Application of computational toxicological approaches in human health risk assessment. I. A tiered surrogate approach

Hazard identification and dose–response assessment for chemicals of concern found in various environmental media are typically based on epidemiological and/or animal toxicity data. However, human health risk assessments are often requested for many compounds found at contaminated sites throughout the US that have limited or no available toxicity information from either humans or animals. To address this issue, recent efforts have focused on expanding the use of structure–activity relationships (SAR) approaches to identify appropriate surrogates and/or predict toxicological phenotype(s) and associated adverse effect levels. A tiered surrogate approach (i.e., decision tree) based on three main types of surrogates (structural, metabolic, and toxicity-like) has been developed. To select the final surrogate chemical and its surrogate toxicity value(s), a weight-of-evidence approach based on the proposed decision tree is applied. In addition, a case study with actual toxicity data serves as the evaluation to support our tiered surrogate approach. Future work will include case studies demonstrating the utility of the surrogate approach under different scenarios for data-poor chemicals. In conclusion, our surrogate approach provides a reasonable starting point for identifying potential toxic effects, target organs, and/or modes-of-action, and for selecting surrogate chemicals from which to derive either reference or risk values.