Literature DB >> 29193123

Physiologically Based Pharmacokinetic Modeling to Evaluate the Systemic Exposure of Gefitinib in CYP2D6 Ultrarapid Metabolizers and Extensive Metabolizers.

Yingxue Chen1, Diansong Zhou1, Weifeng Tang2, Wangda Zhou1, Nidal Al-Huniti1, Eric Masson1.   

Abstract

Gefitinib is a selective inhibitor of epidermal growth factor receptor (EGFR) tyrosine kinase and is used for the treatment of non-small-cell lung cancer (NSCLC) with activating EGFR mutations. Gefitinib is metabolized by CYP2D6 and CYP3A4. This analysis compared the systemic exposure of gefitinib after oral administration in CYP2D6 ultrarapid metabolizers (UM) vs extensive metabolizers (EM). Physiologically based pharmacokinetic (PBPK) modeling was conducted using a population-based simulator. The model was calibrated using itraconazole-gefitinib clinical drug-drug interaction data and validated with gefitinib data in CYP2D6 EM vs poor metabolizers (PM). System components of the PBPK model were evaluated using published clinical metoprolol pharmacokinetic data in CYP2D6 UM, EM, and PM. Our PBPK model predicted a gefitinib geometric least-squares mean area under the plasma concentration-time curve (AUC) from time 0 to 264 hours (AUC(0-264) ) ratio in the presence vs absence of itraconazole of 1.85, similar to the ratio of 1.78 from clinical study data. Predicted and observed metoprolol geometric least-squares mean AUC(0-24) ratios in UM vs EM were also similar (0.46 and 0.55, respectively), suggesting that system components related to CYP2D6 in the PBPK model were properly established. In addition, the PBPK model also captured gefitinib pharmacokinetic profiles in CYP2D6 polymorphic populations. The final PBPK model predicted a decrease in gefitinib AUC of ∼39% in CYP2D6 UM vs EM. Such changes in exposure will have limited impact as the reduced exposure is still above gefitinib's in vitro IC90 for EGFR activating mutations in NSCLC patients.
© 2017, The American College of Clinical Pharmacology.

Entities:  

Keywords:  CYP2D6; PBPK; gefitinib; itraconazole; pharmacogenetics

Mesh:

Substances:

Year:  2017        PMID: 29193123     DOI: 10.1002/jcph.1036

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


  3 in total

1.  Association of Variability and Pharmacogenomics With Bioequivalence of Gefitinib in Healthy Male Subjects.

Authors:  Hong Zhang; Qingmei Li; Xiaoxue Zhu; Min Wu; Cuiyun Li; Xiaojiao Li; Chengjiao Liu; Zhenwei Shen; Yanhua Ding; Shucheng Hua
Journal:  Front Pharmacol       Date:  2018-08-07       Impact factor: 5.810

2.  Evaluation of the Drug-Drug Interaction Potential of Acalabrutinib and Its Active Metabolite, ACP-5862, Using a Physiologically-Based Pharmacokinetic Modeling Approach.

Authors:  Diansong Zhou; Terry Podoll; Yan Xu; Ganesh Moorthy; Karthick Vishwanathan; Joseph Ware; J Greg Slatter; Nidal Al-Huniti
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-05-12

3.  A Transcriptomic Approach to Elucidate the Mechanisms of Gefitinib-Induced Toxicity in Healthy Human Intestinal Organoids.

Authors:  Daniela Rodrigues; Bram Herpers; Sofia Ferreira; Heeseung Jo; Ciarán Fisher; Luke Coyle; Seung-Wook Chung; Jos C S Kleinjans; Danyel G J Jennen; Theo M de Kok
Journal:  Int J Mol Sci       Date:  2022-02-17       Impact factor: 5.923

  3 in total

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