ArticleArchives of toxicology2024
Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice.
Article in Archives of toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Demonstrating the reliability of in vivo metabolomics-based chemical grouping: Part 2 - Consistency of group-specific metabolic effects.Archives of toxicology · 2026Article
- The important role of standards for the uptake of transcriptomics and metabolomics based in vitro methods in regulatory toxicology.Archives of toxicology · 2025Review
- Comparison of popular enrichment methods for untargeted in vitro metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Guidance on the use of read-across for chemical safety assessment in food and feed.EFSA journal. European Food Safety Authority · 2025Article
- Advancing human health risk assessment: the role of new approach methodologies.Frontiers in toxicology · 2025Review
- Molecular similarity: Theory, applications, and perspectives.Artificial intelligence chemistry · 2024Article
- Utilizing Omics Data for Chemical Grouping.Environmental toxicology and chemistry · 2024Article
- Multi-omics bioactivity profile-based chemical grouping and read-across: a case study with Daphnia magna and azo dyes.Archives of toxicology · 2024Article
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.
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Registered trials
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