Application of a Tiered Read-Across Approach in Support of Quantitative Risk Assessment
Application of a Tiered Read-Across Approach in Support of Quantitative Risk Assessment of Organochlorine Contaminants
Traditionally, deriving health reference values for environmental chemicals requires comprehensive human or animal toxicity data to identify potential adverse health effects and associated dose-response. Chemicals with insufficient in vivo toxicity information pose a substantial challenge to regulatory agencies. This research demonstrates the use of a tiered read-across approach to identify surrogate compounds for the evaluation of oral chronic toxicity for a group of data-poor organochlorine contaminants sampled from the Lower Passaic River: p,p’-dichlorodiphenyldichloroethane (p,p’-DDD), cis- and trans- nonachlor, and oxychlordane. Briefly, a list of putative structural analogs with available oral reference values was compiled via structure-activity relationship evaluations. Subsequently, metabolic and toxicity information for the structural analogues was compared to the target compounds. Applying a weight of evidence approach, a final surrogate was selected. p,p’-dichlorodiphenyltrichloroethane (p,p’-DDT) and its no-observed-adverse-effect level (NOAEL) of 0.05 mg/kg-day based on liver lesions in rats were proposed for the derivation of chronic surrogate oral reference values for p,p’-DDD. Similarly, chlordane was selected as a surrogate for the nonachlors and oxychlordane, and its NOAEL of 0.15 mg/kg-day for hepatic necrosis in mice was suggested for developing surrogate risk estimates. Toxicokinetic considerations were central to establishing similarity in the read-across assessments, with supporting evidence from structural and toxicity evaluations. In vitro bioactivity data and relative potency factors were used to address uncertainties associated with the surrogate selection and hazard prediction. Altogether, this analysis illustrates the utility of alternative non-testing approaches in support of human health risk assessment of data-poor chemicals.
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