A systematic assessment of preclinical multilaboratory studies and a comparison to single laboratory studies
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Abstract
Background: Multicentric approaches are widely used in clinical trials to assess the generalizability of findings, however, they are novel in laboratory-based experimentation. It is unclear how multilaboratory studies may differ in conduct and results from single lab studies. Here, we synthesized the characteristics of these studies and quantitatively compared their outcomes to those generated by single laboratory studies. Methods: MEDLINE and Embase were systematically searched. Screening and data extractions were completed in duplicate by independent reviewers. Multilaboratory studies investigating interventions using in vivo animal models were included. Study characteristics were extracted. Systematic searches were then performed to identify single lab studies matched by intervention and disease. Difference in standardized mean differences (DSMD) was then calculated across studies to assess differences in effect estimates based on study design (>0 indicates larger effects in single lab studies). Results: Sixteen multilaboratory studies met inclusion criteria and were matched to 100 single lab studies. The multicenter study design was applied across a diverse range of diseases, including stroke, traumatic brain injury, myocardial infarction, and diabetes. The median number of centers was four (range 2–6) and the median sample size was 111 (range 23–384) with rodents most frequently used. Multilaboratory studies adhered to practices that reduce the risk of bias significantly more often than single lab studies. Multilaboratory studies also demonstrated significantly smaller effect sizes than single lab studies (DSMD 0.72 [95% confidence interval 0.43–1]). Conclusions: Multilaboratory studies demonstrate trends that have been well recognized in clinical research (i.e. smaller treatment effects with multicentric evaluation and greater rigor in study design). This approach may provide a method to robustly assess interventions and the generalizability of findings between laboratories. Funding: uOttawa Junior Clinical Research Chair; The Ottawa Hospital Anesthesia Alternate Funds Association; Canadian Anesthesia Research Foundation; Government of Ontario Queen Elizabeth II Graduate Scholarship in Science and Technology
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A recent systematic review of the biomedical literature found only sixteen examples of multicenter animal studies.
“As a striking example of this limitation, a recent systematic review of the biomedical literature found only sixteen examples of multicenter animal studies (Hunniford et al., 2023).”
From Estimating the replicability of Brazilian biomedical science (2025) · cites this paper as Hunniford et al., 2023
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Estimating the replicability of Brazilian biomedical science
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“As a striking example of this limitation, a recent systematic review of the biomedical literature found only sixteen examples of multicenter animal studies (Hunniford et al., 2023).”
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Reproducibility failure in biomedical research: problems and solutions
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Animal research in cardiac arrest
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Testing the limits: can enhanced external validity promote translation?
MacLellan, A., & Lalu, M. M. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.105473 · Cited by 3 · see citing works
Self-citationStrengthening translational preclinical research through confirmatory multi-laboratory studies
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Investigating the Use of Companion Animal Donor Tissue Banks
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Estimating the replicability of Brazilian biomedical sciencePreprint
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Estimating the replicability of Brazilian biomedical sciencePreprint
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Data Analysis Planning and Reporting for Confirmatory Multi‐Lab Preclinical Trials: A Tutorial
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- Authors
- Hunniford, V. T., Grudniewicz, A., Fergusson, D. A., Montroy, J., Grigor, E., Lansdell, C., Lalu, M. M., & On behalf of The Canadian Critical Care Translational Biology Group
- Affiliations
- University of Ottawa (CA)
- Ottawa Hospital Research Institute (CA)
- Corresponding author
- Lalu, Manoj M
- ORCID
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2023-03-09
- Volume
- 12
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC10168693
- OpenAlex
- W4323652355
- Cited by
- 26
- References
- 79
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 3 · 2023: 1
- FWCI
- 1.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- QEII Scholarship (Graduate Student Scholarship)
- Canadian Anesthesia Research Foundation (Career Scientist Award)
- Topics
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- multicenter study, preclinical animal models, in vivo animal models, effect size comparison, risk of bias, generalizability of findings, rodent models, stroke, traumatic brain injury, myocardial infarction, diabetes mellitus, standardized mean difference
- MeSH terms
- Humans, Myocardial Infarction, Ontario, Multicenter Studies as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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