Biohub, DOE, NIH and Meta/DeepMind back $1.8B virtual-biology data push for predictive AI models of disease

Biohub on October 7 announced a major expansion of its Virtual Biology Initiative with the U.S. Department of Energy, the National Institutes of Health and new funding partners, committing $1.8 billion in funding, data, computation and measurement technology to generate open, AI-ready biological data, according to Biohub’s release, The Verge and PR Newswire.

Who is contributing. DOE will invest more than $500 million over five years in lab measurement, modeling and computing. NIH will coordinate relevant datasets, repositories and knowledge bases from more than $500 million in prior federal investment. Google DeepMind, Isomorphic Labs and Meta are collectively investing $300 million to create technologies and multimodal datasets for predictive models of life. Biohub’s founding $500 million commitment, announced in April, continues to anchor the initiative.

The scientific bet. Biohub Head of Science Alex Rives called building a “virtual cell” one of the defining challenges of the next era of science, arguing that digital experiments could accelerate paths to treating disease. Google DeepMind’s Pushmeet Kohli said an open, standardized data commons is foundational for researchers modeling biology worldwide. DOE Under Secretary for Science Darío Gil framed the partnership as a new standard for open science that couples national-lab facilities with Biohub’s AI and data capabilities.

Institutional partners. Groups including the Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas and Wellcome Sanger Institute are joining the effort; NVIDIA will support accelerated computing infrastructure and domain software.

The expansion deepens Big Tech’s stake in foundational biomedical data—and was also cited in the White House’s October 8 science package alongside the Genesis Mission industry pledges.