ORIGINAL RESEARCH article

Front. Toxicol.

Sec. Regulatory Toxicology

Perspectives on Variability of In Vivo Toxicology Studies: Considerations for Next-generation Toxicology

  • 1. Inotiv, Research Triangle Park, NC, United States

  • 2. Syngenta Crop Protection LLC, Greensboro, United States

  • 3. Independent expert, Durham, United States

  • 4. Institute for Medical Biochemistry, Medical University Innsbruck, Innsbruck, Austria

  • 5. International Collaboration on Cosmetics Safety, Research Triangle Park, NC, United States

  • 6. National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods,, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States

  • 7. Division of Program Coordination, Planning, and Strategic Initiatives, Office of the Director, National Institutes of Health, Research Triangle Park, NC, United States

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Abstract

Animal studies have historically informed toxicological testing and safety assessments. However, assessment of the variability in both quantitative and qualitative results has been limited. Biological variability, experimental differences, interpretation of categorical endpoints, and data availability and curation approaches all contribute to the quantified variability. This review summarizes published investigations of variability within mammalian toxicological studies that have been largely conducted in accordance with health effects test guidelines. While any test system will have inherent variability, understanding its sources and impact on study interpretation will help ensure that appropriate confidence is applied when using the test method. Furthermore, such information aids in establishing relevant metrics to serve as baselines for informing performance characterization of new approach methodologies (NAMs). The results of this review suggest that replicability of in vivo toxicological guideline studies varies widely by study type, endpoint complexity, and classification approach. Future evaluation of NAMs should be contextualized using estimates of uncertainty and variance of the traditional study data to demonstrate "better" performance compared to traditional testing approaches. Robust understanding of guideline study performance is important for risk assessments, where it is important to find species-relevant NAMs that can perform at least as well as existing bioassays.

Summary

Keywords

Generalizability, NAM evaluation, Performance metrics, replicability, Risk Assessment, variability

Received

30 December 2025

Accepted

30 January 2026

Copyright

© 2026 Karmaus, Kreutz, Oyetade, Paul Friedman, Paparella, Reinke, Allen, Hogberg and Kleinstreuer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Helena Therese Hogberg

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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