Literature DB >> 22660440

Prediction of the tacrolimus population pharmacokinetic parameters according to CYP3A5 genotype and clinical factors using NONMEM in adult kidney transplant recipients.

Nayoung Han1, Hwi-yeol Yun, Jin-yi Hong, In-Wha Kim, Eunhee Ji, Su Hyun Hong, Yon Su Kim, Jongwon Ha, Wan Gyoon Shin, Jung Mi Oh.   

Abstract

PURPOSE: Tacrolimus is a commonly used immunosuppressant in solid organ transplantation recipients, but it is characterized by a narrow therapeutic range and large inter-individual variability. The purpose of this study was to establish a population pharmacokinetic (PK) model of tacrolimus and evaluate the influence of clinical covariates, including the genetic polymorphisms of the cytochrome P450 3A5 gene (CYP3A5) and gene encoding P-glycoprotein (ABCB1), on the PK parameters in adult Korean kidney transplant recipients.
METHODS: Clinical data were collected retrospectively for 400 days after the initiation of a tacrolimus-based immunosuppression therapy. Data from 2,788 trough blood samples obtained from 80 subjects were used to perform a population PK analysis with a nonlinear mixed-effect model (NONMEM).
RESULTS: The estimated population mean values of clearance (CL/F) and volume of distribution (V/F) were 22.9 L/h and 716 L, respectively, and the k(a) was fixed to 4.5 h⁻¹. The CYP3A5 genotype, hematocrit level, and post-operative days were identified as the main covariates that influence CL/F, and body weight was found to have a significant effect on V/F. Other covariates, including ABCB1 genotype, corticosteroid dosage, sex, and other clinical data, did not contribute to the pharmacokinetics of tacrolimus.
CONCLUSIONS: This tacrolimus population PK model will be a valuable tool in developing rational guidelines and provides a basis for individualized therapy after kidney transplantation in clinical settings of Korea.

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Year:  2012        PMID: 22660440     DOI: 10.1007/s00228-012-1296-4

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


  37 in total

Review 1.  Genetic contribution to variable human CYP3A-mediated metabolism.

Authors:  Jatinder K Lamba; Yvonne S Lin; Erin G Schuetz; Kenneth E Thummel
Journal:  Adv Drug Deliv Rev       Date:  2002-11-18       Impact factor: 15.470

2.  Relationship of FK506 whole blood concentrations and efficacy and toxicity after liver and kidney transplantation.

Authors:  R P Kershner; W E Fitzsimmons
Journal:  Transplantation       Date:  1996-10-15       Impact factor: 4.939

3.  The genetic determinants of the CYP3A5 polymorphism.

Authors:  E Hustert; M Haberl; O Burk; R Wolbold; Y Q He; K Klein; A C Nuessler; P Neuhaus; J Klattig; R Eiselt; I Koch; A Zibat; J Brockmöller; J R Halpert; U M Zanger; L Wojnowski
Journal:  Pharmacogenetics       Date:  2001-12

4.  The influence of genetic polymorphisms of cytochrome P450 3A5 and ABCB1 on starting dose- and weight-standardized tacrolimus trough concentrations after kidney transplantation in relation to renal function.

Authors:  Michel Mourad; Pierre Wallemacq; Martine De Meyer; Dimitri Brandt; Valérie Van Kerkhove; Jacques Malaise; Djamila Chaïb Eddour; Dominique Lison; Vincent Haufroid
Journal:  Clin Chem Lab Med       Date:  2006       Impact factor: 3.694

5.  Population pharmacokinetics of tacrolimus and CYP3A5, MDR1 and IL-10 polymorphisms in adult liver transplant patients.

Authors:  D Li; W Lu; J-Y Zhu; J Gao; Y-Q Lou; G-L Zhang
Journal:  J Clin Pharm Ther       Date:  2007-10       Impact factor: 2.512

6.  Interindividual variability and tissue-specificity in the expression of cytochrome P450 3A mRNA.

Authors:  Ina Koch; Regina Weil; Renzo Wolbold; Jürgen Brockmöller; Elisabeth Hustert; Oliver Burk; Andreas Nuessler; Peter Neuhaus; Michel Eichelbaum; Ulrich Zanger; Leszek Wojnowski
Journal:  Drug Metab Dispos       Date:  2002-10       Impact factor: 3.922

Review 7.  Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation.

