Literature DB >> 29452291

Pharmacokinetic models to assist the prescriber in choosing the best tacrolimus dose.

Jean-Baptiste Woillard1, Franck Saint-Marcoux2, Jean Debord2, Anders Åsberg3.   

Abstract

Due to a high inter-individual variability in its pharmacokinetics, tacrolimus dose individualization is mandatory. Even though the expert opinion has defined the area under the curve (AUC) as the best marker to use when performing dose adjustment of tacrolimus, most centres only use trough levels. Multiple targets have been proposed for this parameter and physicians rely largely on their personal experience when making a decision about dose adjustment. Several population pharmacokinetics models (POPPK) allowing AUC determination have been developed, but only a few are actually used in routine practice for dose individualization. These POPPK models can also be used to perform Monte Carlo simulations that help to establish different dosing rules or to anticipate the pharmacokinetics of tacrolimus in particular populations, without conducting clinical trials. Various available applications of POPPK models to assist the prescriber in choosing the best tacrolimus dose are discussed in this paper as well as the difficulties in introducing them into routine therapeutic drug monitoring.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian methods; Dose individualization; Monte carlo simulations; Population pharmacokinetics; Tacrolimus

Mesh:

Substances:

Year:  2018        PMID: 29452291     DOI: 10.1016/j.phrs.2018.02.016

Source DB:  PubMed          Journal:  Pharmacol Res        ISSN: 1043-6618            Impact factor:   7.658


  6 in total

1.  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

2.  Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients.

Authors:  Janthima Methaneethorn; Manupat Lohitnavy; Kamonwan Onlamai; Nattawut Leelakanok
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2021-11-24       Impact factor: 2.441

3.  A Prediction Model for Tacrolimus Daily Dose in Kidney Transplant Recipients With Machine Learning and Deep Learning Techniques.

Authors:  Qiwen Zhang; Xueke Tian; Guang Chen; Ze Yu; Xiaojian Zhang; Jingli Lu; Jinyuan Zhang; Peile Wang; Xin Hao; Yining Huang; Zeyuan Wang; Fei Gao; Jing Yang
Journal:  Front Med (Lausanne)       Date:  2022-05-27

4.  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

5.  A Novel, Dose-Adjusted Tacrolimus Trough-Concentration Model for Predicting and Estimating Variance After Kidney Transplantation.

Authors:  Janet Kim; Sam Wilson; Nasrullah A Undre; Fei Shi; Rita M Kristy; Jason J Schwartz
Journal:  Drugs R D       Date:  2019-06

6.  Measured GFR by Utilizing Population Pharmacokinetic Methods to Determine Iohexol Clearance.

Authors:  Anders Åsberg; Anna Bjerre; Runar Almaas; Sergio Luis-Lima; Ida Robertsen; Cathrin Lytomt Salvador; Esteban Porrini; George J Schwartz; Anders Hartmann; Stein Bergan
Journal:  Kidney Int Rep       Date:  2019-12-06
  6 in total

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