Extension of the EFSA Pesticides Genotoxicity Database - SA08 (EFSA GenotoxDB)
06/2022-06/2024
Funding programme / funding institution: Europäische Behörde für Lebensmittelsicherheit (EFSA) - Italien
Grant number: GP/EFSA/AMU/2020/02-SA08
Project homepage: -
Project description:
The results of the project on evaluation of the performance of the existing (Q)SAR models and read across methodologies for prediction of genotoxicity of pesticides finalised in March 2019 showed that: for the prediction of point mutation (Ames test) in silico tools “[…] generated statistically significant predictions, comparable with the experimental variability of the test […] whereas the reliability of the predictions for the other endpoints appears to be far from the optimal to be used for regulatory purpose”. Besides gene mutations in bacteria, tests for clastogenicity/aneugenicity in mammalian cells (e.g. chromosomal aberration and micronucleus tests) are required by regulation. However, data requirements for metabolites and impurities are less stringent than for active substances. According to Regulation (EC) 283/2013 “supplementary studies, where they relate to substances other than the active substance, are not a routine requirement”. Therefore, in silico tools remain a valuable alternative or a complementing tool for the evaluation of the clastogenic/aneugenic potential of chemicals (other than the active substance) but need improvement in order to be routinely used in the regulatory risk assessment. One of the issues are the availability and quality of the data used for the development and testing of these tools.
The current project aims to i) extend the genotoxicity database with curated experimental data for relevant endpoints with a particular interest in the in vitro micronucleus (MN) test (OECD TG 487, 2016) while, ii) also include data extracted by BfR for the bacterial reverse mutation test (Ames test, OECD TG 471) and; iii) validate the database considering the latest changes in the experimental protocol and evaluation criteria of the results.
Therefore, the proposed project would provide additional curated data for further analysis of the reasons of low performance of the in silico tools for endpoints different than Ames mutagenicity.