Literature DB >> 20818834

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in renal transplant recipients on a new once-daily formulation.

Khaled Benkali1, Lionel Rostaing, Aurélie Premaud, Jean-Baptiste Woillard, Franck Saint-Marcoux, Saik Urien, Nassim Kamar, Pierre Marquet, Annick Rousseau.   

Abstract

BACKGROUND AND OBJECTIVES: Advagraf is a new extended-release once-daily formulation of tacrolimus, a potent immunosuppressant widely used in renal transplantation. The aims of his study were (i) to develop a population pharmacokinetic model for once-daily tacrolimus in adult renal transplant patients; and (ii) to develop a Bayesian estimator able to reliably estimate individual pharmacokinetic parameters and exposure indices.
METHODS: Full pharmacokinetic profiles obtained from 41 adult renal transplant patients who had been switched from ciclosporin to a single daily dose of the new once-daily tacrolimus formulation for more than 6 months were analysed. Tacrolimus concentrations were measured using validated turbulent flow chromatography-tandem mass spectrometry methods. Population parameters were computed using nonlinear mixed-effect modelling software (NONMEM Version VI). The patients were randomly divided into (i) a model-building test group (n = 29); and (ii) a validation group (n = 12). Population pharmacokinetic analysis was performed to estimate the effects on tacrolimus pharmacokinetics of demographic characteristics (sex, bodyweight, age), drug interaction with prednisolone, laboratory test results (the haematocrit, haemaglobin level and serum creatinine level) and cytochrome P450 (CYP) 3A5 (CYP3A5) genetic polymorphism. The population pharmacokinetic model was further refined by taking into account all of the data from the 41 patients, and the final model was validated using a bootstrap and a visual predictive check. For Bayesian estimation, the best limited-sampling strategy was determined on the basis of the D-optimality criterion and validation performed in the validation group.
RESULTS: The trapezoidal area under the whole-blood concentration time curve from 0 to 24 hours (AUC(24)) of tacrolimus varied by up to 50% for the same trough concentration value. The pharmacokinetics of once-daily tacrolimus were well described by a two-compartment model combined with an Erlang distribution to describe the absorption phase. The CYP3A5 genotype was the only covariate retained in the final model. The apparent clearance of tacrolimus was 2-fold higher in expressers (with the CYP3A5*1/*1 and CYP3A5*1/*3 genotypes) than in non-expressers (with the CYP3A5*3/*3 genotype). This factor explained around 25% of the interindividual variability in the apparent clearance. A posteriori Bayesian estimation allowed accurate prediction of the AUC(24) of once-daily tacrolimus, using just three sampling times (0, 1 and 3 hours post-dose) with a nonsignificant mean bias of 0.7% (range 16-20%) and good precision (root mean square error 9%).
CONCLUSIONS: Population pharmacokinetic analysis of once-daily tacrolimus in renal transplant recipients resulted in identification of the CYP3A5*1/*3 genotype as a significant covariate on the apparent clearance of tacrolimus, and the design of an accurate maximum a posteriori Bayesian estimator based on three blood concentration measurements and this covariate. Such a tool could be helpful for comparing different exposure indices or different target levels. It could contribute to improvement of the efficacy and tolerability of once-daily tacrolimus in some patients.

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Year:  2010        PMID: 20818834     DOI: 10.2165/11535950-000000000-00000

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  23 in total

Review 1.  Pharmacokinetics of tacrolimus: clinically relevant aspects.

Authors:  N A Undre; P Stevenson; A Schäfer
Journal:  Transplant Proc       Date:  1999-11       Impact factor: 1.066

2.  Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies.

Authors:  Franck Saint-Marcoux; Christiane Knoop; Jean Debord; Philippe Thiry; Annick Rousseau; Marc Estenne; Pierre Marquet
Journal:  Clin Pharmacokinet       Date:  2005       Impact factor: 6.447

3.  Opportunities to optimize tacrolimus therapy in solid organ transplantation: report of the European consensus conference.

