Read-Across Methodology in Toxicological Risk Assessment

Abstract

Grouping approaches like read-across (RAx) are one of the most widely used methods to fill data gaps in human risk assessment. In a RAx approach, in vivo animal data from one to several source substances are extrapolated to a target substance that has not been tested. Here, we describe the currently accepted read-across workflow, which begins with the problem formulation that defines the level of the acceptable uncertainty. The evaluation progresses iteratively from an initial list of structurally similar substances to source compounds with similar toxicodynamic and toxicokinetic properties. Finally, the data gap is closed with a worst-case or a regression analysis, and the uncertainty of the prediction is identified. New approach methodologies, such as in vitro assays and in silico models, have great potential to strengthen read-across assessments by providing mechanistic data and estimates of bioavailability of the grouped compounds.