Biohub and federal agencies expand open biology data effort

Biohub, the U.S. Department of Energy, the National Institutes of Health and new funding partners are expanding an international effort to generate open biological data for predictive AI models. The organizations are committing $1.8 billion in funding, data, computation and measurement technology to create AI-ready resources intended to help researchers better understand, prevent and treat human disease.

DOE will invest more than $500 million over five years in lab measurement, modeling and computation, while NIH will coordinate relevant datasets, repositories and knowledge bases developed through more than $500 million in prior federal investment. Biohub will work with NIH to standardize those datasets for AI model training. Google DeepMind, Isomorphic Labs and Meta are collectively investing $300 million in the Virtual Biology Initiative to support technologies and multimodal datasets for predictive models of life.

The Virtual Biology Initiative builds on Biohub’s founding $500 million commitment. Of that amount, $400 million supports measurement technologies including cryo-electron tomography, large-scale microscopy and engineering tools for perturbing biology, while $100 million funds external research. Additional participants include the Allen Institute, Broad Institute, Gladstone Institutes, the Human Cell Atlas, the Human Protein Atlas, the Wellcome Sanger Institute, NVIDIA and Renaissance Philanthropy.