Evidence map›Paper›PMID 41350941›Full record

ArticleArchives of toxicology2026

Interlaboratory clinical chemistry parameter variation in seven-day acute hydrazine toxicity studies in the Sprague-Dawley rat.

Janonna Kadyrov, Samuele Sala, Lucy Grigoroff, Reika Masuda, Samantha Lodge, Timothy M Ebbels, Michael D Reily, Donald Robertson, Lois Lehman-McKeeman, John Shockcor and 6 more

Abstract read
In one paragraph

Article in Archives of toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Janonna KadyrovCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
Samuele SalaCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
Lucy GrigoroffCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
Reika MasudaCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
Samantha LodgeCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
Timothy M EbbelsDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.
Michael D ReilyFormerly Pfizer Global R&D, Ann Arbor, MI, USA.
Donald RobertsonFormerly Pfizer Global R&D, Ann Arbor, MI, USA.
Lois Lehman-McKeemanFormerly Bristol-Myers-Squibb Company, Princeton, NJ, USA.
John ShockcorFormerly Drug Metabolism and Pharmacokinetics Section, Stine-Haskell Research Center, Dupont Pharmaceuticals Company, Newark, DE, USA.
Bruce D CarFormerly Bristol-Myers-Squibb Company, Princeton, NJ, USA.
Craig ThomasThomaPharma Consulting LLC, McCordsville, IN, 46055, USA.
John C LindonDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Julien WistCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia. Julien.wist@murdoch.edu.au.
Jeremy K NicholsonInstitute of Global Health Innovation, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK. j.nicholson@imperial.ac.uk.
Elaine HolmesCentre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia. elaine.holmes@imperial.ac.uk.ORCID 0000-0002-0556-8389

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical chemistry retains its position as a cornerstone of toxicological assessment, yet inter-laboratory variability in baseline values remains a challenge for the integration and interpretation of multisite datasets. This study leveraged a publicly available clinical chemistry database to assess the impact of inter-laboratory variability in response to hydrazine-induced steatosis. Seventeen clinical chemistry and physico-chemical parameters were evaluated in response to a single dose of hydrazine (at 30 mg/kg or 90 mg/kg) administered to Sprague-Dawley rats (n = 83) across five different pharmaceutical companies and compared with sham-dosed control animals. Hydrazine exposure produced a distinct and consistent biochemical signature at 48 h post-dose across the combined sample set from all laboratory sites, characterised by increased serum bilirubin and BUN and decreased serum protein concentrations, alongside atypical reductions in ALT and AST due to transaminase inhibition. Despite sizable inter-laboratory differences in response when considering single assays, multivariate analysis of the complete dataset was able to extract a core pathological response signature. Early changes at 24 h post-dose in AST, ALT, total protein, and calcium demonstrated strong predictive value for 48-h toxicity profiles (AUROC 0.98), underscoring the translational potential of early biomarkers. This study highlights both the robustness and contextual limitations of clinical chemistry data in toxicological studies. It underscores the importance of matched-control designs and multivariate approaches for multisite studies and advocates for the integration of early predictive modelling to optimise study design and align with the principles of the Replace, Reduce, and Refine initiative.

Indexed as

Clinical Chemistry TestsHydrazinesLaboratoriesToxicity Tests, AcuteAnimalsMaleRatsRats, Sprague-DawleyhydrazineHydrazinesClinical chemistryHydrazine toxicityMultisite studySprague-Dawley

Identifiers

PMID41350941
PMCPMC12967443

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.