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Structure and antibody-design models from Chai Discovery, with Chai-2 reporting high zero-shot antibody hit rates.
Chai-1 and Chai-2 are structure prediction and protein design models from Chai Discovery. Chai-1 (2024) is a diffusion model for biomolecular structure prediction released with open weights, and Chai-2 (2025) adds generative design conditioned on a chosen target epitope, producing antibodies and other binders from scratch. Chai-2 reported roughly 16% zero-shot binder hit rates across dozens of targets in wet-lab tests, meaning a meaningful fraction of computer-designed antibodies bound their target without experimental optimisation. The intended users are biologics teams seeking new antibodies, including against cancer antigens. Independent replication of the Chai-2 hit rates is pending, and developability of the designed antibodies has not been reported. For a newcomer: Chai-2 claims it can design a working antibody from a target's structure on the first try in about one attempt in six.
Diffusion structure prediction; generative design conditioned on target epitope.
Query for this technology: (TITLE:"Chai-1 / Chai-2" OR ABSTRACT:"Chai-1 / Chai-2") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Chai-1 / Chai-2, not a curated reading list.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery and the tags foundation-model, protein-design.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery and the tags foundation-model, protein-design.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery and the tag foundation-model.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery and the tag foundation-model.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery and the tag foundation-model.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow and the tag foundation-model.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow and the tag foundation-model.
Open-source projects that implement or serve this technology, from OnCo's own catalogue: licence and last activity as the repository reported them on the day of the fetch. Listing is not endorsement; check the licence before reuse and the validation before clinical use.
Chai Discovery's multi-modal structure prediction model; code and weights are released, with commercial use permitted under its terms.