Prediction of the Drug-Drug Interaction Types with the Unified Embedding Features from Drug Similarity Networks.

ABSTRACT: Drug combination therapies are a promising strategy to overcome drug resistance and improve the efficacy of monotherapy in cancer, and it has been shown to lead to a decrease in dose-related toxicities. Except the synergistic reaction between drugs, some antagonistic drug-drug interactions (DDIs) exist, which is the main cause of adverse drug events. Precisely predicting the type of DDI is important for both drug development and more effective drug combination therapy applications. Recently, numerous text mining- and machine learning-based methods have been developed for predicting DDIs. All these methods implicitly utilize the feature of drugs from diverse drug-related properties. However, how to integrate these features more efficiently and improve the accuracy of classification is still

SUBMITTER: Yan XY 

PROVIDER: S-EPMC8721167 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature