# Biohub

> Source: https://aiwiki.ai/wiki/biohub
> Updated: 2026-10-07
> Fact-checked: 2026-10-07
> Categories: AI Research, AI for Science, Research Organizations
> License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) - attribute to "AI Wiki (aiwiki.ai)"
> Cite as: AI Wiki. "Biohub." aiwiki.ai, 7 Oct 2026. https://aiwiki.ai/wiki/biohub
> From AI Wiki (https://aiwiki.ai), the free encyclopedia of artificial intelligence. Reuse freely with attribution.

Biohub is a nonprofit biomedical research organization that combines [artificial intelligence](https://aiwiki.ai/wiki/artificial_intelligence), experimental biology, and scientific instrumentation to study cells and disease. Founded by Priscilla Chan and Mark Zuckerberg, it develops models, laboratory technologies, and shared research resources. Its stated mission is to help scientists cure or prevent disease.[1][2]

## Organization and history

Biohub grew out of the Chan Zuckerberg Biohub network. The San Francisco institute began in 2016; the network subsequently included institutes in Chicago and New York. In March 2025, the Chan Zuckerberg Initiative announced that the San Francisco Biohub and its imaging institute would combine their teams, with a new Redwood City science campus planned for 2027.[3]

On November 6, 2025, the organization announced that its scientific teams would operate together under the Biohub name. The [EvolutionaryScale](https://aiwiki.ai/wiki/evolutionaryscale) team would join the organization, and its co-founder Alex Rives would become head of science. Biohub also announced a plan to expand its computing capacity to 10,000 GPUs by 2028.[4][5]

Biohub's organizational structure includes Chan Zuckerberg Biohub, Inc., a 501(c)(3) medical research organization. Chan Zuckerberg Initiative, LLC provides strategic, funding, and operational support; the structure also includes the Chan Zuckerberg Initiative Foundation and a donor-advised fund. Its investigator program supports research and collaborations with university scientists.[2]

## Research programs

Biohub's research agenda connects biological measurements with models that can predict cellular behavior. Its four scientific grand challenges define the principal areas of work:[6]

| Program | Research objective |
|---|---|
| Virtual cells | Build AI models that predict how cells behave, including changes associated with disease.[6] |
| Biological imaging | Measure living systems across scales, from individual proteins to organisms, and use those observations to train and test cellular models.[6] |
| Tissue instrumentation and inflammation | Develop instruments that measure inflammation within tissues and study how immune activity changes over time.[6] |
| Immune cell engineering | Investigate engineered immune cells for earlier disease detection and targeted intervention.[6] |

The Virtual Immune System project, announced in November 2025, is a research roadmap for predictive immunology. It emphasizes intervention-based data and models suited to different biological scales. The proposed workflow links experimental data generation, modeling, predictions, and follow-up experiments, rather than treating a static cell atlas as a complete simulation of immunity.[7]

## AI models

### Protein models and ESM Atlas

Biohub's protein-model platform uses [protein language models](https://aiwiki.ai/wiki/protein_language_model) to learn representations from amino acid sequences. Its protein world-model release includes the following components:[8][9]

| Component | Role |
|---|---|
| ESMC, or ESM Cambrian | Protein representations learned from approximately 2.8 billion sequences.[8] |
| ESMFold2 | Predicts protein structures and biomolecular complexes; also supports computational binder design.[8] |
| ESM Atlas | A browsable collection of 6.8 billion sequences and 1.1 billion predicted structures.[8][9] |

The accompanying June 2026 preprint reports laboratory tests of designed miniproteins and single-chain antibodies with nanomolar binding affinities. These experiments concern molecular binding and protein design. The release page provides platform access and links to model weights and code, and states that the models have an MIT license.[8][9]

