Literature DB >> 28389935

Population Pharmacokinetics and Bayesian Estimators for Refined Dose Adjustment of a New Tacrolimus Formulation in Kidney and Liver Transplant Patients.

Jean-Baptiste Woillard1,2,3, Jean Debord1,2,3, Caroline Monchaud1,2,3, Franck Saint-Marcoux1,2,3, Pierre Marquet4,5,6.   

Abstract

BACKGROUND AND OBJECTIVES: A new once-daily formulation of tacrolimus (Envarsus®) has recently been developed, with alleged different pharmacokinetics from previous tacrolimus formulations. The objectives of this study were to develop population pharmacokinetic models and Bayesian estimators based on limited sampling strategies for Envarsus® in kidney and liver transplant recipients.
MATERIALS AND METHODS: Full tacrolimus concentration-time profiles (13 samples) were drawn from 57 liver (113 profiles) and 49 kidney (97 profiles) graft recipients transplanted for at least 6 months and switched from Prograf® to Envarsus®. The two databases were split into a development (75%) and a validation (25%) dataset. Pharmacokinetic models characterised by a single compartment with first-order elimination and absorption in two phases described by a sum of two gamma distributions were developed using non-parametric (Pmetrics) and parametric (ITSIM) approaches in parallel. The best limited sampling strategy for each patient group was determined using the multiple model optimal algorithm. The performance of the models and derived Bayesian estimators was evaluated in the validation set.
RESULTS: The best limited sampling strategy was 0, 8 and 12 h post-dose, leading to a relative bias ± standard deviation (root-mean-square error) between observed and modelled inter-dose area under the curve in the validation dataset of: 0.32 ± 6.86% (6.87%) for ITSIM and 3.4 ± 13.4% (13.2%) for Pmetrics in kidney transplantation; and 0.89 ± 7.32% (7.38%) for ITSIM and -2.62 ± 8.65% (8.89%) for Pmetrics in liver transplantation.
CONCLUSION: Population pharmacokinetic models and Bayesian estimators for Envarsus® in kidney and liver transplantation were developed and are now available online for area under the curve-based tacrolimus dose adjustment.

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Year:  2017        PMID: 28389935     DOI: 10.1007/s40262-017-0533-5

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


  20 in total

1.  Pharmacokinetic modeling and development of Bayesian estimators in kidney transplant patients receiving the tacrolimus once-daily formulation.

Authors:  Franck Saint-Marcoux; Jean Debord; Nasrullah Undre; Annick Rousseau; Pierre Marquet
Journal:  Ther Drug Monit       Date:  2010-04       Impact factor: 3.681

2.  Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.

Authors:  Aida Bustad; Dimiter Terziivanov; Robert Leary; Ruediger Port; Alan Schumitzky; Roger Jelliffe
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

3.  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

4.  An open-label, concentration-ranging trial of FK506 in primary kidney transplantation: a report of the United States Multicenter FK506 Kidney Transplant Group.

Authors:  D A Laskow; F Vincenti; J F Neylan; R Mendez; A J Matas
Journal:  Transplantation       Date:  1996-10-15       Impact factor: 4.939

5.  Experiment design for nonparametric models based on minimizing Bayes Risk: application to voriconazole¹.

Authors:  David S Bayard; Michael Neely
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-12-01       Impact factor: 2.745

6.  Mycophenolic mofetil optimized pharmacokinetic modelling, and exposure-effect associations in adult heart transplant recipients.

Authors:  Jean-Baptiste Woillard; Franck Saint-Marcoux; Caroline Monchaud; Rym Youdarène; Lucie Pouche; Pierre Marquet
Journal:  Pharmacol Res       Date:  2015-07-17       Impact factor: 7.658

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.  Pharmacokinetic tools for the dose adjustment of ciclosporin in haematopoietic stem cell transplant patients.

Authors:  Jean-Baptiste Woillard; Vincent Lebreton; Michael Neely; Pascal Turlure; Stéphane Girault; Jean Debord; Pierre Marquet; Franck Saint-Marcoux
Journal:  Br J Clin Pharmacol       Date:  2014-10       Impact factor: 4.335

Review 9.  The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation.

Authors:  Dennis A Hesselink; Rachida Bouamar; Laure Elens; Ron H N van Schaik; Teun van Gelder
Journal:  Clin Pharmacokinet       Date:  2014-02       Impact factor: 6.447

10.  Conversion from twice-daily tacrolimus capsules to once-daily extended-release tacrolimus (LCPT): a phase 2 trial of stable renal transplant recipients.

Authors:  A Osama Gaber; Rita R Alloway; Kenneth Bodziak; Bruce Kaplan; Suphamai Bunnapradist
Journal:  Transplantation       Date:  2013-07-27       Impact factor: 4.939

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  8 in total

1.  Population pharmacokinetics and Bayesian estimators for intravenous mycophenolate mofetil in haematopoietic stem cell transplant patients.

Authors:  Marc Labriffe; Julien Vaidie; Caroline Monchaud; Jean Debord; Pascal Turlure; Stephane Girault; Pierre Marquet; Jean-Baptiste Woillard
Journal:  Br J Clin Pharmacol       Date:  2020-02-28       Impact factor: 4.335

2.  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

3.  Therapeutic Drug Monitoring Strategies for Envarsus in De Novo Kidney Transplant Patients Using Population Modelling and Simulations.

Authors:  Emilie Henin; Mirco Govoni; Massimo Cella; Christian Laveille; Giovanni Piotti
Journal:  Adv Ther       Date:  2021-09-12       Impact factor: 3.845

4.  A Limited Sampling Strategy to Estimate Exposure of Everolimus in Whole Blood and Peripheral Blood Mononuclear Cells in Renal Transplant Recipients Using Population Pharmacokinetic Modeling and Bayesian Estimators.

Authors:  Ida Robertsen; Jean Debord; Anders Åsberg; Pierre Marquet; Jean-Baptiste Woillard
Journal:  Clin Pharmacokinet       Date:  2018-11       Impact factor: 6.447

5.  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

6.  Network pharmacology-based analysis of the role of tacrolimus in liver transplantation.

Authors:  Lijian Chen; Yuming Peng; Chunyi Ji; Miaoxian Yuan; Qiang Yin
Journal:  Saudi J Biol Sci       Date:  2021-01-13       Impact factor: 4.219

7.  Predicting model-informed precision dosing: A test-case in tacrolimus dose adaptation for kidney transplant recipients.

Authors:  Ruben Faelens; Nicolas Luyckx; Dirk Kuypers; Thomas Bouillon; Pieter Annaert
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-02-02

8.  Population pharmacokinetics and genetics of oral meltdose tacrolimus (Envarsus) in stable adult liver transplant recipients.

Authors:  Lisa C Martial; Maaike Biewenga; Bastian N Ruijter; Ron Keizer; Jesse J Swen; Bart van Hoek; Dirk Jan A R Moes
Journal:  Br J Clin Pharmacol       Date:  2021-05-04       Impact factor: 4.335

  8 in total

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