A novel methodology has been developed to group chemicals based on common molecular responses using curated omics‐derived data from the Comparative Toxicogenomics Database (CTD). This approach enables the identification of chemical clusters across diverse categories, providing a holistic view of their potential impacts on human health and the environment. Initially focusing on pesticides, the method demonstrated significant overlap with the European Food Safety Authority’s (EFSA) cumulative assessment groups (CAGs), validating the clustering strategy. Additionally, pesticides not currently assigned to EFSA CAGs but listed in the EFSA PARAM catalogue were identified, highlighting potential gaps due to the retrospective nature and time lag in data inclusion within CTD. The analysis was expanded to include pharmaceuticals and other chemicals of interest, such as plasticizers and per‐ and polyfluoroalkyl substances (PFAS), underscoring the intricate interplay of various chemical exposures. Challenges in determining the directionality of chemical effects were discussed, and filtering strategies that prioritize tissue and species specificity were recommended for more accurate groupings. The findings emphasize the need for improved methodologies in chemical grouping and suggest future research directions, including de novo data collection and the use of machine learning techniques to enhance the prediction of chemical groupings and their biological effects.
