Literature DB >> 10471980

FDA evaluations using in vitro metabolism to predict and interpret in vivo metabolic drug-drug interactions: impact on labeling.

B Davit1, K Reynolds, R Yuan, F Ajayi, D Conner, E Fadiran, B Gillespie, C Sahajwalla, S M Huang, L J Lesko.   

Abstract

Recent advances in in vitro metabolism methods have led to an improved ability to predict clinically relevant metabolic drug-drug interactions. To address the relationships of in vitro metabolism data and in vivo metabolism outcomes, the Office of Clinical Pharmacology and Biopharmaceutics in the Center for Drug Evaluation and Research, Food and Drug Administration, evaluated a number of recently approved new drug applications. The goal of these evaluations was to determine the contribution of in vitro metabolism data in (1) predicting in vivo drug-drug interactions, (2) determining the need to conduct an in vivo drug-drug interaction study, and (3) incorporating findings into drug product labeling. Ten cases are presented in this article. They fall into two major groups: (1) in vitro data were predictive of in vivo results, and (2) in vitro data were not predictive of in vivo results. Discussion of these cases highlights factors limiting predictability of in vivo metabolic interactions from in vitro metabolism data. The integration of these findings into drug product labeling is also discussed.

Mesh:

Year:  1999        PMID: 10471980     DOI: 10.1177/00912709922008515

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  14 in total

Review 1.  Manufacturer's drug interaction and postmarketing adverse event data: what are appropriate uses?

Authors:  W K Kraft; S A Waldman
Journal:  Drug Saf       Date:  2001       Impact factor: 5.606

Review 2.  Do drug metabolism and pharmacokinetic departments make any contribution to drug discovery?

Authors:  Dennis Smith; Esther Schmid; Barry Jones
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

Review 3.  Database analyses for the prediction of in vivo drug-drug interactions from in vitro data.

Authors:  Kiyomi Ito; Hayley S Brown; J Brian Houston
Journal:  Br J Clin Pharmacol       Date:  2004-04       Impact factor: 4.335

4.  Predicting drug candidate victims of drug-drug interactions, using microdosing.

Authors:  Marie Croft; Brendan Keely; Ian Morris; Lan Tann; Graham Lappin
Journal:  Clin Pharmacokinet       Date:  2012-04-01       Impact factor: 6.447

5.  The effect of ketoconazole on the in vivo intestinal permeability of fexofenadine using a regional perfusion technique.

Authors:  Christer Tannergren; Tina Knutson; Lars Knutson; Hans Lennernäs
Journal:  Br J Clin Pharmacol       Date:  2003-02       Impact factor: 4.335

Review 6.  Clinical Implications of P-Glycoprotein Modulation in Drug-Drug Interactions.

Authors:  Marie Lund; Tonny Studsgaard Petersen; Kim Peder Dalhoff
Journal:  Drugs       Date:  2017-05       Impact factor: 9.546

7.  Artemisinin and thiabendazole are potent inhibitors of cytochrome P450 1A2 (CYP1A2) activity in humans.

Authors:  Tashinga E Bapiro; Jane Sayi; Julia A Hasler; Mary Jande; Gerald Rimoy; Amos Masselle; Collen M Masimirembwa
Journal:  Eur J Clin Pharmacol       Date:  2005-10-29       Impact factor: 2.953

8.  Quantitative drug interactions prediction system (Q-DIPS): a dynamic computer-based method to assist in the choice of clinically relevant in vivo studies.

Authors:  P Bonnabry; J Sievering; T Leemann; P Dayer
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

9.  Transport characteristics of fexofenadine in the Caco-2 cell model.

Authors:  Niclas Petri; Christer Tannergren; David Rungstad; Hans Lennernäs
Journal:  Pharm Res       Date:  2004-08       Impact factor: 4.200

10.  Identification of human cytochrome P(450)s that metabolise anti-parasitic drugs and predictions of in vivo drug hepatic clearance from in vitro data.

Authors:  Xue-Qing Li; Anders Björkman; Tommy B Andersson; Lars L Gustafsson; Collen M Masimirembwa
Journal:  Eur J Clin Pharmacol       Date:  2003-08-12       Impact factor: 2.953

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