A weighted Bayesian integration method for predicting drug combination using heterogeneous data.

ABSTRACT:

Background

In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies.

Methods

In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profile

SUBMITTER: Li T 

PROVIDER: S-EPMC11437629 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature