Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Abstract

To facilitate the practical implementation of the guidance on the residue definition for dietary risk assessment, EFSA has organized an evaluation of applicability of existing in silico models for predicting the genotoxicity of pesticides and their metabolites, including analysis of the impact on genotoxicity of the metabolic structural changes. The prediction ability of (Q)SARs for in vitro and in vivo tests were evaluated. For the Ames test, all (Q)SAR models generated statistically significant predictions, comparable with the experimental variability of the test; instead, the reliability of the (Q)SAR models for assays / endpoints different from in vitro bacterial mutagenicity appears to be quite far from optimality. Secondly, two new Read Across approaches were applied to predict Ames mutagenicity and in vitro Chromosomal Aberrations: Read Across was largely successful for predicting the Ames test results, but much less for in vitro Chromosomal Aberrations. The worse results for endpoints different from Ames may be attributable to the several revisions of experimental protocols and evaluation criteria of results that have made the databases qualitatively non‐homogeneous, and poorly suitable for modelling. A third dimension of this research is the evaluation of the impact of the structural changes‐in result of metabolic or degradation processes‐on the genotoxic potential of the substances. Parent/Metabolite structural differences (beyond the known Structural Alerts) that may, or may not cause changes in the Ames mutagenicity were identified and catalogued. In addition, Structural Alerts analysis applied under human expert supervision permitted the rationalization of the large majority of the changes of patterns of genotoxicity. The findings from this work are suitable for being integrated into Weight‐of‐Evidence and Tiered evaluation schemes. The importance of the human expert knowledge is particularly emphasized.

Outcome of the pesticides peer review meeting on general recurring issues in mammalian toxicology

“…ii. External against the EFSA Genotoxicity Pesticides Database (around 67% sensitivity, around 89% specificity, see Figure 21 in Benigni et al, 2019). d. Domains: The compounds in the dataset are primarily small and medium-sized chemicals and so are representative of the structures used to build the model.…”

“…A stepwise approach using all the methodology investigated for assessment of genotoxicity of pesticides was developed. External scientific report presenting the above mentioned project is available on the EFSA website (Benigni R et al, 2019).…”

“…ii. External against the EFSA Genotoxicity Pesticides Database (around 60% sensitivity, around 85% specificity, see Figure 21 in Benigni et al, 2019). d. Domains: The model was built using dataset of 4337 molecular structures with corresponding Ames test data (2401 mutagens and 1936 non-mutagens) The model is applicable to heterogenous chemicals and defined an applicability domain index.…”

(Q)SAR tools for the prediction of mutagenic properties: Are they ready for application in pesticide regulation?

“…Scientific publications and guidance documents (e.g. by European Chemicals Agency (ECHA) and OECD) [28][29][30][31][32] recommend the combined use of both system types to minimise the number of false-positive or false-negative predictions for chemicals. With implementation of the ICH M7 guideline Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk (Q)SAR can, in the absence of adequate data, be also used to assess the mutagenic potential of impurities in the approval process for pharmaceuticals.…”

“…Sarah Nexus or Derek Nexus) predicted a substance to be mutagenic meeting the acceptance criteria described above. 31 For negative overall predictions both Derek and Sarah Nexus results were taken into account. Only when Derek Nexus as well as Sarah Nexus predicted a substance to be non-mutagenic was this prediction considered reliably convincing.…”