Biohub has expanded its Virtual Biology Initiative to $1.8 billion with new funding, data and computing commitments from the US government, Google DeepMind, Isomorphic Labs and Meta, aiming to create open datasets for predictive AI models of biology.
The Department of Energy will invest more than $500 million over five years in laboratory measurement, modelling and computation through the Genesis Mission. The National Institutes of Health will coordinate datasets and repositories developed through more than $500 million in previous federal investment, with Biohub standardising the material for AI training.
Google DeepMind, Isomorphic Labs and Meta are collectively committing $300 million to generate technologies and multimodal datasets for the initiative. Biohub provided the initial $500 million commitment in April, including $400 million for measurement technologies and $100 million for research outside the organisation.
Biohub head of science Alex Rives told Reuters that the initiative will use an embargo system for commercially funded datasets, giving funders a period to work with the data before it becomes publicly available. Government-funded work will not have those restrictions, he said.
The initiative aims to expand biological measurements from hundreds of millions of cells in current datasets to billions and eventually trillions, according to Rives. The first dataset is expected in about a year, while the partners are targeting predictive models within five years for work that would otherwise take decades.
Biohub head of science Alex Rives said the project could change how biological research is conducted by allowing scientists to test hypotheses digitally. “An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally,” he said.
The Department of Energy will use exascale computing, imaging technologies, autonomous laboratories and national laboratory facilities to support the work. DOE under secretary for science Darío Gil said the partnership would combine federal computing and experimental capabilities with Biohub’s AI and biological data expertise.
NIH deputy director Nicole Kleinstreuer said combining datasets and research capabilities could help develop models able to predict how cells respond to interventions. She said the resulting models could shorten the time required to achieve medical breakthroughs compared with laboratory experiments alone.
The initiative has attracted further support from the Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas and Wellcome Sanger Institute. NVIDIA will provide computing infrastructure and technical expertise, while Renaissance Philanthropy will support further funding for data generation.
