Literature DB >> 30798390

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

Laszlo Endrenyi1, Laszlo Tothfalusi2.   

Abstract

Regulatory authorities introduced procedures in the last decade for evaluating the bioequivalence (BE) for highly variable drugs. These approaches are similar in principle but differ in details. For example, the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) recommend differing regulatory constants. The constant suggested by FDA results in discontinuity of the BE limits around the switching variation at 30% observed within-subject variation of the reference product. The regulatory constant of EMA does not have these problems. The Type I error reaches 6-7% around the switching variation with the EMA constant but 16-17% with the FDA constant. Various procedures were recently suggested, especially for the EMA approach, to eliminate the inflation of the Type I error. Notably, the so-called Exact algorithms try to amalgamate the positive features of both EMA and FDA procedures without their negative sides. The computational procedure for the EMA approach is simple and has a straightforward interpretation. The procedure for the FDA approach is based on an approximation, has a bias at small degrees of freedom, and requires a suitable computer program. All regulatory agencies impose a second requirement constraining the point estimate of the ratio of geometric means. In addition, EMA and Health Canada impose an upper limit for applying the recommended procedures. These expectations have psychological motivation and political rationale but no scientific foundations. Their inclusion results in incorrect and misleading interpretation of the principal criterion which involves confidence intervals. Different regulatory authorities expect to apply their approaches either to both AUC and Cmax or only to AUC or only to Cmax. Rational resolution of the disharmonization is needed.

Entities:  

Keywords:  Bioequivalence; Highly variable drugs; Reference-scaled average bioequivalence; Regulatory constants; Type I error

Mesh:

Substances:

Year:  2019        PMID: 30798390     DOI: 10.1007/s10928-019-09623-w

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  28 in total

1.  A small sample confidence interval approach to assess individual bioequivalence.

Authors:  T Hyslop; F Hsuan; D J Holder
Journal:  Stat Med       Date:  2000-10-30       Impact factor: 2.373

2.  Evaluation of the bioequivalence of highly-variable drugs and drug products.

Authors:  L Tothfalusi; L Endrenyi; K K Midha; M J Rawson; J W Hubbard
Journal:  Pharm Res       Date:  2001-06       Impact factor: 4.200

3.  Kullback-Leibler divergence for evaluating bioequivalence.

Authors:  Vladimir Dragalin; Valerii Fedorov; Scott Patterson; Byron Jones
Journal:  Stat Med       Date:  2003-03-30       Impact factor: 2.373

4.  Limits for the scaled average bioequivalence of highly variable drugs and drug products.

Authors:  Laszlo Tothfalusi; Laszlo Endrenyi
Journal:  Pharm Res       Date:  2003-03       Impact factor: 4.200

5.  Novel scaled average bioequivalence limits based on GMR and variability considerations.

Authors:  Vangelis Karalis; Mira Symillides; Panos Macheras
Journal:  Pharm Res       Date:  2004-10       Impact factor: 4.200

6.  Geometric mean ratio-dependent scaled bioequivalence limits with leveling-off properties.

Authors:  Vangelis Karalis; Panos Macheras; Mira Symillides
Journal:  Eur J Pharm Sci       Date:  2005-09       Impact factor: 4.384

7.  Novel scaled bioequivalence limits with leveling-off properties.

Authors:  John Kytariolos; Vangelis Karalis; Panos Macheras; Mira Symillides
Journal:  Pharm Res       Date:  2006-10-18       Impact factor: 4.200

Review 8.  Bioequivalence approaches for highly variable drugs and drug products.

Authors:  Sam H Haidar; Barbara Davit; Mei-Ling Chen; Dale Conner; LaiMing Lee; Qian H Li; Robert Lionberger; Fairouz Makhlouf; Devvrat Patel; Donald J Schuirmann; Lawrence X Yu
Journal:  Pharm Res       Date:  2007-09-22       Impact factor: 4.200

9.  Highly variable drugs: observations from bioequivalence data submitted to the FDA for new generic drug applications.

Authors:  Barbara M Davit; Dale P Conner; Beth Fabian-Fritsch; Sam H Haidar; Xiaojian Jiang; Devvrat T Patel; Paul R H Seo; Keri Suh; Christina L Thompson; Lawrence X Yu
Journal:  AAPS J       Date:  2008-03-05       Impact factor: 4.009

10.  Bioequivalence of endogenous substances facing homeostatic equilibria: an example with potassium.

Authors:  A Marzo; D Vuksic; F Crivelli
Journal:  Pharmacol Res       Date:  2000-12       Impact factor: 7.658

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2.  An In Vitro-In Vivo Simulation Approach for the Prediction of Bioequivalence.

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Journal:  Materials (Basel)       Date:  2021-01-24       Impact factor: 3.623

3.  Influence of Gender, Body Mass Index, and Age on the Pharmacokinetics of Itraconazole in Healthy Subjects: Non-Compartmental Versus Compartmental Analysis.

Authors:  Milijana N Miljković; Nemanja Rančić; Aleksandra Kovačević; Bojana Cikota-Aleksić; Ivan Skadrić; Vesna Jaćević; Momir Mikov; Viktorija Dragojević-Simić
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