Loading
Build a shared, openly available AI model that has learned how cancer cells respond to genetic and drug perturbations, so any lab can predict what a new drug or combination might do.
Single-cell perturbation atlases, CRISPR screens (DepMap), drug-response datasets and proteomics now exist at scale, but models trained on them are mostly proprietary or single-lab. The proposal is a pre-competitive, openly licensed foundation model of the cancer cell (transcriptomic and proteomic state under perturbation) trained on pooled public and consortium data with open weights, evaluated on held-out perturbations and prospective wet-lab validation, in the way AlphaFold became shared infrastructure for structure. The Chan Zuckerberg Initiative's virtual cell work and the Arc Institute's efforts are precedents.
Shares CRISPR functional genomics, AI-driven drug & target discovery, AI that is built but not validated or deployed, Lab models that fail to predict what happens in patients.
Shares DepMap (Cancer Dependency Map), CRISPR functional genomics, AI-driven drug & target discovery, Lab models that fail to predict what happens in patients.
Shares Broad Institute of MIT and Harvard, AI-driven drug & target discovery, AI that is built but not validated or deployed, Lab models that fail to predict what happens in patients.
Shares Broad Institute of MIT and Harvard, CRISPR functional genomics, Single-cell & spatial profiling, Lab models that fail to predict what happens in patients.
Shares Virtual cell models and in-silico perturbation screens, CZ CELLxGENE / Human Cell Atlas, Single-cell & spatial profiling, Cancer AI vocabulary (CanSim terms map).
Shares CZ CELLxGENE / Human Cell Atlas, DepMap (Cancer Dependency Map), Broad Institute of MIT and Harvard, CRISPR functional genomics.
Shares Broad Institute of MIT and Harvard, CRISPR functional genomics, Too many combinations to test.
Shares DepMap (Cancer Dependency Map), Broad Institute of MIT and Harvard, CRISPR functional genomics, Lab models that fail to predict what happens in patients.