A coalition of research institutions, US government agencies and technology companies has announced a combined commitment of $1.8 billion to generate the biological data needed to build AI models capable of predicting how human cells behave and respond to disease.
The initiative, called the Virtual Biology Initiative, is led by Biohub, a San Francisco-based nonprofit research institute, and brings together the US Department of Energy (DOE) and the National Institutes of Health (NIH) alongside Google DeepMind, Isomorphic Labs and Meta.
"Generating the data to solve predictive systems biology requires scaling past the limits of what any single organization can produce today," said Max Jaderberg, President of Isomorphic Labs, in a press release announcing the tie-up.
"By joining the Virtual Biology Initiative as a founding member, Isomorphic Labs is helping build a massive, multimodal data foundation. This initiative will generate the data needed to push the industry closer to the next significant breakthrough for biology."
Standardised data
The goal is to create an open, standardised data resource that researchers worldwide can use to train AI models of biological systems, with the ultimate aim of allowing scientists to run experiments digitally before conducting them in a laboratory.
The data will cover how cells respond to interventions across a far wider range of cell types and conditions than have previously been studied, with new technologies deployed to image and analyse cells at greater speed and scale.
Biohub's founding commitment of $500 million anchors the effort: $400 million supports new measurement technologies including cryo-electron tomography, which resolves near-atomic detail inside cells, and microscopy capable of imaging billions of cells in living tissue.
US government investment
The DOE will invest more than $500 million over five years through its Genesis Mission, drawing on exascale supercomputing, X-ray and neutron scattering, and cryo-electron microscopy across its National Laboratory system.
NIH will contribute existing biomedical datasets and national data infrastructure representing more than $500 million in prior federal investment, working with Biohub to standardise those datasets for AI model training.
Big Tech backing
Google DeepMind, Isomorphic Labs, the drug discovery company spun out of DeepMind, and Meta are collectively investing $300 million in the initiative.
"This investment in biological data generation will help create an open, standardised data commons, which will lay the foundations researchers around the world need to better model biology," said Pushmeet Kohli, vice president of AI for Science at Google DeepMind.
Nvidia will support the initiative with accelerated computing infrastructure and technical expertise.
Scientific community
A group of leading research institutions has also joined as partners, including the Allen Institute, the Broad Institute, the Gladstone Institutes, the Human Cell Atlas, the Human Protein Atlas and the Wellcome Sanger Institute.
"An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally," said Alex Rives, head of science at Biohub.
The initiative builds on a decade of open data projects led by Biohub, including Tabula Sapiens, a comprehensive atlas of human cells, and the CryoET Data Portal.
