Literature DB >> 18446515

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

Barbara M Davit1, 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.   

Abstract

INTRODUCTION: It is widely believed that acceptable bioequivalence studies of drugs with high within-subject pharmacokinetic variability must enroll higher numbers of subjects than studies of drugs with lower variability. We studied the scope of this issue within US generic drug regulatory submissions.
MATERIALS AND METHODS: We collected data from all in vivo bioequivalence studies reviewed at FDA's Office of Generic Drugs (OGD) from 2003-2005. We used the ANOVA root mean square error (RMSE) from bioequivalence statistical analyses to estimate within-subject variability. A drug was considered highly variable if its RMSE for C (max) and/or AUC was > or =0.3. To identify factors contributing to high variability, we evaluated drug substance pharmacokinetic characteristics and drug product dissolution performance. RESULTS AND DISCUSSION: In 2003-2005, the OGD reviewed 1,010 acceptable bioequivalence studies of 180 different drugs, of which 31% (57/180) were highly variable. Of these highly variable drugs, 51%, 10%, and 39% were either consistently, borderline, or inconsistently highly variable, respectively. We observed that most of the consistent and borderline highly variable drugs underwent extensive first pass metabolism. Drug product dissolution variability was high for about half of the inconsistently highly variable drugs. We could not identify factors causing variability for the other half. Studies of highly variable drugs generally used more subjects than studies of lower variability drugs.
CONCLUSION: About 60% of the highly variable drugs we surveyed were highly variable due to drug substance pharmacokinetic characteristics. For about 20% of the highly variable drugs, it appeared that formulation performance contributed to the high variability.

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Year:  2008        PMID: 18446515      PMCID: PMC2751460          DOI: 10.1208/s12248-008-9015-x

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  4 in total

1.  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

Review 2.  The bioequivalence of highly variable drugs and drug products.

Authors:  K K Midha; M J Rawson; J W Hubbard
Journal:  Int J Clin Pharmacol Ther       Date:  2005-10       Impact factor: 1.366

Review 3.  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

4.  Evaluation of bioequivalence of highly variable drugs using clinical trial simulations. II: Comparison of single and multiple-dose trials using AUC and Cmax.

Authors:  A A el-Tahtawy; T N Tozer; F Harrison; L Lesko; R Williams
Journal:  Pharm Res       Date:  1998-01       Impact factor: 4.200

  4 in total
  27 in total

1.  Summary workshop report: Facilitating oral product development and reducing regulatory burden through novel approaches to assess bioavailability/bioequivalence.

Authors:  James E Polli; Jack A Cook; Barbara M Davit; Paul A Dickinson; Domenick Argenti; Nancy Barbour; Alfredo García-Arieta; Jean-Marie Geoffroy; Kerry Hartauer; Shoufeng Li; Amitava Mitra; Francis X Muller; Vivek Purohit; Manuel Sanchez-Felix; John W Skoug; Kin Tang
Journal:  AAPS J       Date:  2012-06-09       Impact factor: 4.009

Review 2.  Challenges and opportunities in achieving bioequivalence for fixed-dose combination products.

Authors:  Amitava Mitra; Yunhui Wu
Journal:  AAPS J       Date:  2012-06-09       Impact factor: 4.009

3.  Use of partial AUC to demonstrate bioequivalence of Zolpidem Tartrate Extended Release formulations.

Authors:  Robert A Lionberger; Andre S Raw; Stephanie H Kim; Xinyuan Zhang; Lawrence X Yu
Journal:  Pharm Res       Date:  2012-01-26       Impact factor: 4.200

4.  Summary workshop report: bioequivalence, biopharmaceutics classification system, and beyond.

Authors:  James E Polli; Bertil S I Abrahamsson; Lawrence X Yu; Gordon L Amidon; John M Baldoni; Jack A Cook; Paul Fackler; Kerry Hartauer; Gordon Johnston; Steve L Krill; Robert A Lipper; Waseem A Malick; Vinod P Shah; Duxin Sun; Helen N Winkle; Yunhui Wu; Hua Zhang
Journal:  AAPS J       Date:  2008-08-05       Impact factor: 4.009

Review 5.  Evaluation of bioequivalence for highly variable drugs with scaled average bioequivalence.

Authors:  Laszlo Tothfalusi; Laszlo Endrenyi; Alfredo Garcia Arieta
Journal:  Clin Pharmacokinet       Date:  2009       Impact factor: 6.447

6.  Pharmacokinetics of Orally Inhaled Drug Products.

Authors:  Günther Hochhaus; Stephen Horhota; Leslie Hendeles; Sandra Suarez; Juliet Rebello
Journal:  AAPS J       Date:  2015-03-12       Impact factor: 4.009

7.  Biopharmaceutical considerations and characterizations in development of colon targeted dosage forms for inflammatory bowel disease.

Authors:  Rajkumar Malayandi; Phani Krishna Kondamudi; P K Ruby; Deepika Aggarwal
Journal:  Drug Deliv Transl Res       Date:  2014-04       Impact factor: 4.617

Review 8.  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

Review 9.  Implementation of a reference-scaled average bioequivalence approach for highly variable generic drug products by the US Food and Drug Administration.

Authors:  Barbara M Davit; Mei-Ling Chen; Dale P Conner; Sam H Haidar; Stephanie Kim; Christina H Lee; Robert A Lionberger; Fairouz T Makhlouf; Patrick E Nwakama; Devvrat T Patel; Donald J Schuirmann; Lawrence X Yu
Journal:  AAPS J       Date:  2012-09-13       Impact factor: 4.009

10.  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

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