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. 2025 Aug 21;15(1):30745.
doi: 10.1038/s41598-025-15935-4.

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

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

Hugh G G Townsend et al. Sci Rep. .

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.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
A Randomized Complete Block Design challenge trial using 16 animals; four cages, four treatment groups, one animal per treatment group in each cage. A Two-way ANOVA showing significant differences in tissue virus concentrations among the vaccine groups (p < 0.0001) after controlling for the effect of Cage (horizontal bars denote mean values). B Two-way ANOVA showing significant differences among cages (p = 0.048) after controlling for the effect of vaccination due to a significant difference between cages 1 and 3 (p = 0.0454, horizontal bars denote mean values). (C). Consistency plot of the differences in virus concentration by cage and vaccine, showing the relatively constant differences within and between cages by vaccine.

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