Predicting the effects of drugs and unveiling their mechanisms of action using an interpretable pharmacodynamic mechanism knowledge graph (IPM-KG).
Journal:
Computers in biology and medicine
Published Date:
Nov 17, 2024
Abstract
BACKGROUND: Multiple studies have aimed to consolidate drug-related data and predict drug effects. However, most of these studies have focused on integrating diverse data through correlation rather than representing them based on the pharmacodynamic mechanism of action (MOA). It is thus crucial to obtain interpretability to validate prediction results. In this study, we propose a novel framework to construct knowledge graphs that represent pharmacodynamic MOA, predict drug effects, and derive conceivable mechanistic pathways.