Determining the optimal sample size for a study assures an adequate power to detect statistical significance. Hence, it is a critical step in the design of a planned research protocol. Using too many participants in a study is expensive and exposes more number of subjects to procedure. Similarly, if study is underpowered, it will be statistically inconclusive and may make the whole protocol a failure. This paper covers the essentials in calculating sample size for highly variable drug study designs. Sample size computation for highly variable drugs was done incompliance to the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA) for reference scaled average bioequivalence (RSABE) studies. To elucidate the complicated features and the relationship between sample size, within-subject variability of reference product, within subject standard deviation of reference product and intra-subject variability comparing test versus reference products. Partial replicate (reference replicate) and full replicate studies were simulated in estimating the sample size for yielding 80% and 90% statistical powers.