Authors:  Pierre Wallemacq; Victor W Armstrong; Merce Brunet; Vincent Haufroid; David W Holt; Atholl Johnston; Dirk Kuypers; Yannick Le Meur; Pierre Marquet; Michael Oellerich; Eric Thervet; Burkhand Toenshoff; Nas Undre; Lutz T Weber; Ian S Westley; Michel Mourad
Journal:  Ther Drug Monit       Date:  2009-04       Impact factor: 3.681

4.  CYP3A5*3 influences sirolimus oral clearance in de novo and stable renal transplant recipients.

Authors:  Yannick Le Meur; Nassim Djebli; Jean-Christophe Szelag; Guillaume Hoizey; Olivier Toupance; Jean Philippe Rérolle; Pierre Marquet
Journal:  Clin Pharmacol Ther       Date:  2006-07       Impact factor: 6.875

5.  Clinical utility of monitoring tacrolimus blood concentrations in liver transplant patients.

Authors:  R Venkataramanan; L M Shaw; L Sarkozi; R Mullins; J Pirsch; G MacFarlane; D Scheller; D Ersfeld; M Frick; W E Fitzsimmons; M Virji; A Jain; K L Brayman; A Shaked
Journal:  J Clin Pharmacol       Date:  2001-05       Impact factor: 3.126

6.  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

7.  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

8.  Population pharmacokinetic modeling of oral cyclosporin using NONMEM: comparison of absorption pharmacokinetic models and design of a Bayesian estimator.

Authors:  A Rousseau; F Léger; Y Le Meur; F Saint-Marcoux; G Paintaud; M Buchler; P Marquet
Journal:  Ther Drug Monit       Date:  2004-02       Impact factor: 3.681

9.  Two years postconversion from a prograf-based regimen to a once-daily tacrolimus extended-release formulation in stable kidney transplant recipients.

Authors:  Rita Alloway; Steven Steinberg; Kassem Khalil; Sita Gourishankar; Joshua Miller; Douglas Norman; Sundaram Hariharan; John Pirsch; Arthur Matas; Jeffrey Zaltzman; Kathleen Wisemandle; William Fitzsimmons; M Roy First
Journal:  Transplantation       Date:  2007-06-27       Impact factor: 4.939

10.  Influence of CYP3A5 genetic polymorphism on tacrolimus daily dose requirements and acute rejection in renal graft recipients.

Authors:  Lina Quteineh; Céline Verstuyft; Valerie Furlan; Antoine Durrbach; Alexia Letierce; Sophie Ferlicot; Anne-Marie Taburet; Bernard Charpentier; Laurent Becquemont
Journal:  Basic Clin Pharmacol Toxicol       Date:  2008-12       Impact factor: 4.080

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  35 in total

1.  Population pharmacokinetic model and Bayesian estimator for two tacrolimus formulations--twice daily Prograf and once daily Advagraf.

Authors:  Jean-Baptiste Woillard; Brenda C M de Winter; Nassim Kamar; Pierre Marquet; Lionel Rostaing; Annick Rousseau
Journal:  Br J Clin Pharmacol       Date:  2011-03       Impact factor: 4.335

Review 2.  Clinical Evaluation of Modified Release and Immediate Release Tacrolimus Formulations.

Authors:  Simon Tremblay; Rita R Alloway
Journal:  AAPS J       Date:  2017-07-17       Impact factor: 4.009

Review 3.  PharmGKB summary: cyclosporine and tacrolimus pathways.

Authors:  Julia M Barbarino; Christine E Staatz; Raman Venkataramanan; Teri E Klein; Russ B Altman
Journal:  Pharmacogenet Genomics       Date:  2013-10       Impact factor: 2.089

4.  Dosing equation for tacrolimus using genetic variants and clinical factors.

Authors:  Chaitali Passey; Angela K Birnbaum; Richard C Brundage; William S Oetting; Ajay K Israni; Pamala A Jacobson
Journal:  Br J Clin Pharmacol       Date:  2011-12       Impact factor: 4.335

5.  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

6.  Population pharmacokinetic model and Bayesian estimator for 2 tacrolimus formulations in adult liver transplant patients.

Authors:  Camille Riff; Jean Debord; Caroline Monchaud; Pierre Marquet; Jean-Baptiste Woillard
Journal:  Br J Clin Pharmacol       Date:  2019-06-14       Impact factor: 4.335

Review 7.  Clinical Pharmacokinetics of Once-Daily Tacrolimus in Solid-Organ Transplant Patients.

Authors:  Christine E Staatz; Susan E Tett
Journal:  Clin Pharmacokinet       Date:  2015-10       Impact factor: 6.447

8.  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

9.  Statistical tools for dose individualization of mycophenolic acid and tacrolimus co-administered during the first month after renal transplantation.

Authors:  Flora T Musuamba; Michel Mourad; Vincent Haufroid; Martine De Meyer; Arnaud Capron; Isabelle K Delattre; Roger K Verbeeck; Pierre Wallemacq
Journal:  Br J Clin Pharmacol       Date:  2013-05       Impact factor: 4.335

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

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