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Preclinical pilot studies: Five common pitfalls and how to avoid them
Natasha A Karp1, Alan Sharpe2, Benjamin Phillips1
1Data Sciences & Quantitative Biology, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
Abstract:
Pilots are small-scale initial experiments that are intended to guide the design of future, larger studies, with a view to increasing their effectiveness. In this statistical primer we highlight five common mistakes that limit the utility of pilot studies and provide practical guidance to avoid such errors and increase their effectiveness. The common thread connecting these mistakes is insufficient planning and over-interpretation of the results. This approach compromises the ultimate goals of the research programme and the future experimental cascade. In support of our view that over-interpretation is an error, we present a simple simulation to demonstrate that pilots will generally generate an inaccurate estimate of the variability of the biological endpoint under study and that frequent under-estimation will lead to inconclusive and unethical subsequent experiments. We argue that well planned pilots are an important part of the research cascade and still need to be implemented to a high standard.
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