Literature DB >> 25995169

Development of population pharmacokinetics model of icotinib with non-linear absorption characters in healthy Chinese volunteers to assess the CYP2C19 polymorphism and food-intake effect.

Pei Hu1, Jia Chen, Dongyang Liu, Xin Zheng, Qian Zhao, Ji Jiang.   

Abstract

PURPOSE: Icotinib is a potent and selective inhibitor of epidermal growth factor receptors (EGFR) approved to treat non-small cell lung cancer (NSCLC). However, its high variability may impede its application. The objectives of this analysis were to assess plasma pharmacokinetics and identify covariates that may explain variability in icotinib absorption and/or disposition following single dose of icotinib in healthy volunteers.
METHODS: Data from two clinical studies (n = 22) were analyzed. One study was designed as three-period and Latin-squared (six sequence) trial to evaluate dose proportionality, and the other one was designed as two-way crossover trial to evaluate food effect on pharmacokinetics (PK) characters. Icotinib concentrations in plasma were analyzed using non-linear mixed-effects model (NONMEM) method. The model was used to assess influence of food, demographic characteristics, measurements of blood biochemistry, and CYP2C19 genotype on PK characters of icotinib in humans. The final model was diagnosed by goodness-of-fit plots and evaluated by visual predictive check (VPC) and bootstrap methods.
RESULTS: A two-compartment model with saturated absorption character was developed to capture icotinib pharmacokinetics. Typical value of clearance, distribution clearance, central volume of distribution, maximum absorption rate were 29.5 L/h, 24.9 L/h, 18.5 L, 122.2 L and 204,245 μg/h, respectively. When icotinib was administrated with food, bioavailability was estimated to be increased by 48%. Inter-occasion variability was identified to affect on maximum absorption rate constant in food-effect study. CL was identified to be significantly influenced by age, albumin concentration (ALB), and CYP2C19 genotype. No obvious bias was found by VPC and bootstrap methods.
CONCLUSIONS: The developed model can capture icotinib pharmacokinetics well in healthy volunteers. Food intake can increase icotinib exposure. Three covariates, age, albumin concentration, and CYP2C19 genotype, were identified to significantly affect icotinib PK profiles in healthy subjects.

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Year:  2015        PMID: 25995169     DOI: 10.1007/s00228-015-1864-5

Source DB:  PubMed          Journal:  Eur J Clin Pharmacol        ISSN: 0031-6970            Impact factor:   2.953


  21 in total

1.  Bootstrap approach for constructing confidence intervals for population pharmacokinetic parameters. II: A bootstrap modification of standard two-stage (STS) method for phase I trial.

Authors:  A Yafune; M Ishiguro
Journal:  Stat Med       Date:  1999-03-15       Impact factor: 2.373

2.  Bootstrap approach for constructing confidence intervals for population pharmacokinetic parameters. I: A use of bootstrap standard error.

Authors:  A Yafune; M Ishiguro
Journal:  Stat Med       Date:  1999-03-15       Impact factor: 2.373

3.  Icotinib: kick-starting the Chinese anticancer drug industry.

Authors:  D Ross Camidge
Journal:  Lancet Oncol       Date:  2013-08-13       Impact factor: 41.316

4.  Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions.

Authors:  Radojka M Savic; Mats O Karlsson
Journal:  AAPS J       Date:  2009-08-01       Impact factor: 4.009

5.  Development of a population pharmacokinetic model to describe azithromycin whole-blood and plasma concentrations over time in healthy subjects.

Authors:  T Pene Dumitrescu; T Anic-Milic; K Oreskovic; J Padovan; K L R Brouwer; P Zuo; V D Schmith
Journal:  Antimicrob Agents Chemother       Date:  2013-04-29       Impact factor: 5.191

6.  Phase I trial of icotinib, a novel epidermal growth factor receptor tyrosine kinase inhibitor, in Chinese patients with non-small cell lung cancer.

Authors:  Han-ping Wang; Li Zhang; Yin-xiang Wang; Fen-lai Tan; Ying Xia; Guan-jun Ren; Pei Hu; Ji Jiang; Meng-zhao Wang; Yi Xiao
Journal:  Chin Med J (Engl)       Date:  2011-07-05       Impact factor: 2.628

Review 7.  Clinical relevance of genetic polymorphisms in the human CYP2C subfamily.

Authors:  J A Goldstein
Journal:  Br J Clin Pharmacol       Date:  2001-10       Impact factor: 4.335

8.  Quantitative determination of icotinib in human plasma and urine using liquid chromatography coupled to tandem mass spectrometry.

Authors:  Dongyang Liu; Ji Jiang; Pei Hu; Fenlai Tan; Yingxiang Wang
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2009-09-24       Impact factor: 3.205

Review 9.  Current methods for predicting human food effect.

Authors:  Kimberley A Lentz
Journal:  AAPS J       Date:  2008-05-24       Impact factor: 4.009

10.  Effect of the CYP2C19 genotype on the pharmacokinetics of icotinib in healthy male volunteers.

Authors:  Can-Jun Ruan; Dong-Yang Liu; Ji Jiang; Pei Hu
Journal:  Eur J Clin Pharmacol       Date:  2012-05-15       Impact factor: 2.953

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  3 in total

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Authors:  Devender Kodati; Harish Kaushik Kotakonda; Narsimhareddy Yellu
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-08       Impact factor: 2.441

2.  A Phase I Study of the Safety and Pharmacokinetics of Higher-Dose Icotinib in Patients With Advanced Non-Small Cell Lung Cancer.

Authors:  Jian Liu; Lihua Wu; Guolan Wu; Xingjiang Hu; Huili Zhou; Junchun Chen; Meixiang Zhu; Wei Xu; Fenlai Tan; Lieming Ding; Yinxiang Wang; Jianzhong Shentu
Journal:  Oncologist       Date:  2016-10-27

3.  Population pharmacokinetic modeling of flurbiprofen, the active metabolite of flurbiprofen axetil, in Chinese patients with postoperative pain.

Authors:  Jingru Zhang; Hong Zhang; Libo Zhao; Jian Gu; Yi Feng; Haiyan An
Journal:  J Pain Res       Date:  2018-11-30       Impact factor: 3.133

  3 in total

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