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Each ring-trial partner applied their preferred metabolomics workflows to acquire, process, quality assess and statistically analyse their data. All five partners whose datasets passed quality control correctly clustered the substances into three groups according to previously established toxicological effects, both for female and male rats. However, to ensure high confidence in each grouping hypothesis, metabolomics data should support a plausible toxicological interpretation by linking changes in annotated metabolite profiles to known toxicological effects associated with the substances. In this follow-up study, our first data-driven objective was to determine the consistency of group-specific discriminatory metabolites (including lipids) across partners. For all six cases (three groups in female and male rats), statistically significant consistency was observed, confirming that all partners discovered similar metabolic perturbations underpinning each group. Strikingly, this was achieved even though a range of statistical and computational approaches were used for both discovering and annotating discriminatory metabolites. Secondly, we evaluated whether pre-existing toxicological knowledge, organised using an Adverse Outcome Pathway-informed framework of metabolomic associative events (mAEs), could provide plausible toxicological interpretations of the partner\u2019s discriminatory metabolite profiles, for each toxicological effect (androgen receptor activity (AR), peroxisome proliferation (PP), anaemia). Binomial distribution analysis revealed statistically significant detection of characteristic mAEs for all six cases, albeit with insufficient specificity across the three effects. Consequently, a third objective was developed, to refine the mAEs by combining the pre-existing toxicological knowledge with partner-to-partner detection reproducibility of metabolites and their directional change, thereby significantly enhancing mAE detection specificity. Overall, the discovery by the five partners of significantly consistent metabolic perturbations underpinning each group further demonstrates the reliability of metabolomics for chemical grouping. Moreover, an integrated knowledge and data-driven approach is presented as a basis for deriving metabolomic signatures that were used to support plausible toxicological interpretations of the metabolomics data. Considering the broader implications of this study, we propose the development of a collaborative framework to facilitate community-driven contributions to a shared knowledgebase of metabolomic signatures.<\/jats:p>","DOI":"10.1007\/s00204-026-04570-1","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T08:33:32Z","timestamp":1791362012000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Demonstrating the reliability of in vivo metabolomics-based chemical grouping: Part 2 \u2013 Consistency of group-specific metabolic effects"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7989-6695","authenticated-orcid":false,"given":"G. 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Dr Aniko Kende, Ms Florence Lai and Mrs Lauraine Swindale are employees of Syngenta, a company which conducts and uses metabolomics studies to assess the toxicity and\/or justify grouping and read-across of chemicals for the purpose of registration and marketing. Dr Volker Haake and Prof. Hennicke Kamp (until March 31st, 2026) are employees of BASF Metabolome Solutions GmbH, a company which conducts metabolome analysis for various clients. Dr Franziska Zickgraf is an employee of BASF SE, a company which conducts and uses metabolomics studies to assess the toxicity and\/or justify grouping and read-across of chemicals for the purpose of registration and marketing. Prof. Mark Viant is an employee of the University of Birmingham and founder and director of Michabo Health Science Limited, a spin-out company of the University of Birmingham providing scientific consultancy services in \u2018omics technologies and computational toxicology. The other authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The views expressed in this paper are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency (EPA) and other participating organisations. Mention of trade names or products does not convey, and should not be interpreted as conveying, official EPA (and other participating organisations) approval, endorsement or recommendation.","order":3,"name":"Ethics","label":"Disclaimer","group":{"name":"EthicsHeading","label":"Declarations"}}]}}