Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approach.

ABSTRACT: Personalized cancer treatments based on the molecular profile of a patient's tumor are an emerging and exciting class of treatments in oncology. As genomic tumor profiling is becoming more common, targeted treatments for specific molecular alterations are gaining traction. To discover new potential therapeutics that may apply to broad classes of tumors matching some molecular pattern, experimentalists and pharmacologists rely on high-throughput, in vitro screens of many compounds against many different cell lines. We propose a hierarchical Bayesian model of how cancer cell lines respond to drugs in these experiments and develop a method for fitting the model to real-world high-throughput screening data. Through a case study, the model is shown to capture nontrivial associations between mol

SUBMITTER: Tansey W 

PROVIDER: S-EPMC9007438 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature