Literature DB >> 9755880

Individual bioequivalence: attractive in principle, difficult in practice.

L Endrenyi1, G L Amidon, K K Midha, J P Skelly.   

Abstract

Keywords:  Non-programmatic

Mesh:

Year:  1998        PMID: 9755880     DOI: 10.1023/a:1011972732530

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


× No keyword cloud information.
  8 in total

1.  The basis for individual bioequivalence. FDA Population and Individual Bioequivalence Working Group.

Authors:  R L Williams; R N Patnaik; M L Chen
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2000 Jan-Mar       Impact factor: 2.441

2.  Subject-by-formulation interaction in bioequivalence: conceptual and statistical issues. FDA Population/Individual Bioequivalence Working Group. Food and Drug Administration.

Authors:  W W Hauck; T Hyslop; M L Chen; R Patnaik; R L Williams
Journal:  Pharm Res       Date:  2000-04       Impact factor: 4.200

3.  Subject-by-formulation interaction in determinations of individual bioequivalence: bias and prevalence.

Authors:  L Endrenyi; L Tothfalusi
Journal:  Pharm Res       Date:  1999-02       Impact factor: 4.200

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.  Bioequivalence of highly variable drugs: a comparison of the newly proposed regulatory approaches by FDA and EMA.

Authors:  Vangelis Karalis; Mira Symillides; Panos Macheras
Journal:  Pharm Res       Date:  2011-12-28       Impact factor: 4.200

6.  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

7.  Statistical aspects of bioequivalence testing between two medicinal products.

Authors:  E Zintzaras
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2005 Jan-Jun       Impact factor: 2.441

8.  Spline functions in convolutional modeling of verapamil bioavailability and bioequivalence. I: conceptual and numerical issues.

Authors:  J Popović
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2006 Apr-Jun       Impact factor: 2.441

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.