### Cellular and biological reasoning models

Biohub's November 2025 announcement introduced VariantFormer, CryoLens, and scLDM, alongside models already available through its virtual-cell platform:[4]

| Model | Described research use |
|---|---|
| VariantFormer | Predict tissue-specific gene activity associated with genetic variation.[4] |
| CryoLens | Analyze structural similarities in cryo-electron tomography data.[4] |
| scLDM | Generate synthetic single-cell data.[4] |
| GREmLN | Model gene regulatory networks and their relationship to cellular behavior.[4] |
| rBio | Support conversational biological reasoning through a [large language model](https://aiwiki.ai/wiki/large_language_model).[4] |

## Open biological datasets

Biohub's data resources include measurements of gene expression, protein localization, and molecular interactions. These datasets describe different aspects of biology rather than interchangeable measurements of the same phenomenon.[10][11]

| Resource | Contents |
|---|---|
| Tabula Sapiens | A human single-cell transcriptome atlas. Its portal combines two releases and lists more than 1.1 million cells from 28 organs of 24 people.[10] |
| OpenCell | Human protein localization and interaction measurements, with a searchable portal containing 1,310 tagged proteins, 29,922 protein interactions, and 5,912 three-dimensional images.[11] |

The 2022 OpenCell paper combines genome engineering, live-cell confocal imaging, mass spectrometry, and data analysis. Its [unsupervised learning](https://aiwiki.ai/wiki/unsupervised_machine_learning) approach groups proteins by spatial and interaction patterns to investigate cellular organization.[12]

## Examples of published research

### Virtual Lab

Biohub San Francisco and Stanford researchers developed Virtual Lab, a system in which a principal-investigator AI agent directs specialist agents while a human scientist gives high-level feedback. A 2025 Nature paper describes a computational pipeline combining ESM, [AlphaFold-Multimer](https://aiwiki.ai/wiki/alphafold_multimer), and Rosetta to design 92 nanobodies. Laboratory testing identified two with improved binding to the SARS-CoV-2 JN.1 or KP.3 variants while retaining binding to the ancestral spike protein. The study presents them as candidates for further investigation.[13]

### AI-guided screening for psoriasis targets

A 2026 Nature Communications study by Biohub Chicago researchers and collaborators combined a genome-wide CRISPR screen with VirtualCRISPR, a language-model framework trained on functional-genomics data. The work identified ALOX5 and OXTR as regulators of the IL-17 receptor in human keratinocytes. Topical inhibitors of these targets reduced experimentally induced psoriasis-like dermatitis in mice. These results are preclinical, rather than evidence of treatment effectiveness in human patients.[14]

## Virtual Biology Initiative

On April 29, 2026, Biohub announced a five-year Virtual Biology Initiative to expand open data for predictive biological models. Its $500 million commitment comprises $400 million for internal technologies and data generation and $100 million for external research. The initiative coordinates with research institutes and biological atlas consortia, with [NVIDIA](https://aiwiki.ai/wiki/nvidia) as a technology partner.[15]

An October 7, 2026 expansion announced a combined $1.8 billion commitment in funding, data, computation, and measurement technology. This includes more than $500 million of Department of Energy investment over five years, NIH resources developed through more than $500 million of prior federal investment, Biohub's founding $500 million commitment, and $300 million collectively from [Google DeepMind](https://aiwiki.ai/wiki/google_deepmind), [Isomorphic Labs](https://aiwiki.ai/wiki/isomorphic_labs), and Meta. The NIH contribution consists of existing datasets and infrastructure, not a newly announced $500 million cash grant. The effort seeks shared data standards and access for training biological models.[16]

## Validation and responsible use

Biohub's platform limitations state that ESM models and the atlas support research and hypothesis generation. Generated structures, annotations, similarity scores, and cluster assignments are computational predictions that require independent validation before drawing biological or clinical conclusions. Reliability can vary by target and sequence context, and the atlas's AI search agent can return inaccurate or incomplete answers.[17]

Biohub's ethics policy addresses scientific misconduct, credit, grant funding, and respectful treatment of participants. It also requires compliance with institutional and national standards for research involving human participants or animals.[18]

