Biohub: The Future of Biology is Open-Source with Mark Zuckerberg, Priscilla Chan, and Alex Rives
In a Nutshell
Biohub's core mission is to accelerate biology by building open-source AI models and data-generation tools that empower the entire scientific community, rather than pursuing disease-specific cures directly. The strategy centers on creating hierarchical world models—from proteins to cells to systems—by integrating frontier AI with novel experimental methods that produce the large-scale data these models require. Key outcomes include releasing general protein models like ESM Fold that enable computational design of therapeutics and shifting from discovery-based to engineering-based biology through open, decentralized collaboration.
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The goal is to provide tools to the entire scientific community. The focus is on understanding how biology works at the individual level, including understanding a person's genetics and their risks for different illnesses. The objective is to treat individuals as individuals, understand mechanisms, and intervene effectively. The approach emphasizes open-source projects to get tools into more scientists' hands faster and accelerate progress across the entire scientific field rather than attempting to cure diseases directly.
The theory is not that Biohub will cure diseases. Instead, the goal is to accelerate the pace of progress for the whole scientific field. The team folded over 1.1 billion proteins and predicted their structures. They did not design a model specifically for antibodies or for binding one particular target. They designed a model that could understand proteins. If a protein can be designed to actually change physiology, then it becomes possible to cure someone.
Biohub in its current form is viewed as a good fit for what the organization brings to the table. The work started 10 years ago with the goal of building an organization that could cure, prevent, and manage all disease by the end of the century. Early meetings with Nobel Prize-winning scientists involved skepticism about this ambition. The response clarified that the organization would not be the one curing diseases. The goal was always to build tools that could accelerate the whole scientific field so the field collectively could cure all diseases. The original timeline of curing all disease by the end of the century is now considered too conservative.
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