Rachel V Thomas

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Meta, Google, US Government Back $1.8B AI Biology Initiative: What It Means For Drug Discovery

Artificial intelligence (AI) is moving deeper into biological research, with Meta, Google DeepMind, the US government and other partners backing a $1.8 billion effort to build AI-ready biological datasets and predictive models of life that could help scientists better understand, predict and treat diseases.

Mark Zuckerberg and Priscilla Chan-backed nonprofit Biohub first announced the Virtual Biology Initiative in April 2026 with a $500 million commitment.

The five-year effort aims to generate large-scale, multimodal biological data that could help scientists develop AI models capable of predicting how cells respond to different interventions — potentially accelerating disease research, drug discovery and the development of new treatments.

The initiative has now expanded through partnerships involving the US Department of Energy, National Institutes of Health, Meta, Google DeepMind and Isomorphic Labs, bringing the total commitment to $1.8 billion.

“An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally. The insights that come from this could unlock a far greater understanding of disease and open up completely new paths for cures,” said Biohub Head of Science Alex Rives.

“Because of this potential, the creation of a virtual cell is one of the most important challenges for the next era of science. It will require coordinated data generation efforts at a national and international scale, which is why these partners are coming together. We invite the worldwide scientific community to join us in this project,” he added.

Also read: <a href="https://www.healthandme.com/health-news/anthropic-openevidence-expand-clinical-ai-globally-who-warns-of-ethics-risks-article-156209939" data-type="tilCustomLink">Anthropic, OpenEvidence Expand Clinical AI Globally: WHO Warns of Ethics Risks</a>

<h2>What Is the Virtual Biology Initiative?</h2>

The Virtual Biology Initiative aims to coordinate biological data generation across institutions and scientific disciplines, creating open, AI-ready datasets that can support predictive models of life.

The broader goal is to build increasingly accurate models of the complex workings of cells, allowing scientists to investigate biological mechanisms and understand how diseases develop. Such models could allow researchers to ask and test questions digitally at a scale and speed that would be difficult to achieve through laboratory experiments alone.

If successful, the approach could help accelerate scientific discovery, identify potential biological targets and support the development of therapies for complex diseases.

Of that commitment, $400 million supports technologies designed to expand what scientists can measure, including cryo-electron tomography to resolve near-atomic details inside cells, microscopy capable of imaging millions to billions of cells in living tissue, and engineering tools to build and perturb biology at molecular, cellular, tissue and whole-organism levels. A further $100 million supports research outside Biohub.

Read More: <a href="https://www.healthandme.com/health-news/google-deepminds-alphagenome-atlas-maps-9-billion-mutations-unlocking-genetics-and-rare-diseases-article-156123544" data-type="tilCustomLink">Google DeepMind’s AlphaGenome Atlas Maps 9 Billion Mutations in Human Genome; To Reveal Genetics, Rare Disease Clues</a>

<h2>Inside the $1.8B AI Biology Effort</h2>

<ul><li>Biohub: Provides biological measurement technologies, research infrastructure and open datasets to build the foundation for virtual biology.</li><li>US Department of Energy: Will contribute more than $500 million through its Genesis Mission, including advanced imaging, biological research, AI-driven analysis, modeling and high-performance computing.</li><li>NIH: Brings together existing biomedical datasets, repositories, knowledge bases and research infrastructure developed through previous federal investment.</li><li>Google DeepMind: Contributes AI and AI-for-science expertise to help develop predictive models of biology.</li><li>Isomorphic Labs: Brings AI-driven drug discovery expertise and capabilities in biological modelling.</li><li>Meta: Brings AI and computational expertise as part of the industry's collective $300 million commitment.</li><li>NVIDIA: Contributes accelerated computing infrastructure, software and technical expertise.</li><li>Research institutions: Organizations including the Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas and Wellcome Sanger Institute contribute biological data, scientific expertise and international coordination.</li></ul>

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Artificial intelligence (AI) is moving deeper into biological research, with Meta, Google DeepMind, the US government and other partners backing a $1.8 billion effort to build AI-ready biological datasets and predictive models of life that could help scientists better understand, predict and treat diseases.Mark Zuckerberg and Priscilla Chan-backed nonprofit Biohub first announced the Virtual Biology Initiative in April 2026 with a $500 million commitment.The five-year effort aims to generate large-scale, multimodal biological data that could help scientists develop AI models capable of predicting how cells respond to different interventions — potentially accelerating disease research, drug discovery and the development of new treatments.The initiative has now expanded through partnerships involving the US Department of Energy, National Institutes of Health, Meta, Google DeepMind and Isomorphic Labs, bringing the total commitment to $1.8 billion. “An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally. The insights that come from this could unlock a far greater understanding of disease and open up completely new paths for cures,” said Biohub Head of Science Alex Rives.“Because of this potential, the creation of a virtual cell is one of the most important challenges for the next era of science. It will require coordinated data generation efforts at a national and international scale, which is why these partners are coming together. We invite the worldwide scientific community to join us in this project,” he added.Also read: Anthropic, OpenEvidence Expand Clinical AI Globally: WHO Warns of Ethics RisksWhat Is the Virtual Biology Initiative?The Virtual Biology Initiative aims to coordinate biological data generation across institutions and scientific disciplines, creating open, AI-ready datasets that can support predictive models of life.The broader goal is to build increasingly accurate models of the complex workings of cells, allowing scientists to investigate biological mechanisms and understand how diseases develop. Such models could allow researchers to ask and test questions digitally at a scale and speed that would be difficult to achieve through laboratory experiments alone.If successful, the approach could help accelerate scientific discovery, identify potential biological targets and support the development of therapies for complex diseases.Of that commitment, $400 million supports technologies designed to expand what scientists can measure, including cryo-electron tomography to resolve near-atomic details inside cells, microscopy capable of imaging millions to billions of cells in living tissue, and engineering tools to build and perturb biology at molecular, cellular, tissue and whole-organism levels. A further $100 million supports research outside Biohub.Read More: Google DeepMind’s AlphaGenome Atlas Maps 9 Billion Mutations in Human Genome; To Reveal Genetics, Rare Disease Clues Inside the $1.8B AI Biology EffortBiohub: Provides biological measurement technologies, research infrastructure and open datasets to build the foundation for virtual biology.US Department of Energy: Will contribute more than $500 million through its Genesis Mission, including advanced imaging, biological research, AI-driven analysis, modeling and high-performance computing.NIH: Brings together existing biomedical datasets, repositories, knowledge bases and research infrastructure developed through previous federal investment.Google DeepMind: Contributes AI and AI-for-science expertise to help develop predictive models of biology.Isomorphic Labs: Brings AI-driven drug discovery expertise and capabilities in biological modelling.Meta: Brings AI and computational expertise as part of the industry's collective $300 million commitment.NVIDIA: Contributes accelerated computing infrastructure, software and technical expertise.Research institutions: Organizations including the Allen Institute, Broad Institute, Gladstone Institutes, Human Cell Atlas, Human Protein Atlas and Wellcome Sanger Institute contribute biological data, scientific expertise and international coordination.

meta, google, us government back $1.8b ai biology initiative: what it means for drug discovery

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