Pilot and Repeat Trials as Development Tools Associated with Demonstration of Bioequivalence

Abstract

The purpose of this work is to use simulated trials to study how pilot trials can be implemented in relation to bioequivalence testing, and how the use of the information obtained at the pilot stage can influence the overall chance of showing bioequivalence (power) or the chance of approving a truly bioinequivalent product (type I error). The work also covers the use of repeat pivotal trials since the difference between a pilot trial followed by a pivotal trial and a pivotal trial followed by a repeat trial is mainly a question of whether a conclusion of bioequivalence can be allowed after the first trial. Repeating a pivotal trial after a failed trial involves dual or serial testing of the bioequivalence null hypothesis, and the paper illustrates how this may inflate the type I error up to almost 10%. Hence, it is questioned if such practice is in the interest of patients. Tables for power, type I error, and sample sizes are provided for a total of six different decision trees which allow the developer to use either the observed geometric mean ratio (GMR) from the first or trial or to assume that the GMR is 0.95. In cases when the true GMR can be controlled so as not to deviate more from unity than 0.95, sequential design methods ad modum Potvin may be superior to pilot trials. The tables provide a quantitative basis for choosing between sequential designs and pivotal trials preceded by pilot trials.

Fig. 1

Decision tree for method 1

Fig. 2

Decision tree for method 6

Fig. 3

Type I error rate as function of coefficient of variation when an initial sample size of 24 subjects is applied at GMR = 0.95. Note that for methods 2, 4, 6, and 8, the type I error rate exceeds 0.05. The maximum standard error was 3.0 × 10⁻⁴, observed for method 1 at CV = 0.1

Fig. 4

Power as function of the coefficient of variation when an initial sample size of 24 subjects is applied at GMR = 0.95. The maximum standard error was 4.9 × 10⁻⁴, observed for method 3 (=7) at CV = 0.1

Fig. 5

Average sample size as function of coefficient of variation when an initial sample size of 24 subjects is applied at GMR = 0.95. Note that methods 3, 4, 7, and 8 are associated with a distinctly higher sample size than methods 1, 2, 5, and 6 since the latter assume a GMR of 0.95 for the planning of the second trial

Fig. 6

Power as function of the GMR for the eight methods when an initial sample size of 24 subjects is applied and when the CV is 0.3. Methods 2, 4, 6 and 8 are generally associated with the highest power, but those are methods that can inflate the type I error due to serial testing for bioequivalence cf. table II. The maximum standard error was 5.0 × 10⁻⁴, observed for methods 5 and 7 at GMR = 0.90