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<p>This review comprehensively examines the variability and uncertainty associated with test guideline (TG)-conform genotoxicity data and explores the respective implications for the integration of non-animal-methods (NAMs) into regulatory frameworks. Historical amendments to OECD TGs are mapped to reveal the method’s evolution that improves the scientific quality of the data but also explains data heterogeneity within available databases. An analysis of the major genotoxicity databases ECVAM, ISSMIC, and OASIS demonstrates substantial variability in genotoxicity calls. Using the EFSA genotoxicity database, which currently harbours the best-curated (meta-) data, we estimate that 22–77% of compounds exhibit similarity of replicate results below 85%, depending on the assay. The potentially most important variables statistically explaining variability and sensitivity were analysed. The practical limitations to identify them with high reliability and to define their optimum needs to be accepted as a qualitative baseline uncertainty. These findings underscore the necessity of contextualizing NAM performance evaluations within the intrinsic variability and uncertainty of animal and in vitro reference data. We propose that this variability is explicitly considered in the development and validation of NAM-based Integrated Approaches for Testing and Assessment. This review provides a critical foundation for regulators and scientists aiming to enhance the acceptance and utility of NAMs in genotoxicity assessment.</p>

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Variability and uncertainty of data from genotoxicity test guidelines: what we know and why it matters

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月17日

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  • Giuseppa Raitano,
  • Tessa E. Pronk,
  • Chiara L. Battistelli,
  • Cecilia Bossa,
  • Vasiliki Hatzi,
  • Dimitra Nikolopoulou,
  • Evgenia Chaideftou,
  • Olga Tcheremenskaia,
  • Christelle Adam-Guillermin,
  • Marc Audebert,
  • Birgit Mertens,
  • Martin Paparella

摘要

This review comprehensively examines the variability and uncertainty associated with test guideline (TG)-conform genotoxicity data and explores the respective implications for the integration of non-animal-methods (NAMs) into regulatory frameworks. Historical amendments to OECD TGs are mapped to reveal the method’s evolution that improves the scientific quality of the data but also explains data heterogeneity within available databases. An analysis of the major genotoxicity databases ECVAM, ISSMIC, and OASIS demonstrates substantial variability in genotoxicity calls. Using the EFSA genotoxicity database, which currently harbours the best-curated (meta-) data, we estimate that 22–77% of compounds exhibit similarity of replicate results below 85%, depending on the assay. The potentially most important variables statistically explaining variability and sensitivity were analysed. The practical limitations to identify them with high reliability and to define their optimum needs to be accepted as a qualitative baseline uncertainty. These findings underscore the necessity of contextualizing NAM performance evaluations within the intrinsic variability and uncertainty of animal and in vitro reference data. We propose that this variability is explicitly considered in the development and validation of NAM-based Integrated Approaches for Testing and Assessment. This review provides a critical foundation for regulators and scientists aiming to enhance the acceptance and utility of NAMs in genotoxicity assessment.