'Build AI that can accurately represent the full complexity of biology': Mark Zuckerberg wants to cure all diseases but needs far more data to deliver a digital twin of human cells—As genetic data becomes the next frontier, will you trust him with yours?

• Global effort seeks massive biological datasets to power advanced cellular AI models
• Predictive cell simulations could accelerate disease research and future medical treatments
• Questions remain about data ownership as biological datasets expand worldwide

Meta billionaire Mark Zuckerberg is backing a sweeping $500 million push to build massive biological datasets that could power AI models capable of simulating human cells.

The effort, called the Virtual Biology Initiative, comes from Biohub, the nonprofit led by Zuckerberg and Priscilla Chan, M.D., and focuses on creating what scientists describe as predictive models of life at the cellular level.

The project will split the funding, with $100 million going toward supporting global data collection and $400 million on developing tools for imaging, measuring, and engineering biology at unprecedented scale.

Wanted: vast amounts of biological data

Building accurate digital models of cells has long been discussed as a pathway toward faster drug discovery and improved understanding of disease.

Scientists say the tools to begin that work now exist, but the missing ingredient remains vast amounts of high-quality biological data.

“To build artificial intelligence that can accurately represent the full complexity of biology and accelerate scientific research, we need orders of magnitude more data than exists today. We need new technologies to observe the cell, from the molecular to the tissue level, and in the context of health and disease," said Alex Rives, Biohub Head of Science.

"At Biohub, we’re committing our resources to solve this problem. Generating this data will require a coordinated global effort. We’re thrilled to partner with leading institutions and consortia who are also committed to this and to work with them to galvanize a larger effort to create the foundation for predictive models of the cell,” Rives added.

Several major research organizations have agreed to participate, including the Allen Institute, Arc Institute, Broad Institute, and Wellcome Sanger Institute.

The scale of the project reflects how quickly artificial intelligence is moving into biology, especially as researchers attempt to model how cells behave under different conditions.

Support from Nvidia will provide the computing power needed to process the enormous datasets, which scientists say are essential for training AI systems that can simulate cellular behavior accurately.

Zuckerberg said last year that Biohub’s long-term goal is to cure all human disease by combining advances in AI with large-scale biological research.

Accurate digital models of cells could allow scientists to test ideas virtually before running expensive laboratory experiments, dramatically increasing the speed of discovery.

“Achieving a predictive understanding of cellular behavior will require coordination and data at a truly global scale. The Human Cell Atlas brings together a global community, data, capabilities, and expertise needed to help make this possible—and efforts like this, where leading partners including Biohub come together, have the potential to accelerate progress in ways no single organization and consortium could achieve alone,” said Muzz Haniffa, co-Vice-Chair of the Human Cell Atlas Organising Committee.

Although the scientific promise is substantial, the scale of data required raises big questions about governance, ownership, and trust as biological information becomes an increasingly valuable resource.

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