DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.

ABSTRACT: Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy. DD-PRiSM consists of two predictive models. The first is the Monotherapy model, which predicts parameters of the drug response curve based on drug structure and cell line gene expression. This reconstructed curve is then used to predict cell viability at the given drug dosage. The second is the Com

SUBMITTER: Jin I 

PROVIDER: S-EPMC11725392 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature