DeepMind, Meta put $300 million into Biohub virtual cell

Biohub was founded in 2016 with the aim of combating diseases, and its bet is that an accurate predictive model of biology can let scientists run experiments digitally instead of in the lab. The new $300 million from Google DeepMind, Meta, and Isomorphic Labs sits inside a $1.8 billion initiative to build the AI datasets such a model would need, and it arrives alongside public support: the US Department of Energy is putting in more than $500 million over the next five years, while the National Institutes of Health is contributing datasets, repositories, and knowledge bases from prior federal investment totaling over $500 million.

What ties these contributions together is scale. Alex Rives, Biohub's head of science, says creating a virtual cell will require coordinated data generation at national and international scale, which is the stated reason these partners are coming together. In other words, the money is not just funding a model but a shared data effort that no single lab or company is expected to assemble alone.

The test, based on Rives's framing, is whether that coordination actually materializes across countries and institutions; the datasets, rather than the dollars, are likely to determine how far the virtual cell gets. For the companies involved, the payoff would be a faster path to disease prevention and management, though that depends on whether the data generation effort holds together.