Critical Remarks on Reference-Scaled Average Bioequivalence

Abstract

Purpose: More than a decade ago the option to assess highly variable drugs / drug products by reference-scaled average bioequivalence was introduced in regulatory practice. Recommended approaches differ between jurisdictions and may lead to different conclusions even for the same data set. According to our knowledge, implemented methods have not been directly compared for their operating characteristics (Type I Error and power). Methods: We performed Monte Carlo simulations to assess the consumer risk and the clinically relevant difference for the recommended regulatory settings. Results: In all methods for reference-scaled average bioequivalence the Type I Error can be inflated with a consequently compromised consumer risk. Furthermore, the clinically relevant difference could vary between studies performed with the same reference product. Conclusions: Only average bioequivalence with fixed – widened – limits would both maintain the consumer risk and offer an unambiguously defined clinically not relevant difference. As long as such an approach is not implemented in regulatory practice, we recommend adjusting the level of the test a.

Finite sample corrections for average equivalence testing

“…Figure 4 presents the data, collected via a simple paired design, in which each pig delivered two skin samples respectively treated with one of the two drugs of interest. Such designs, possibly attractive for studies not involving regulators, are stricto sensu incompatible with the use of design‐specific SABE‐like corrections 26 and therefore interesting to showcase the advantages of our design‐agnostic method. In order to assess bioequivalence of both topical treatments, the TOST and $$$ \alpha $$$‐TOST procedures, based on a paired $$$ t $$$‐test statistic considering ECZ levels on the logarithmic scale, are conducted using $$$ c={\delta}_U=-{\delta}_L=\log (1.25)\approx 0.223 $$$.…”

Finite Sample Corrections for Average Equivalence Testing

“…Figure 4 presents the data, collected via a simple paired design, in which each pig delivered two skin samples respectively treated with one of the two drugs of interest. Such designs, possibly attractive for studies not involving regulators, are stricto sensu incompatible with the use of design-specific SABE-like corrections 26 and therefore interesting to showcase the advantages of our design-agnostic method. In order to assess bioequivalence of both topical treatments, the TOST and α -TOST procedures, based on a paired t -test statistic considering ECZ levels on the logarithmic scale, are conducted using c = δ U = − δ L = log(1.25) ≈ 0.223.…”

“…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 tests cannot be assessed using the IIP and the last two are difficult to interpret due to the use of polar coordinates. 25 In the specific context of average bioequivalence testing in replicated crossover designs 26 for highly variable drugs, i.e., for cases with relatively large σ ν , regulatory authorities have recommended an alternative approach based on the linear scaling of the bioequivalence limits according to the value of the standard deviation within the reference group, called Scaled Average BioEquivalence (SABE), 27 also referred to as Average BioEquivalence with Expanding limits (ABEL) in some references, 26,28,29 with the constraint that p θ lies within the bioequivalence margins p´c, cq. These recommendations were issued by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA).…”