Literature DB >> 17875118

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

D Li1, W Lu, J-Y Zhu, J Gao, Y-Q Lou, G-L Zhang.   

Abstract

BACKGROUND AND
OBJECTIVE: Tacrolimus, an immunosuppressant widely used after liver transplantation, is characterized by a large inter-individual variability in its pharmacokinetics. The aim of this study was to perform population pharmacokinetic analysis of oral tacrolimus in liver transplant recipients and clarify the potential role of CYP3A5, MDR1 and IL-10 genetic polymorphisms in the variability of population pharmacokinetic parameters.
METHODS: Tacrolimus blood concentration data (n = 1106) were collected from 104 full liver transplant patients and were analysed using a non-linear mixed-effects modelling program (nonmem). The CYP3A5*3, MDR1 G2677T/A and C3435T genetic polymorphisms were determined using polymerase chain reaction (PCR)-restriction fragment length polymorphism analysis. The IL-10 G-1082A variant was studied by allele-specific PCR method. RESULTS AND DISCUSSION: The liver function in patients as indicated by the total bilirubin level (TBIL) and different CYP3A5*3 genotypes in donors (CYPD) and recipients (CYPR) were observed to influence tacrolimus pharmacokinetic parameter of apparent clearance (Cl/F). The final regression model can be expressed as Cl/F = 15.9 - 1.88 TBIL + 7.65 CYPD + 7.00 CYPR. The relative standard errors (%RSE) of the parameter estimation were lower than 30% and the residual variability of tacrolimus trough blood concentration was 2.81 ng/mL. No significant effect of MDR1 and IL-10 polymorphisms was observed on population pharmacokinetic parameter of tacrolimus within 175 days after liver transplantation.
CONCLUSION: The TBIL in patients and CYP3A5*3 genetic polymorphism in both donors and recipients contribute to the inter-individual variability of oral tacrolimus apparent clearance in Chinese adult liver transplant patients.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17875118     DOI: 10.1111/j.1365-2710.2007.00850.x

Source DB:  PubMed          Journal:  J Clin Pharm Ther        ISSN: 0269-4727            Impact factor:   2.512


  23 in total

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

Authors:  Nayoung Han; 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
Journal:  Eur J Clin Pharmacol       Date:  2012-06-02       Impact factor: 2.953

2.  Personalizing initial calcineurin inhibitor dosing by adjusting to donor CYP3A-status in liver transplant patients.

Authors:  Katalin Monostory; Katalin Tóth; Ádám Kiss; Edit Háfra; Nóra Csikány; József Paulik; Enikő Sárváry; László Kóbori
Journal:  Br J Clin Pharmacol       Date:  2015-10-26       Impact factor: 4.335

Review 3.  Effect of CYP3A and ABCB1 single nucleotide polymorphisms on the pharmacokinetics and pharmacodynamics of calcineurin inhibitors: Part I.

Authors:  Christine E Staatz; Lucy K Goodman; Susan E Tett
Journal:  Clin Pharmacokinet       Date:  2010-03       Impact factor: 6.447

4.  Impact of CYP3A5 genetic polymorphism on pharmacokinetics of tacrolimus in healthy Japanese subjects.

Authors:  Yoshiharu Suzuki; Masato Homma; Kosuke Doki; Fumio Itagaki; Yukinao Kohda
Journal:  Br J Clin Pharmacol       Date:  2008-03-13       Impact factor: 4.335

5.  Pharmacogenetics and population pharmacokinetics: impact of the design on three tests using the SAEM algorithm.

Authors:  Julie Bertrand; Emmanuelle Comets; Céline M Laffont; Marylore Chenel; France Mentré
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-06-27       Impact factor: 2.745

6.  The impact of liver transplant recipient and donor genetic variability on tacrolimus exposure and transplant outcome.

Authors:  Janet K Coller; Jeyamani Ramachandran; Libby John; Jonathan Tuke; Alan Wigg; Matthew Doogue
Journal:  Br J Clin Pharmacol       Date:  2019-07-24       Impact factor: 4.335

7.  Determination of the most influential sources of variability in tacrolimus trough blood concentrations in adult liver transplant recipients: a bottom-up approach.

Authors:  Cécile Gérard; Jeanick Stocco; Anne Hulin; Benoit Blanchet; Céline Verstuyft; François Durand; Filomena Conti; Christophe Duvoux; Michel Tod
Journal:  AAPS J       Date:  2014-02-14       Impact factor: 4.009

8.  Population pharmacokinetic analysis of tacrolimus in the first year after pediatric liver transplantation.

Authors:  V Guy-Viterbo; A Scohy; R K Verbeeck; R Reding; P Wallemacq; Flora Tshinanu Musuamba
Journal:  Eur J Clin Pharmacol       Date:  2013-04-16       Impact factor: 2.953

9.  Tacrolimus population pharmacokinetic-pharmacogenetic analysis and Bayesian estimation in renal transplant recipients.

Authors:  Khaled Benkali; Aurelie Prémaud; Nicolas Picard; Jean-Philippe Rérolle; Olivier Toupance; Guillaume Hoizey; Alain Turcant; Florence Villemain; Yannick Le Meur; Pierre Marquet; Annick Rousseau
Journal:  Clin Pharmacokinet       Date:  2009       Impact factor: 6.447

Review 10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.