GenBio AI Builds First World Model of the Human Cell

First-of-its-kind system simulates human cell behavior across the full biological hierarchy, from DNA and RNA through protein to the whole-cell level

PALO ALTO, Calif.--(BUSINESS WIRE)-- GenBio AI ('GenBio') is an AI for Science company co-founded by Nobel Laureate David Baker, leading AI scientist Eric Xing, and other prominent life science and artificial intelligence researchers from Stanford, Carnegie Mellon University, Mohamed Bin Zayed University of Artificial Intelligence, Harvard, Weizmann Institute, and other research institutions. Today, the company introduced AIDO Cell, its virtual cell world model — the first system capable of simulating a human cell, both in its natural state and in response to drugs and other interventions, across its full biological hierarchy, from DNA and RNA through protein to the whole-cell level.

A Key First in Biological and Medical Sciences:

Full-hierarchy virtual cell simulation has been widely identified as a key milestone in computational biology. Compared to the previous efforts by various research labs, AIDO Cell is the first to integrate the entire molecular-to-cellular spectrum into one continuous simulation. Using the system, a researcher can perturb the cell at any level and observe how the entire cell responds. Knock out a gene, for example, and watch the effects cascade from gene regulation, to changes in protein behavior, to effects on the cell as a whole.

“What's exciting here isn't that we've solved cellular biology — we haven't, at least not yet. It's that, for the first time, we have a system capable of simulating a cell across the full hierarchy of biological scales, from DNA to whole-cell behavior, in one place, which lets you interrogate it computationally,” said Baker, who received the 2024 Nobel Prize in Chemistry for his pioneering work in computational protein design. “AIDO Cell is a meaningful foundation to build on, even at this early stage, and could have major implications for fields like drug discovery, toxicology, and disease research broadly.”

AIDO Cell's multi-scale capability is made possible by an underlying world model-based architecture, representing one of the first biological applications for an emerging area of AI research. “What world model architecture enables, and what makes our system genuinely new, is that it's both multi-scale and stateful. The simulation remembers what you've done to the cell. You can run entire sequences of perturbations, where each one builds on the last, and see the evolving, cumulative effect in the cell, just as you would in a real (wet lab) workflow,” said GenBio AI President and Chief Scientist Eric Xing.

The process of bringing new drugs and therapies to market is notoriously slow, risky, and expensive. For every 10,000 compounds that enter the drug development pipeline, only one, on average, reaches the clinic. This process takes over 10 years at an estimated average cost of over US$2 billion per successful drug candidate. A major reason why is the sheer complexity of human biology and the inability of existing research tools to capture more than a fraction of it. AIDO Cell is a first step toward closing that gap. In an early case study, the system successfully recapitulated the mechanism behind imatinib in leukemia cells, demonstrating its ability to trace how a drug treatment cascades through the full cellular environment.

“We’ve released this version of the system as a preview, an early but functional demonstration that multi-scale, stateful virtual cell simulation is now possible,” said Xing. “We plan on releasing more advanced versions of the system with enhanced capabilities and accuracy later this year and over the next year.”

AIDO Cell supports K562 and HepG2 cell lines with additional cell types in development. GenBio is preparing to launch an early access/academic collaborator program to scientists across academia, biotech, and pharma.

Founding Team: GenBio AI was founded by a team combining world-leading expertise in AI, computational biology, and business:

• David Baker — Co-Founder, GenBio AI; Professor of Biochemistry, HHMI Investigator and Director of the Institute for Protein Design, University of Washington; 2024 Nobel Laureate in Chemistry
• Ziv Bar-Joseph — Co-Founder and Chief Scientific Officer, GenBio AI; Professor, Carnegie Mellon University; former Head of AI, Sanofi; Overton Prize Winner 2012
• Fred Hu — Co-Founder and CEO, GenBio AI; Founder and Chairman, Primavera Capital Group; former Partner, Goldman Sachs
• Emma Lundberg — Co-Founder and Chief Strategic Advisor, GenBio AI; Associate Professor, Stanford University; Professor, KTH Royal Institute of Technology, Co-Director, Human Protein Atlas
• Le Song — Co-Founder and Chief Technology Officer, GenBio AI; Professor, MBZUAI; former CTO and Chief AI Scientist, BioMap
• Eric Xing — Co-Founder, President and Chief Scientist, GenBio AI; President and University Professor MBZUAI; Professor, Carnegie Mellon University

In addition, Eran Segal (Dean of Biological and Life Sciences Division and Professor, MBZUAI; Professor, Weizmann Institute of Science; Overton Prize Winner 2007), and Debora Marks (Professor, Harvard University and Overton Prize Winner 2016; co-founder, Seismic Therapeutic) serve as scientific fellows.

About GenBio AI: GenBio AI is an AI for Science company on a mission to make biology fully computable. The company is building an AI-Driven Digital Organism (AIDO) to simulate living systems, decode biology holistically, and accelerate medical and scientific research, thereby transforming medicine and healthcare to benefit humanity. AIDO Cell — a world model that simulates a cell's biology from molecules to whole-cell behavior — is the first step toward that larger mission. Founded in 2024, GenBio AI is a global venture headquartered in Palo Alto, California, with labs in Paris and Abu Dhabi.

For more information, visit: genbio.ai.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260818090648/en/

Media Contact: [email protected]

Source: GenBio AI

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