Literature DB >> 24977292

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in paediatric liver transplant recipients.

Nastya Kassir, Line Labbé, Jean-Romain Delaloye, Mohamad-Samer Mouksassi, Anne-Laure Lapeyraque, Fernando Alvarez, Michel Lallier, Mona Beaunoyer, Yves Théorêt, Catherine Litalien.   

Abstract

AIMS: The objectives of this study were to develop a population pharmacokinetic (PopPK) model for tacrolimus in paediatric liver transplant patients and determine optimal sampling strategies to estimate tacrolimus exposure accurately.
METHODS: Twelve hour intensive pharmacokinetic profiles from 30 patients (age 0.4-18.4 years) receiving tacrolimus orally were analysed. The PopPK model explored the following covariates: weight, age, sex, type of transplant, age of liver donor, liver function tests, albumin, haematocrit, drug interactions, drug formulation and time post-transplantation. Optimal sampling strategies were developed and validated with jackknife.
RESULTS: A two-compartment model with first-order absorption and elimination and lag time described the data. Weight was included on all pharmacokinetic parameters. Typical apparent clearance and central volume of distribution were 12.1 l h(-1) and 31.3 l, respectively. The PopPK approach led to the development of optimal sampling strategies, which allowed estimation of tacrolimus pharmacokinetics and area under the concentration–time curve (AUC) on the basis of practical sampling schedules (three or four sampling times within 4 h) with clinically acceptable prediction error limit. The mean bias and precision of the Bayesian vs. reference (trapezoidal) AUCs ranged from -2.8 to -1.9% and from 7.4 to 12.5%, respectively.
CONCLUSIONS: The PopPK of tacrolimus and empirical Bayesian estimates represent an accurate and convenient method to predict tacrolimus AUC(0-12) in paediatric liver transplant recipients, despite high between-subject variability in pharmacokinetics and patient demographics. The developed optimal sampling strategies will allow the undertaking of prospective trials to define the tacrolimus AUC-based therapeutic window and dosing guidelines in this population.

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Year:  2014        PMID: 24977292      PMCID: PMC4093930          DOI: 10.1111/bcp.12276

Source DB:  PubMed          Journal:  Br J Clin Pharmacol        ISSN: 0306-5251            Impact factor:   4.335


  37 in total

1.  Correlation between graft size and necessary tacrolimus dose after living-related liver transplantation.

Authors:  Y Harihara; K Sano; M Makuuchi; H Kawarasaki; T Takayama; K Kubota; M Ito; K Mizuta; H Yoshino; M Hirata; Y Kita; S Hisatomi; K Kusaka; Y Miura; K Hashizume
Journal:  Transplant Proc       Date:  2000-11       Impact factor: 1.066

2.  Therapeutic drug monitoring of cyclosporin A: should we use the area under the concentration-time curve and forget trough levels?

Authors:  P F Hoyer
Journal:  Pediatr Transplant       Date:  2000-02

3.  Covariate effects on the apparent clearance of tacrolimus in paediatric liver transplant patients undergoing conversion therapy.

Authors:  M J García Sánchez; C Manzanares; D Santos-Buelga; A Blázquez; J Manzanares; P Urruzuno; E Medina
Journal:  Clin Pharmacokinet       Date:  2001-01       Impact factor: 6.447

Review 4.  Limited sampling strategies for estimating cyclosporin area under the concentration-time curve: review of current algorithms.

Authors:  O J David; A Johnston
Journal:  Ther Drug Monit       Date:  2001-04       Impact factor: 3.681

Review 5.  Comparative clinical pharmacokinetics of tacrolimus in paediatric and adult patients.

Authors:  P E Wallemacq; R K Verbeeck
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

6.  Population pharmacokinetics of tacrolimus in children who receive cut-down or full liver transplants.

Authors:  C E Staatz; P J Taylor; S V Lynch; C Willis; B G Charles; S E Tett
Journal:  Transplantation       Date:  2001-09-27       Impact factor: 4.939

7.  Correlation between optimal tacrolimus doses and the graft weight in living donor liver transplantation.

Authors:  Y Sugawara; M Makuuchi; J Kaneko; T Ohkubo; H Imamura; H Kawarasaki
Journal:  Clin Transplant       Date:  2002-04       Impact factor: 2.863

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

Review 9.  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

10.  Universal approach to pharmacokinetic monitoring of immunosuppressive agents in children.

Authors:  G Filler; J Feber; N Lepage; G Weiler; I Mai
Journal:  Pediatr Transplant       Date:  2002-10
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  10 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.  The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients.

Authors:  Olivia Campagne; Donald E Mager; Daniel Brazeau; Rocco C Venuto; Kathleen M Tornatore
Journal:  Br J Clin Pharmacol       Date:  2019-01-04       Impact factor: 4.335

3.  Model-Based Therapeutic Drug Monitoring of Infliximab Using a Single Serum Trough Concentration.

Authors:  David Ternant; Christophe Passot; Alexandre Aubourg; Philippe Goupille; Céline Desvignes; Laurence Picon; Thierry Lecomte; Denis Mulleman; Gilles Paintaud
Journal:  Clin Pharmacokinet       Date:  2018-09       Impact factor: 6.447

4.  Population pharmacokinetics and pharmacogenomics of tacrolimus in Chinese children receiving a liver transplant: initial dose recommendation.

Authors:  Xiao Chen; Dong-Dong Wang; Hong Xu; Zhi-Ping Li
Journal:  Transl Pediatr       Date:  2020-10

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

Review 7.  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

8.  Predicting tacrolimus concentrations in children receiving a heart transplant using a population pharmacokinetic model.

Authors:  Joseph E Rower; Chris Stockmann; Matthew W Linakis; Shaun S Kumar; Xiaoxi Liu; E Kent Korgenski; Catherine M T Sherwin; Kimberly M Molina
Journal:  BMJ Paediatr Open       Date:  2017-11-22

9.  Immune cell function assays in the diagnosis of infection in pediatric liver transplantation: an open-labeled, two center prospective cohort study.

Authors:  Feng Xue; Wei Gao; Tian Qin; Cheng Wu; Yi Luo; Jing Chen; Tao Zhou; Mingxuan Feng; Bijun Qiu; Jianjun Zhu; Jia He; Qiang Xia
Journal:  Transl Pediatr       Date:  2021-02

10.  Population Pharmacokinetic Model Development of Tacrolimus in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplantation.

Authors:  Jordan T Brooks; Ron J Keizer; Janel R Long-Boyle; Sandhya Kharbanda; Christopher C Dvorak; Brian D Friend
Journal:  Front Pharmacol       Date:  2021-12-07       Impact factor: 5.810

  10 in total

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