Dybdal, Noël
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Publication An Opportunity to Decrease Data Variability and to Improve Study Reproducibility: Animal Welfare and Allostatic State in Biomedical Research(2022-01-01) Dybdal, NoëlConcern over reliability of experimental study results is growing. Quality of data from animal model studies investigating mechanisms of diseases and response to disease intervention are of particular concern. Poor quality of published animal data has been cited as a significant contributor to clinical trial failure. Given that animal studies are foundational in guiding understanding of basic biological systems and informing investment decisions in development of new medicines, the societal costs of setting a low bar for reproducibility in animal studies is high. Current discussions on ways to improve research reproducibility focus principally on physical study design parameters, including power calculations in determination of appropriate group size, randomization procedures, and reporting bias. While attention to these elements is clearly important, a holistic approach which includes enhanced attention to animal welfare offers the greatest opportunity for improvement. The cumulative effects of stressful conditions experienced by animals throughout their entire lifecycle (rearing, transport, experimental conditions) on their physiological and psychological resilience are underappreciated study variables. The impact of chronic stress on resilience is referred to specifically as the allostatic state while the cost of adaptation to chronic stress is referred to as allostatic load. Animal welfare science provides the foundation for understanding how to reduce allostatic load and enhance positive welfare. In this presentation, I will advance a proposal that investment in conditions that reduce the allostatic load and support a positive welfare state of laboratory animals will result in more robust study outcomes.