Choosing Confidence Intervals in Bioequivalence Studies: 100(1 - 2\(\alpha\) )% and 100(1 - \(\alpha\) )% Approaches
Kexuan Li *
Global Biometrics and Data Sciences Bristol Myers Squibb, Cambridge, Massachusetts, US.
Susie Sinks
Global Analytics and Data Sciences, Biogen, Cambridge, Massachusetts, US.
Peng Sun
Global Analytics and Data Sciences, Biogen, Cambridge, Massachusetts, US.
Lingli Yang
Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, Massachusetts, US.
*Author to whom correspondence should be addressed.
Abstract
A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assigned to receive two formulations. The two formulations are then compared with respect to their pharmacokinetic profiles, which encompass the absorption, distribution, metabolism, and elimination of the drug. Under the guidance from Food and Drug Administration (FDA), for a size-\(\alpha\) bioequivalence test, the standard approach is to construct a 100(1 - 2\(\alpha\))% confidence interval and verify if the confidence interval falls with the critical region. In this work, we clarify that 100(1-2\(\alpha\))% confidence interval approach for bioequivalence testing yields a size-\(\alpha\) test only when the two one-sided tests in TOST are "equal-tailed". Furthermore, a 100(1 - \(\alpha\))% confidence interval approach is also discussed in the bioequivalence study.
Keywords: Bioequivalence study, two one-sided tests, confidence interval