An iterative method to protect the type I error rate in bioequivalence studies under two‐stage adaptive 2×2 crossover designs

Abstract

Bioequivalence studies are the pivotal clinical trials submitted to regulatory agencies to support the marketing applications of generic drug products. Average bioequivalence (ABE) is used to determine whether the mean values for the pharmacokinetic measures determined after administration of the test and reference products are comparable. Two‐stage 2×2 crossover adaptive designs (TSDs) are becoming increasingly popular because they allow making assumptions on the clinically meaningful treatment effect and a reliable guess for the unknown within‐subject variability. At an interim look, if ABE is not declared with an initial sample size, they allow to increase it depending on the estimated variability and to enroll additional subjects at a second stage, or to stop for futility in case of poor likelihood of bioequivalence. This is crucial because both parameters must clearly be prespecified in protocols, and the strategy agreed with regulatory agencies in advance with emphasis on controlling the overall type I error.We present an iterative method to adjust the significance levels at each stage which preserves the overall type I error for a wide set of scenarios which should include the true unknown variability value. Simulations showed adjusted significance levels higher than 0.0300 in most cases with type I error always below 5%, and with a power of at least 80%. TSDs work particularly well for coefficients of variation below 0.3 which are especially useful due to the balance between the power and the percentage of studies proceeding to stage 2. Our approach might support discussions with regulatory agencies.

Finite Sample Corrections for Average Equivalence Testing

“…These recommendations were issued by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) (see e.g., Muñoz et al, 2016; Davit et al, 2012, for more details). The amount of expansion is limited by the authorities, and several recent publications have shown that the TIER can be larger than the nominal level α (see e.g., Wonnemann et al, 2015; Muñoz et al, 2016; Endrenyi and Tothfalusi, 2019; Molins et al, 2021; Schütz et al, 2022, and the references therein) and therefore have proposed different ways to correct for it (see also Labes and Schütz, 2016; Tothfalusi and Endrenyi, 2016; Ocaña and Muñoz, 2019; Deng and Zhou, 2020). These corrections not only ensure that the TIER is smaller than or equal to α , but also lead to acceptance regions that change more smoothly with σ ν .…”

“…This method involves the linear adjustment of equivalence limits based on the value of σ ν within the reference group, while still requiring that falls within the equivalence margins (– c, c ). Despite the authorities’ constraints on the degree of expansion, recent studies have revealed that the TOST can exceed the nominal level α (see, for example, Wonnemann et al, 2015; Muñoz et al, 2016; Endrenyi and Tothfalusi, 2019; Molins et al, 2021; Schütz et al, 2022, and references therein), leading to proposals for correction methods that ensure a level- α test. Moreover, these corrections also result in more seamless changes to the acceptance regions as σ ν varies.…”

“…These recommendations were issued by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA). 20,30 The amount of expansion is limited by the authorities, and several recent publications have shown that the size of the SABE can be larger than the significance level α 20,26,31,32,33 and therefore have proposed different ways to correct for it. 28,34,35,36 These corrections ensure that the size is smaller than or equal to α and lead to acceptance regions that change more smoothly with σ ν .…”

Finite sample corrections for average equivalence testing

“…These recommendations were issued by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) 20,30 . The amount of expansion is limited by the authorities, and several recent publications have shown that the size of the SABE can be larger than the significance level $$$ \alpha $$$ 20,26,31‐33 and therefore have proposed different ways to correct for it 28,34‐36 . These corrections ensure that the size is smaller than or equal to $$$ \alpha $$$ and lead to acceptance regions that change more smoothly with $$$ {\sigma}_{\nu } $$$.…”

Proposing some innovative study design features to regulatory agencies (EMA and FDA) in bioequivalence trials : Reference Scaled Average Bioequivalence, and Two-Stage Adaptive Designs

“…Regulators also allow using two-stage adaptive designs (TSD) with unblinded interim sample size re-estimation based on the usual 2×2 crossover RT/TR design with bioequivalence limits 0.80-1.25 (in the original scale), whose application is becoming increasingly popular. This design is also useful for HVD (7,10,11,(21)(22)(23)(24)(25).…”