Expanded Read-across Searches in Risk Assessments & Drug Discovery
The expanded read-across approach leverages information on structurally and functionally similar analogues to generate hypotheses about the bioactivities of a data-poor chemical and accordingly predict its toxicological effects based on the known properties or potential effects of a suitably tested source analogue. In traditional read-across, the structural similarity is the primary criterion for the candidate analogues. On the other hand, the expanded read-across considers a broader range of relationships including chemical category/group, metabolism, toxicokinetic/toxicodynamic properties, mechanism of action, expert judgment, the weight of evidence approach, Quantitative structure-activity relationship (QSAR) models, and diverse data sources. These approaches have been utilized for hazard identification, dose-response assessment of the chemicals of concern to the Superfund and Resource Conservation and Recovery Act (RCRA) Programs, and risk assessments for new chemical substances under the amended Toxic Substances Control Act (TSCA). In drug discovery, the expanded read-across approach also considers a broader pool of chemical and biological data sources even beyond structural similarity including pharmacological/ toxicological properties, biological activity profiles, omics data, other characteristics, and more complex computational modeling and simulations. These approaches are utilized to identify source analogue in the early discovery phase, select a lead chemical in the lead optimization stage, and predict pharmacological/
toxicological properties at the pharmacokinetics and toxicology stage. Overall, the expanded read-across approach complements conventional experimental methods and applications and fills data gaps by providing valuable computational tools in chemical risk assessment and drug discovery.