Validation of OECD QSAR Toolbox profilers for genotoxicity assessment of pesticides using the MultiCase genotoxicity database

Quantitative Structure Activity Relationship (QSAR) models are widely used for genotoxicity assessment in regulatory settings. In silico profilers are a special case of models capturing mechanistic insights specific to a particular toxicological endpoint or reflecting chemistry-related attributes that may not be directly associated with a defined mechanism of toxicity. This study explores the accuracy of using such profilers as a lower tier in genotoxicity assessment to inform regulatory concerns. Relevant profilers in the OECD QSAR Toolbox are investigated using an external validation dataset derived from the MultiCASE Genotoxicity database, which contains AMES mutagenicity and in vivo micronucleus (MNT) experimental results. The MNT dataset includes the commercial in vivo MNT dataset expanded with pesticide data from regulatory documents. This analysis incorporates the use of metabolism simulations by the OECD QSAR Toolbox to assess their influence on profiler performance. The present findings show that the absence of profiler alerts correlates well with experimentally negative outcomes. However, the calculated accuracy for the MNT-related and AMES-related profilers varies considerably (41%-78% for MNT-related profilers and 62%-88% for AMES-related profilers using the full set with and without consideration of metabolism). Incorporating metabolism simulations increases accuracy by 4–6% for the full AMES-dataset, and 4–16% for the full MNT-dataset. Together, genotoxicity assessment using the Toolbox profilers should include a critical evaluation of any triggered alerts, considering the overall performance statistics of the profilers presented within this work. Results from third-party QSAR models provide critical insights to complement the expert review of any profiler positive result, as profilers alone are not recommended to be used directly for prediction purpose.