Biohub, the nonprofit founded by Mark Zuckerberg and Priscilla Chan, began its latest push in April with a $500 million commitment to build what it calls a “virtual cell” — an AI system intended to simulate cellular behavior and help researchers narrow down which experiments are worth doing in the lab.¹

The ambition has since widened into a $1.8 billion coalition. The Department of Energy plans to put more than $500 million into biological measurement, modeling and computing over five years; the National Institutes of Health is contributing datasets and research infrastructure built through more than $500 million in prior federal investment. Google DeepMind, Meta and Isomorphic Labs are jointly adding $300 million.²

For Biohub’s science chief, Alex Rives, the premise is straightforward: better digital models could make every physical experiment more informative. “If we can put more and more reasoning and intelligence into every single question that we actually ask in the lab, the value of those empirical results will be far greater,” he said.²

But the partners are not portraying this as another exercise in simply scaling compute. AI has made striking progress with proteins and other discrete pieces of biology; a living cell is a vastly messier target. The missing ingredient, Rives argues, is the evidence that must be painstakingly collected from real cells. “The big challenge in biology is to bridge that gap between compute and the digital world and the real physical world of biology and life,” he said. “The way to do that is through data.”²

The first phase will assemble a broad map of cells and their responses to change. Within a year of receiving an initial large-scale dataset, Biohub expects to test whether models improve predictably as data grows — a crucial verdict on whether the virtual-cell promise can move from compelling concept to dependable scientific tool.²

There is also a commercial bargain at the heart of the collaboration: corporate contributors will receive one year of exclusive access to the data they help generate before it becomes public. Biohub says the embargo is meant to attract private money without permanently closing off a resource it wants to become broadly available to science.²