Prediction of synergistic drug combinations using PCA-initialized deep learning.

ABSTRACT:

Background

Cancer is one of the main causes of death worldwide. Combination drug therapy has been a mainstay of cancer treatment for decades and has been shown to reduce host toxicity and prevent the development of acquired drug resistance. However, the immense number of possible drug combinations and large synergistic space makes it infeasible to screen all effective drug pairs experimentally. Therefore, it is crucial to develop computational approaches to predict drug synergy and guide experimental design for the discovery of rational combinations for therapy.

Results

We present a new deep learning approach to predict synergistic drug combinations by integrating gene expression profiles from cell lines and chemical structure data. Specifically, we use principal component a

SUBMITTER: Ma J 

PROVIDER: S-EPMC8527604 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature