Challenges and Considerations on Sample Size Estimation in Preclinical Discovery Research: Replace, Reduce, Refine

• Activity Number: 371
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Catherine Tuglus* and Lei Zhou
• Companies: Amgen and Amgen
• Keywords: Sample Size ; Preclinical ; Discovery Research ; Consulting

Abstract

The application of sample size calculation and power analysis in preclinical discovery research is not a straightforward task. Unlike its clinical counterpart, where sample size calculations are standard procedure, the utility of sample size calculations is less clear in the preclinical world. Here we present a selection of case studies of sample size calculation and power analysis application in preclinical discovery research in the biotechnology field. We include both in vitro and in vivo studies in a variety of therapeutic research areas. We will discuss challenges faced by statisticians advising in the field, including working within 3R principles (Replace, Reduce, Refine), educating scientists on the relevance of sample size calculations and addressing multiple testing considerations, resource limitations, historical precedence, and the reliance on a p-value measure of success.