Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.

ABSTRACT: The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biologi

SUBMITTER: Menden MP 

PROVIDER: S-EPMC6572829 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature