From toxicogenomics data to cumulative assessment groups: a framework for chemical grouping.

Abstract

The grouping of chemicals based on common 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 using chemical-gene-phenotype-disease (CGPD) tetramers derived from the Comparative Toxicogenomics Database (CTD). Our approach integrates publicly available toxicogenomics data to identify and cluster chemicals with similar molecular and phenotypic effects. The considered chemicals belong to diverse use groups including pesticides, pharmaceuticals, and industrial chemicals. We validated our method by comparing CGPD tetramer-based clusters with cumulative assessment groups (CAGs) that have been established by EFSA for pesticides and demonstrate 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 the support of evidence-based regulatory decision-making to facilitate the transition to next-generation risk assessment methodologies.