Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.

ABSTRACT: The evolving landscape of chemical risk assessment is increasingly focused on developing tiered, mechanistically driven approaches that avoid the use of animal experiments. In this context, adverse outcome pathways have gained importance for evaluating various types of chemical-induced toxicity. Using hepatic steatosis as a case study, this review explores the use of diverse computational techniques, such as structure-activity relationship models, quantitative structure-activity relationship models, read-across methods, omics data analysis, and structure-based approaches to fill data gaps within adverse outcome pathway networks. Emphasizing the regulatory acceptance of each technique, we examine how these methodologies can be integrated to provide a comprehensive understanding of chemical

SUBMITTER: Ortega-Vallbona R 

PROVIDER: S-EPMC11508863 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature