Tradition, Not Science, Is the Basis of Animal Model Selection in Translational and Applied Research

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Abstract

National and international laws and regulations exist to protect animals used for scientific purposes in translational and applied research, which includes drug development. However, multiple animal models are available for each disease. We evaluated the argumentation behind the selection of a specific animal model using thematic content analysis in project applications issued in 2017-2019 in the Netherlands. In total, 125 animal models for translational and applied research from 110 project applications were assessed. Explanations to select a specific model included: the model’s availability (79%); the availability of expertise (62%); and the model showing similar disease pathology/symptoms (59%) to humans. Therefore, current selection of a specific animal model seems to be based on tradition rather than its potential predictive value for clinical outcome. The applicants’ explanations for the implementation of the 3R principles (replacement, reduction and refinement) as to the animal model were unspecific. Replacement was achieved by using data from prior in vitro studies, reduction by optimal experimental design and statistics, and refinement by reducing discomfort. Additionally, due to the stated need for a test model with high complexity (47%) and intactness (30%), the full replacement of animal models with alternative (non-live animal) approaches was thought unachievable. Without a clear, systematic and transparent justification for the selection of a specific animal model, the likelihood of poorly translatable research remains. It is not only up to the researcher to demonstrate this, as ethical committees and funding bodies can provide positive stimuli to drive this change.

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Veening-Griffioen, D. H., Ferreira, G. S., Boon, W. P. C., Gispen-De Wied, C. C., Schellekens, H., Moors, E. H. M., & van Meer, P. J. K. (2021). Tradition, Not Science, Is the Basis of Animal Model Selection in Translational and Applied Research. Altex, 38(1), 49–62. https://doi.org/10.14573/altex.2003301

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