Testing bioequivalence for multiple formulations with power and sample size calculations.
Bioequivalence (BE) trials play an important role in drug development for demonstrating the BE between test and reference formulations. The key statistical analysis for BE trials is the use of two one-sided tests (TOST), which is equivalent to showing that the 90% confidence interval of the relative bioavailability is within a given range. Power and sample size calculations for the comparison between one test formulation and the reference formulation has been intensively investigated, and tables and software are available for practical use. From a statistical and logistical perspective, it might be more efficient to test more than one formulation in a single trial. However, approaches for controlling the overall type I error may be required. We propose a method called multiplicity-adjusted TOST (MATOST) combining multiple comparison adjustment approaches, such as Hochberg's or Dunnett's method, with TOST. Because power and sample size calculations become more complex and are difficult to solve analytically, efficient simulation-based procedures for this purpose have been developed and implemented in an R package. Some numerical results for a range of scenarios are presented in the paper. We show that given the same overall type I error and power, a BE crossover trial designed to test multiple formulations simultaneously only requires a small increase in the total sample size compared with a simple 2 × 2 crossover design evaluating only one test formulation. Hence, we conclude that testing multiple formulations in a single study is generally an efficient approach. The R package MATOST is available at https://sites.google.com/site/matostbe/.
Novartis Pharmaceuticals Corp., One Health Plaza, East Hanover, NJ, USA. zhengcheng@gmail.com
Cheng
C
Zheng
Jixian
J
Wang
Lihui
L
Zhao
D018849:Controlled Clinical Trials as Topic / Q000379:methods*; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D015195:Drug Design; D006801:Humans; D012107:Research Design; D012984:Software; D013810:Therapeutic Equivalency