Literature DB >> 21209240

Effect of different durations and formulations of diltiazem on the single-dose pharmacokinetics of midazolam: how long do we go?

Evan J Friedman1, Iain P Fraser, Ying-Hong Wang, Arthur J Bergman, Chi-Chung Li, Patrick J Larson, Jeffrey Chodakewitz, John A Wagner, S Aubrey Stoch.   

Abstract

Understanding how inhibition of cytochrome P4503A (CYP3A) affects the metabolism of a new drug is critical in determining if a clinically relevant drug interaction will occur. Diltiazem interaction studies assess a given compound's sensitivity to moderate CYP3A inhibition. The present study compared the effect different durations and formulations of diltiazem (extended release [XR] and conventional release [CR]) had on the single-dose pharmacokinetics of midazolam. The geometric mean ratio (GMR; midazolam + diltiazem(XR × 5 days)/midazolam + diltiazem(XR × 2 days)) for midazolam AUC(0-∞) was 0.98 (90% confidence interval [CI], 0.87, 1.10). The GMR (midazolam + diltiazem(XR × 2 days)/midazolam + diltiazem(CR × 2 days)) for midazolam AUC(0-∞) was 0.82 (90% CI, 0.73, 0.92). Simcyp simulations accurately predicted the observed clinical results only when a hepatic CYP3A degradation rate (k(deg)) different from that provided by the software was used. The data suggest that dosing diltiazem XR for 2 days predicts the change in midazolam AUC as reliably as 5 days of XR dosing and 2 days of CR dosing. In addition, the authors believe that a hepatic CYP3A kdeg of 0.03 h(-1) should be considered for future Simcyp studies.

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Year:  2011        PMID: 21209240     DOI: 10.1177/0091270010387141

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


  6 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

2.  Drug-drug interaction study of ACT-178882, a new renin inhibitor, and diltiazem in healthy subjects.

Authors:  Jasper Dingemanse; Laurent Nicolas
Journal:  Clin Drug Investig       Date:  2013-03       Impact factor: 2.859

Review 3.  Drug-drug interaction studies: regulatory guidance and an industry perspective.

Authors:  Thomayant Prueksaritanont; Xiaoyan Chu; Christopher Gibson; Donghui Cui; Ka Lai Yee; Jeanine Ballard; Tamara Cabalu; Jerome Hochman
Journal:  AAPS J       Date:  2013-03-30       Impact factor: 4.009

4.  Population Pharmacokinetic Modeling of Diltiazem in Chinese Renal Transplant Recipients.

Authors:  Xiao-Feng Guan; Dai-Yang Li; Wen-Jun Yin; Jun-Jie Ding; Ling-Yun Zhou; Jiang-Lin Wang; Rong-Rong Ma; Xiao-Cong Zuo
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2018-02       Impact factor: 2.441

5.  Modeling of rifampicin-induced CYP3A4 activation dynamics for the prediction of clinical drug-drug interactions from in vitro data.

Authors:  Fumiyoshi Yamashita; Yukako Sasa; Shuya Yoshida; Akihiro Hisaka; Yoshiyuki Asai; Hiroaki Kitano; Mitsuru Hashida; Hiroshi Suzuki
Journal:  PLoS One       Date:  2013-09-24       Impact factor: 3.240

6.  Simulation and Prediction of the Drug-Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling.

Authors:  D Zhou; K Bui; M Sostek; N Al-Huniti
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-04-16
  6 in total

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