Abstract
<jats:p>As interest in the quantitative interpretation of genotoxicity assay data continues to grow, the Ames bacterial mutagenicity assay offers a valuable opportunity due to its long-standing use and extensive dose-response data sets. A key challenge for quantitative use of this data is determining how best to apply benchmark dose (BMD) analysis to Ames data to support a quantitative risk assessment. This requires careful selection of both an appropriate benchmark response (BMR) and the most suitable modeling approach. Using an in-house database of Ames bacterial mutagenicity test data from regulatory submissions, we evaluate a range of BMRs and several benchmark modeling approaches. Our evaluation indicates that a 50% increase in revertants over the background (BMR50) is a strong candidate BMR for Ames studies in the pesticides regulatory context. Furthermore, in this regulatory data set, the Bayesian implementations (BMABMDR Laplace approximation and Bridge sampling) yielded acceptable BMD estimates for a larger proportion of data sets according to EFSA’s acceptability criteria, with narrower confidence intervals, than the PROAST implementation. Together, these findings provide a practical framework for deriving quantitative potency estimates from Ames mutagenicity data, enabling more robust and informative assessments of mutagenic risk in both regulatory and research settings.</jats:p>