## See also

- [Foundation Models](https://aiwiki.ai/wiki/foundation_models)
- [AI Drug Discovery](https://aiwiki.ai/wiki/ai_drug_discovery)
- [EvolutionaryScale](https://aiwiki.ai/wiki/evolutionaryscale)

## References

1. Biohub. [Biohub research mission and programs](https://biohub.org/). Accessed October 8, 2026.
2. Biohub. [Team](https://biohub.org/team/). Organizational structure, founders, and investigator program. Accessed October 8, 2026.
3. Biohub. [CZI announces Biohub to develop breakthrough imaging technologies to observe cells in action](https://biohub.org/news/develop-breakthrough-imaging-technologies-observe-cells/). March 26, 2025.
4. Biohub. [AI-biology launch announcement](https://biohub.org/news/ai-biology-cure-disease/). November 6, 2025.
5. Biohub. [Launching the first large-scale scientific initiative combining frontier AI with frontier biology to solve disease](https://biohub.org/blog/frontier-ai-biology-initiative/). November 6, 2025.
6. Biohub. [4 scientific grand challenges to transform human health at the intersection of AI and biology](https://biohub.org/blog/ai-biology-grand-scientific-challenges/). April 16, 2025.
7. Aly Khan. [The Virtual Immune System: A roadmap for predictive human immunology](https://biohub.org/blog/virtual-immune-system-ai/). Biohub, November 6, 2025.
8. Biohub. [A World Model of Protein Biology](https://biohub.ai/esm/protein/about). Model descriptions, experimental results, and availability. Accessed October 8, 2026.
9. Salvatore Candido, Thomas Hayes, et al. [Language Modeling Materializes a World Model of Protein Biology](https://www.biorxiv.org/content/10.64898/2026.06.03.729735v1). bioRxiv preprint, posted June 4, 2026. DOI: 10.64898/2026.06.03.729735.
10. Tabula Sapiens Consortium. [Tabula Sapiens data portal](https://tabula-sapiens.sf.czbiohub.org/). Combined release description and cell counts. Accessed October 8, 2026.
11. OpenCell. [OpenCell protein data portal](https://opencell.sf.czbiohub.org/). Dataset counts and search interface. Accessed October 8, 2026.
12. Nathan H. Cho, Keith C. Cheveralls, Andreas-David Brunner, et al. [OpenCell: Endogenous tagging for the cartography of human cellular organization](https://pubmed.ncbi.nlm.nih.gov/35271311/). Science 375(6585), eabi6983, March 11, 2022. DOI: 10.1126/science.abi6983.
13. Kyle Swanson, Wesley Wu, Nash L. Bulaong, John E. Pak, and James Zou. [The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies](https://www.nature.com/articles/s41586-025-09442-9). Nature 646, 716-723, published July 29, 2025. DOI: 10.1038/s41586-025-09442-9.
14. Chenlin Zhao, Mushaine Shih, Sharif Ahmed, et al. [AI-guided CRISPR screening reveals therapeutic targets in psoriasis](https://www.nature.com/articles/s41467-026-75249-5). Nature Communications 17, 8346, published July 6, 2026. DOI: 10.1038/s41467-026-75249-5.
15. Biohub. [Biohub Launches the Virtual Biology Initiative to Galvanize a Global Effort to Create the Open Data Foundation for AI-Accelerated Biology](https://biohub.org/news/virtual-biology-initiative/). April 29, 2026.
16. Biohub. [International, cross-sector collaboration commits nearly $2 billion to build foundational data for AI models to predict and treat disease](https://biohub.org/news/virtual-biology-initiative-expansion/). October 7, 2026.
17. Biohub. [Limitations](https://biohub.ai/limitations). Updated May 27, 2026. Accessed October 8, 2026.
18. Biohub. [Ethics](https://biohub.org/ethics/). Accessed October 8, 2026.