Prediction of adverse drug reactions based on pharmacogenomics combination features: a preliminary study.

ABSTRACT:

Introduction

Adverse Drug Reactions (ADRs), a widespread phenomenon in clinical drug treatment, are often associated with a high risk of morbidity and even death. Drugs and changes in gene expression are the two important factors that affect whether and how adverse reactions occur. Notably, pharmacogenomics data have recently become more available and could be used to predict ADR occurrence. However, there is a challenge in effectively analyzing the massive data lacking guidance on mutual relationship for ADRs prediction.

Methods

We constructed separate similarity features for drugs and ADRs using pharmacogenomics data from the Comparative Toxicogenomics Database [CTD, including Chemical-Gene Interactions (CGIs) and Gene-Disease Associations (GDAs)]. We proposed a novel deep

SUBMITTER: He M 

PROVIDER: S-EPMC11931068 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature