Generating a Novel Dataset for Mechanisms of Drug-Induced Toxicity using LLM-supported tools

Toxicity is a leading cause of drug failure, yet existing resources often lack the mechanistic context linking drug perturbations to adverse outcomes. To bridge this gap, we introduce ToxMech, an ongoing project developing an LLM-supported system that extracts and structures toxicity mechanisms into a comprehensive heterogeneous knowledge graph. ToxMech integrates data from diverse sources, including PubMed, AOP-Wiki, FDA boxed warnings, and clinical news, using retrieval-augmented agents to mine both structured repositories and unstructured text. By encoding relationships between drugs, targets, pathways, and outcomes, ToxMech enables structured reasoning over the causal chains of drug-induced toxicity. This evolving resource aims to provide researchers with a robust tool for mechanistic modelling and enhanced safety assessment in the drug discovery pipeline.