturer now 4/ @kevinace - stage 4 lung cancer, angel investor in 300+ companies, first drug stopped working after 18 months. Vaccine designed, now paying $300k out of pocket for the vaccine 5/ @masonbgrant: going founder mode on his his 32-year-old wife's rare liver cancer, sequencing her tumor with AI agents 6/ @ArunRLverma: former product leader at Atoms and Shopify, brain tumor, built a vaccine from his tumor. Now building an AI health agent startup based on what he went through We're going to make it

I’m incredibly excited to share this video, in which I had the extraordinary privilege of mentioning the transformative impact of @OpenAI Codex and AI models on biomedicine, as well as what I’m working to develop using these technologies. I believe the video is beginning to air across various media outlets. I hope it inspires others to explore the incredible possibilities AI is opening up for biomedical science and humanity! 🖖 I am truly grateful and thankful to OpenAI team for the opportunity and a tiny drop of contribution in this most important era of human existence.🙏

Cancer patients with the same diagnosis often have very different tumor biology. Molecular testing can reveal underlying differences, but that's slow and expensive. Introducing Holon-S1, our platform to predict genes and biomarkers from routine pathology slides. • beats two other models at predicting spatial gene activity in a controlled comparison • has identified potentially novel biomarkers in breast cancer and colon cancer • evaluated across 16 organ types and more than 15 scanners, using slides from both formalin-fixed, paraffin-embedded and fresh-frozen tissue. We believe Holon-S1 has the potential to help researchers find new biomarkers in slides they already have, discover treatment targets, and bring more personalized cancer care within reach!

We’ve acquired Orchestra Bio, a platform that helps biopharma teams coordinate the complex process of drug development. Together, we’ll build on Rosalind, our AI models and tools for life sciences research, to streamline those operations and help new treatments reach patients sooner. Welcome @ashokaraj_ and team! openai.com/index/openai-to-a…

Today we are excited to release Artios, a fully open source system for designing functional de novo enzymes. Enzymes present a new frontier for de novo protein design models due to the challenge of coordinating precise chemistry, rather than binding a target. Enzymes are life’s biological machines and by designing them we can truly start to engineer biology. We believe these fundamental capabilities should be built in the open and shared with the community to progress science faster. 🧵 1/6

Introducing Omnii-1, our most powerful genome language model, and a major step toward general biological intelligence In a world first, Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use

We are bringing agents to the wet-lab bench at Google Research to navigate complex biological landscapes. Learn how we are grounding agents in physical lab robotics to run fast closed-loop molecular design cycles, ultimately discovering single-digit nanomolar protein binders for cancer targets →goo.gle/4B5mMMB

Dialectic 60: Patrick Hsu! @pdhsu & @arcinstitute are combining biology, engineering, and AI to turn a sci-fi future into reality. Patrick got expelled from college at 13, returned at 15, later worked on early CRISPR breakthroughs, and teamed up with @SKonermann & @patrickc to found Arc. He works 3 jobs: core investigator at Arc, professor at Stanford, and venture partner at @thrivecapital. For all his intensity and ambition, he carries a lightness and boldness that is contagious. We discuss: - why research is 99% failure and even your best ideas kind of suck - infinite games and speedrunning school - the reach of GLP-1s and power laws in biotech - what makes a good biologist - Arc’s bet on people over projects - lab robots that finally work - AI-designed organisms and new forms of life - why heart disease could go the way of infectious disease - bro science, peptides, and biofuturism - research taste in the age of AI Timestamps: (0:00) Opening Highlights (1:39) Intro: Patrick Hsu (4:29) Start: Boldness, Infinite Games, & Ambition (12:54) GLP-1s and Power Laws in Biotechnology (20:17) Expelled at 13 and Falling for Biology (25:51) What Makes a Good Biologist, Research Taste, and Biology's Data Challenges (37:58) The Arc Model: Full-Stack Science (52:01) Betting on People, Style, & Learning to Simplify (57:22) Perturbation, World Models, and Evo (1:03:27) Virtual Cell Models (1:09:56) Designing Life: From Stem Cells to Genome Writing (1:18:39) Testing, Bro Science, and Human Data (1:24:26) Can It Exist vs. Will It Exist: Science Meets Markets (1:29:59) Biofuturism: Interoception, Peptides, Muscle Modulation, Sleep, and New Forms of Life (1:43:47) Fun, Obsolescence, Going Slow, and the Future @dialecticpod 60: Patrick Hsu - Speedrunning the Infinite Game - is available on all platforms, including X. Links below.

Real life, baby

Breaking news in the world of longevity and congrats to @AliceParkNY on exclusive reporting. @davidasinclair 's @lifebiosciences early clinical trial succeed. Read the @TIME article and their announcement.

Today we introduce MedDecider - an open weight family of Jev style decision models for medicine. MedDecider achieves SOTA results on variety of medical tasks including knowledge questions, ICD codes, trial notes. 9B scores higher than Decider from Perplexity that is 3 times larger.

Arc Institute just introduced PIE (Perturbation is Everything), a new model tackling one of the hardest problems in virtual cells: predicting the effects of an unseen perturbation in an unseen cell type. The results are striking: • 2.7× higher AUPRC (0.239 vs. 0.088) when both cell context and perturbation are unseen. • 3.2× improvement on unseen perturbations. • Directly predicts differential gene expression using biological knowledge and experimental evidence. Instead of simulating entire single-cell transcriptomes, PIE focuses on what actually changes. And there's another twist: all code was written by AI coding agents, with some experiments autonomously orchestrated by AI. Virtual cells are still far from solved. But PIE offers a promising new direction. 📄 Paper: biorxiv.org/content/10.64898… 💻 GitHub: github.com/ArcInstitute/pie #VirtualCell #AIforBiology #BioAI

By my count, China has cleared 160 novel drugs for first-in-human clinical trials this year — so far. One of them is a potential treatment for sepsis, a condition associated with ~20% of all deaths globally. The drug, made by Pyrotech Therapeutics, is the first to enter the clinic that blocks formation of the gasdermin D pore (that triggers pyroptosis - inflammatory cell death - in sepsis). That’s just one of many — we looked at all of them here: breakingground.substack.com/…

BREAKING: The U.S. government, Google, Meta & Zuckerberg-backed @biohub are launching a $1.8B push to build the data layer for AI biology. The goal is to create the largest open, AI-ready biological dataset ever assembled, giving models the data needed to better predict how biology works & ultimately help treat disease. The coalition is massive: › Biohub committed $500M › DOE is investing $500M+ across measurement, modeling & compute › NIH is bringing $500M+ of federally funded datasets & repositories › Meta, Google DeepMind & @IsomorphicLabs are jointly investing another $300M This is effectively an infrastructure buildout for AI biology. Instead of just building bigger models, they’re attacking one of the biggest bottlenecks in biology AI today, generating standardized, high-quality biological data at massive scale & making it openly available to researchers. $1.8B committed to turning biology into something AI can increasingly model, predict & engineer.