bioRxiv · 10.64898/2026.02.14.705918
A Pan-Cancer Ex Vivo Drug Screen Atlas for Functional Precision Oncology
Abstract
Compared to immortalized cell lines, patient-derived organoids and other ex vivo models have been shown to better recapitulate patient responses to therapy. High cost and technical complexity have prevented the creation of pan-cancer ex vivo datasets, limiting comprehensive analyses and predictive modeling for ex vivo drug response. We present the Pan-PreClinical (PPC) project: a drug screen atlas of 2.1M experiments across 1,982 ex vivo samples and 3,100 drugs spanning 134 cancer indications tested across 26 studies. We develop a contrastive Bayesian model to harmonize across studies, identifying 303 tissue-specific drug sensitivities and demonstrating drug sensitivities are predictive of clinically-relevant molecular profiles. Integrating established cell line databases reveals systematic biases across 55 cancer subtypes, with cell line screens favoring drugs targeting highly proliferative cells and undervaluing cell-cell communication targets. We leverage PPC to establish an ex vivo foundation model and computational platform for scalable ex vivo cancer biology and predictive oncology.
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Pichotta, K., White, J. B., Quinn, J. F., Markus, A., Tosh, C., De Mathelin, A., Coyne, E., Huang, F., Tansey, W.. 2026-02-17. A Pan-Cancer Ex Vivo Drug Screen Atlas for Functional Precision Oncology. https://doi.org/10.64898/2026.02.14.705918
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