Biohub launches first large-scale scientific initiative combining Frontier AI with Frontier Biology to cure or prevent disease

(Press-News.org) Mark Zuckerberg and Priscilla Chan today announced the launch of a first-of-its-kind initiative combining frontier artificial intelligence and frontier biology to dramatically accelerate scientific progress toward understanding and addressing human disease.

Since its founding in 2016, Biohub’s multidisciplinary teams of scientists and engineers have developed groundbreaking technologies to observe, measure, and program biology at the cellular level. The organization has built the largest single-cell datasets and established large-scale compute dedicated to biological research — resources that do not exist anywhere else.

Today, advances in artificial intelligence are opening new frontiers for science. To meet this moment, Biohub is launching the first large-scale scientific initiative dedicated to advancing artificial intelligence for biology. The biomedical research organization is uniquely positioned to lead this effort, combining world-class compute capacity, frontier AI research and engineering, and state-of-the-art experimental and imaging technologies.

“When we started, our goal was to help scientists cure or prevent all diseases this century,” said Biohub Co-Founder Mark Zuckerberg. “With advances in AI, we now believe this may be possible much sooner. Accelerating science is the most positive impact we think we can make. So we're going all in on AI-powered biology for our next chapter.”

To accelerate this work, EvolutionaryScale, a frontier AI research lab and public benefit company that has created groundbreaking large-scale AI systems for the life sciences, will join Biohub. Alex Rives, EvolutionaryScale’s co-founder and chief scientist — and a computer scientist known for pioneering work opening up the field of AI language modeling in biology — will serve as head of science, leading an integrated research strategy across experimental biology, data, and artificial intelligence.

“Advances in artificial intelligence are already starting to give us new tools to understand and engineer biology,” said Head of Science Alex Rives. “As we bring together frontier artificial intelligence, with biological data generation at scale, and creative experimental science, it may be possible to greatly accelerate the rate at which fundamental new scientific discoveries can be made.”

The combined team of scientists, engineers, and AI researchers will develop the datasets, laboratory technologies, and modeling innovations needed to build the next generation of AI systems to power the future of biological discovery and disease research. To fuel these efforts, Biohub is expanding its compute capacity tenfold, to 10,000 GPUs by 2028, and channeling its resources into data generation and experimental biology.

Biohub has committed to four scientific grand challenges: developing a unified AI-based model of the cell to predict and understand how cells behave within the human body; advancing state-of-the-art imaging systems to visualize complex biological processes at unprecedented scales; creating new instrumentation to monitor and modulate inflammation in real time; and using AI to reprogram and harness the immune system for early detection, prevention, and treatment of disease. Together, these efforts aim to decode the inner workings of human biology and enable scientific and medical breakthroughs.

“When I worked as a pediatrician at UCSF, I treated children with diseases whose conditions were, in many cases, still mysteries to science,” said Biohub Co-Founder Priscilla Chan. “What I wanted more than anything was a way to see what was happening inside their cells — how genetic mutations were expressed in different cell types and what, exactly, was breaking down. Until now, that kind of understanding has been out of reach. AI is changing that. For the first time, we have the potential to model and predict the biology of disease in ways that can reveal what’s gone wrong and how we can develop new treatments to address it.”

A Vision for AI-Powered Biology

Biohub’s AI-powered biology initiative aims to create powerful AI systems that can reason about and represent biology to accelerate science:

Virtual biology: As we build high-fidelity digital representations of molecules, genomes, cells, and living systems, we’ll increasingly be able to ask scientific questions digitally — conducting virtual experiments at a scale and pace far beyond what’s possible in the lab. Digital representations of biology will enable scientists to simulate experimental outcomes and explore biological systems with unprecedented speed and depth, allowing them to ask and answer fundamental questions in ways never before possible.

Accelerated discovery: We are simultaneously working toward scientific artificial intelligence that can reason about, learn from, and synthesize the world’s scientific data, to reveal fundamental insights and accelerate the rate at which new scientific discoveries can be made.

Biohub will research, build, and scale up these powerful technologies — and make them available to scientists to drive basic advances in biology and frontier medical applications. As we make progress on these kinds of systems, we believe it might eventually become possible to achieve decades of discoveries in months. 

We believe this will come together to unlock frontier medicine. AI could enable advances like early disease detection, monitoring, and prevention; programmable cellular medicines; personalized, gene-editing-based cures; and approaches to prevent and cure inflammatory and chronic disease.

Early Milestones: Virtual Immune System and New AI Models

As Biohub builds toward this longer-term roadmap, today we are also sharing several updates on our work in progress: 

Biohub is launching the Virtual Immune System, a flagship effort to model the immense complexity of the human immune system. The aim is to change the understanding of immunological science — opening the door to engineering human health, simulating immune therapies, reprogramming dysfunctional cells, and preventing diseases before they arise.

And, Biohub is making freely available three new models on its virtual cells platform:

VariantFormer: a model that directly translates personal genetic variations into tissue-specific gene activity patterns;  CryoLens: an end-to-end, pre-trained, large-scale model for cryoET providing unsupervised structural similarity analysis; and 

scLDM: a new AI model that can generate realistic single-cell data in silico at unprecedented fidelity. 

These complement other leading models that were recently made available, including GREmLN, a graph-aware model for understanding how gene regulatory networks govern cell behavior, and rBio, a conversational large language model designed to perform biological reasoning and make scientific knowledge more accessible, and other models, providing a comprehensive platform for AI-based research in biology. 

Rapid advances in technology are driving a revolution in life sciences — where frontier AI and virtual biology shape this next era of biological discovery. Biohub, since its earliest days, will continue to partner responsibly with the worldwide scientific community, and datasets and models will be shared freely to democratize access to cutting-edge technologies for research and discovery. 

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