ReviewFrontiers in pharmacology2026
Reduce or not reduce: a practical guide to calculate sample size for various experimental design in studies involving animals.
Review in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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0 citing papers in PubMed.
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Authors and funding
2 authors.
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Abstract
The ethical imperative to reduce the use of animals in scientific experimentation has become increasingly prominent, driven by societal expectations, regulatory frameworks, and concerns regarding the reproducibility of preclinical research. While the principle of Reduction, one of the 3Rs originally defined by Russell and Burch, is widely endorsed, its practical implementation remains challenging. In particular, inappropriate experimental designs, inadequate statistical planning, and insufficient reporting standards continue to undermine both scientific validity and ethical justification, often leading either to the unnecessary use of animals or to underpowered studies whose results lack reliability. This review provides an updated and practical framework for determining the appropriate number of animals required in experimental biology and pharmacology. Building on earlier methodological recommendations, it emphasizes the central role of rigorous study planning, including the clear definition of objectives and primary endpoints, appropriate experimental design, randomization, blinding, and the judicious use of control groups. Special attention is given to factorial designs and the inclusion of interactions, which often allow substantial reductions in animal numbers without compromising statistical power. The review also discusses conditional procedures, pilot studies, interim analyses, and the frequent confusion between biological replicates, technical replicates, and true experimental replication. The statistical foundations of
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