From Toxicogenomics Data to Cumulative Assessment Groups: A Mechanistic Framework for Chemical Grouping

Abstract

The grouping of chemicals based on shared properties or molecular mechanisms of action is pivotal for advancing regulatory toxicology, reducing data gaps, and enabling cumulative risk assessments. This study introduces a novel framework usingChemical-Gene-Phenotype-Disease (CGPD) tetramers derived from the Comparative Toxicogenomics Database (CTDbase). Our approach integrates toxicogenomics data to identify and cluster chemicals with similar molecular and phenotypic effects across diverse categories, including pesticides, pharmaceuticals, and industrial chemicals such as bisphenols and per- and poly-fluoroalkyl substances (PFAS). We validated our method by comparing CGPD Tetramer-based clusters with cumulative assessment groups (CAGs) for pesticides, demonstrating strong overlap with established groupings while identifying additional compounds relevant for risk assessment. Key examples include clusters associated with endocrine disruption and metabolic disorders.By bridging omics-derived molecular data with phenotypic and disease endpoints, this framework provides a comprehensive tool for chemical grouping and supports evidence-based regulatory decision-making, facilitating the transition to next-generation risk assessment methodologies.