Validating Methods that Promote Reduction and Refinement in Laboratory Animal Science

Walker, Michael
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University of Guelph

Millions of animals are used in biomedical research each year. Unfortunately, much of the research performed on them is likely spurious and non-replicable, making their use ethically questionable. There is, thus, an ethical imperative to improve the quality of scientific research being conducted, in addition to the well-known mandates to reduce the number of animals being used, and to improve the welfare of those individuals that are being used. In this work I contribute to these obligations by first validating ‘mixed-strain housing’: an example of a split-plot experimental design that allows many fewer animals to be used without compromising statistical power. Accordingly, no welfare issues were created by housing mice of different strains together, nor were there adverse effects in terms of data quality. Furthermore, when mice of different coat colours are housed together, they no longer need to be individually identified via aversive marking techniques. I then implement this housing paradigm successfully when validating that crossing a floor electrified by increasing magnitude of current represents a perceived cost for mice, and as such that it can then be used to measure motivation by assessing how much they would be ‘willing to pay’ to access preferred resources. I highlight the potential advantages this has over other means of imposing resource access costs, and then implement it when assessing mouse preferences for two commercially available running wheels: Bio Serv®‘s ‘fast-trac’ wheel combo and a stainless steel mesh 5” upright wheel by Ware Manufacturing Inc. In addition, the welfare significance and anatomical impact of the two wheels are quantified, and I ultimately recommend that of the two, the ‘fast-trac’ wheel is better for laboratory mice. Finally, I argue that the false discovery rate of a test is much more meaningful and informative than a p-value, and demonstrate how exactly the (expected) false discovery rate can be used to plan experiments that are likely to find significant effects while avoiding spurious results, thus ensuring that animals are not being wasted. Overall, this thesis provides validated methods that contribute to the ongoing goals of reduction and refinement.

Welfare, Experimental Design, Mice, Reduction, Refinement