Evidence map›Paper›PMID 40841741›Full record

ArticleScientific reports2025

A call to action to address critical flaws and bias in laboratory animal experiments and preclinical research.

Hugh G G Townsend, Klaus Osterrieder, Murray D Jelinski, Douglas W Morck, Cheryl L Waldner, William R Cox, Volker Gerdts, Andrew A Potter, Lorne A Babiuk, James C Cross

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
–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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Review
  6. Article
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

10 authors.

Hugh G G TownsendDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine (Emeritus) and Vaccine and Infectious Disease Organization (Retired), University of Saskatchewan, Saskatoon, SK, Canada. hugh.townsend@usask.ca.
Klaus OsterriederUniversity of Veterinary Medicine Hannover, Foundation, Hannover, Germany.
Murray D JelinskiDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Douglas W MorckDepartment of Biological Sciences, Faculty of Science, University of Calgary, Calgary, AB, Canada.
Cheryl L WaldnerDepartment of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
William R CoxAmphoraxe Life Sciences, 4103 Parkway Dr, Vancouver, BC, V6L 3C9, Canada.
Volker GerdtsVaccine and Infectious Disease Organization and Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Andrew A PotterDepartment of Veterinary Microbiology (Emeritus), Western College of Veterinary Medicine and Vaccine and Infectious Disease Organization (Retired), University of Saskatchewan, Saskatoon, SK, Canada.
Lorne A BabiukDepartment of Veterinary Microbiology (Emeritus), Western College of Veterinary Medicine and Vaccine and Infectious Disease Organization (Retired), University of Saskatchewan, Saskatoon, SK, Canada.
James C CrossFaculty of Veterinary Medicine (Emeritus), University of Calgary, Calgary, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the design of hypothesis-driven, comparative laboratory animal experiments, investigators must control for cage effects, ensure full blinding and full randomization while adhering to established experimental designs, notably variations of the Completely Randomized Design and the Randomized Block Designs. Failure to meet these criteria introduces partial or complete confounding by multiple known and unknown variables, resulting in biased outcome measures and rendering valid statistical analysis impossible. Our analysis of a stratified, random sample of comparative laboratory animal experiments conducted in North America and Europe and published in 2022, shows that as few as 0-2.5% utilized valid, unbiased experimental designs. The failure of investigators to adopt valid, unbiased study designs undermines scientific rigour, squanders resources and animal lives, and impedes the reliable translation of preclinical research findings to human and veterinary medicine. We propose practical, achievable solutions focused on enhancing the rigour and validity of study designs. This includes developing a specialized group of scientists with expertise in the design of laboratory animal experiments and data analysis, to ensure future studies are conducted with the highest scientific standards.

Indexed as

Animal ExperimentationAnimals, LaboratoryBiomedical ResearchResearch DesignAnimalsBiasEuropeHumans

Identifiers

PMID40841741
PMCPMC12371031

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.