Authors:  Christine E Staatz; Susan E Tett
Journal:  Clin Pharmacokinet       Date:  2004       Impact factor: 6.447

8.  C2 (2-h) levels are not superior to trough levels as estimates of the area under the curve in tacrolimus-treated renal-transplant patients.

Authors:  Kaj Jørgensen; Johan Povlsen; Søren Madsen; Melvin Madsen; Hans Hansen; Asger Pedersen; Else-Marie Heinsvig; Jørgen Poulsen
Journal:  Nephrol Dial Transplant       Date:  2002-08       Impact factor: 5.992

9.  Impact of cytochrome p450 3A5 genetic polymorphism on tacrolimus doses and concentration-to-dose ratio in renal transplant recipients.

Authors:  Eric Thervet; Dany Anglicheau; Barry King; Marie-Hélène Schlageter; Bruno Cassinat; Philippe Beaune; Christophe Legendre; Ann K Daly
Journal:  Transplantation       Date:  2003-10-27       Impact factor: 4.939

10.  Population pharmacokinetics of tacrolimus in adult kidney transplant recipients.

Authors:  Christine E Staatz; Charlene Willis; Paul J Taylor; Susan E Tett
Journal:  Clin Pharmacol Ther       Date:  2002-12       Impact factor: 6.875

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  22 in total

1.  External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients.

Authors:  Chen-Yan Zhao; Zheng Jiao; Jun-Jun Mao; Xiao-Yan Qiu
Journal:  Br J Clin Pharmacol       Date:  2016-02-26       Impact factor: 4.335

2.  Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation.

Authors:  Carlos Orlando Jacobo-Cabral; Pilar García-Roca; Elba Margarita Romero-Tejeda; Herlinda Reyes; Mara Medeiros; Gilberto Castañeda-Hernández; Iñaki F Trocóniz
Journal:  Br J Clin Pharmacol       Date:  2015-06-22       Impact factor: 4.335

3.  Dosage Optimization Based on Population Pharmacokinetic Analysis of Tacrolimus in Chinese Patients with Nephrotic Syndrome.

Authors:  Tong Lu; Xu Zhu; Shansen Xu; Mingming Zhao; Xueshi Huang; Zhanyou Wang; Limei Zhao
Journal:  Pharm Res       Date:  2019-02-04       Impact factor: 4.200

4.  Importance of hematocrit for a tacrolimus target concentration strategy.

Authors:  Elisabet Størset; Nick Holford; Karsten Midtvedt; Sara Bremer; Stein Bergan; Anders Åsberg
Journal:  Eur J Clin Pharmacol       Date:  2013-09-27       Impact factor: 2.953

Review 5.  Population Pharmacokinetic Modelling and Bayesian Estimation of Tacrolimus Exposure: Is this Clinically Useful for Dosage Prediction Yet?

Authors:  Emily Brooks; Susan E Tett; Nicole M Isbel; Christine E Staatz
Journal:  Clin Pharmacokinet       Date:  2016-11       Impact factor: 6.447

6.  Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach.

Authors:  Tom M Nanga; Thao T P Doan; Pierre Marquet; Flora T Musuamba
Journal:  Br J Clin Pharmacol       Date:  2019-12-17       Impact factor: 4.335

7.  Tacrolimus Population Pharmacokinetics and Multiple CYP3A5 Genotypes in Black and White Renal Transplant Recipients.

Authors:  Olivia Campagne; Donald E Mager; Daniel Brazeau; Rocco C Venuto; Kathleen M Tornatore
Journal:  J Clin Pharmacol       Date:  2018-05-18       Impact factor: 3.126

8.  Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes.

Authors:  Can Hu; Wen-Jun Yin; Dai-Yang Li; Jun-Jie Ding; Ling-Yun Zhou; Jiang-Lin Wang; Rong-Rong Ma; Kun Liu; Ge Zhou; Xiao-Cong Zuo
Journal:  Eur J Clin Pharmacol       Date:  2018-07-17       Impact factor: 2.953

Review 9.  Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Authors:  Olivia Campagne; Donald E Mager; Kathleen M Tornatore
Journal:  J Clin Pharmacol       Date:  2018-10-29       Impact factor: 3.126

10.  Practical recommendations for population PK studies with sampling time errors.

Authors:  Leena Choi; Ciprian M Crainiceanu; Brian S Caffo
Journal:  Eur J Clin Pharmacol       Date:  2013-08-24       Impact factor: 2.953

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