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Use existing cell-line and organoid data to score thousands of drug pairs, publish the ranking openly, and only test the top of the list in people.
DepMap dependency screens, the NCI ALMANAC pairwise matrix and published organoid drug-response sets contain far more combination signal than has been mined. A public model that predicts synergy and, critically, therapeutic window (tumour versus normal-cell toxicity) for each pair in each molecular context would give trialists a prioritised shortlist. Models should be scored prospectively against every new combination readout.
Shares DrugBank & ChEMBL, DepMap (Cancer Dependency Map), CRISPR functional genomics, Patient-derived organoids.
Shares Patient-derived organoids to pick ADC payloads, AI-driven drug & target discovery, Patient-derived organoids, 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 DepMap (Cancer Dependency Map), CRISPR functional genomics, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares CRISPR functional genomics, AI-driven drug & target discovery, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares CRISPR functional genomics, AI-driven drug & target discovery, Lab models that fail to predict what happens in patients, Too many combinations to test.
Shares A public atlas of drug-pair responses across a thousand patient-derived organoids, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares CRISPR functional genomics, Patient-derived organoids, Lab models that fail to predict what happens in patients.