Literature DB >> 22162308

Viewpoint: observations on scaled average bioequivalence.

Scott D Patterson1, Byron Jones.   

Abstract

The two one-sided test procedure (TOST) has been used for average bioequivalence testing since 1992 and is required when marketing new formulations of an approved drug. TOST is known to require comparatively large numbers of subjects to demonstrate bioequivalence for highly variable drugs, defined as those drugs having intra-subject coefficients of variation greater than 30%. However, TOST has been shown to protect public health when multiple generic formulations enter the marketplace following patent expiration. Recently, scaled average bioequivalence (SABE) has been proposed as an alternative statistical analysis procedure for such products by multiple regulatory agencies. SABE testing requires that a three-period partial replicate cross-over or full replicate cross-over design be used. Following a brief summary of SABE analysis methods applied to existing data, we will consider three statistical ramifications of the proposed additional decision rules and the potential impact of implementation of scaled average bioequivalence in the marketplace using simulation. It is found that a constraint being applied is biased, that bias may also result from the common problem of missing data and that the SABE methods allow for much greater changes in exposure when generic-generic switching occurs in the marketplace.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 22162308     DOI: 10.1002/pst.498

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  5 in total

Review 1.  Bioequivalence for highly variable drugs: regulatory agreements, disagreements, and harmonization.

Authors:  Laszlo Endrenyi; Laszlo Tothfalusi
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-02-23       Impact factor: 2.745

2.  Inflation of Type I Error in the Evaluation of Scaled Average Bioequivalence, and a Method for its Control.

Authors:  Detlew Labes; Helmut Schütz
Journal:  Pharm Res       Date:  2016-08-01       Impact factor: 4.200

3.  Likelihood approach for evaluating bioequivalence of highly variable drugs.

Authors:  Liping Du; Leena Choi
Journal:  Pharm Stat       Date:  2014-11-19       Impact factor: 1.894

4.  Reference Datasets for Studies in a Replicate Design Intended for Average Bioequivalence with Expanding Limits.

Authors:  Helmut Schütz; Detlew Labes; Michael Tomashevskiy; Mario González-de la Parra; Anastasia Shitova; Anders Fuglsang
Journal:  AAPS J       Date:  2020-02-07       Impact factor: 4.009

5.  Pharmacogenetic selection of volunteers increases stringency of bioequivalence studies; the case of clopidogrel.

Authors:  J Garcés-Eisele; A Ruiz-Argüelles; Larisa Estrada-Marín; Virginia Reyes-Núñez; R Vázquez-Pérez; Olga Guzmán-García; R Coutiño-Medina; Leticia Acosta-Sandria; Beatriz Cedillo-Carvallo
Journal:  Indian J Pharm Sci       Date:  2014-07       Impact factor: 0.975

  5 in total

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