Literature DB >> 25846845

Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation.

Carlos Orlando Jacobo-Cabral1, Pilar García-Roca2, Elba Margarita Romero-Tejeda3, Herlinda Reyes2, Mara Medeiros2,4, Gilberto Castañeda-Hernández1, Iñaki F Trocóniz5,6.   

Abstract

AIMS: The aims of this study were (i) to develop a population pharmacokinetic (PK) model of tacrolimus in a Mexican renal transplant paediatric population (n = 53) and (ii) to test the influence of different covariates on its PK properties to facilitate dose individualization.
METHODS: Population PK and variability parameters were estimated from whole blood drug concentration profiles obtained at steady-state using the non-linear mixed effect modelling software NONMEM® Version 7.2.
RESULTS: Tacrolimus PK profiles exhibited high inter-patient variability (IPV). A two compartment model with first order input and elimination described the tacrolimus PK profiles in the studied population. The relationship between CYP3A5 genotype and tacrolimus CL/F was included in the final model. CL/F in CYP3A5*1/*1 and *1/*3 carriers was approximately 2- and 1.5-fold higher than in CYP3A5*3/*3 carriers (non-expressers), respectively, and explained almost the entire IPV in CL/F. Other covariates retained in the final model were the tacrolimus dose and formulation type. Limustin® showed markedly lower concentrations than the rest of the formulations.
CONCLUSIONS: Population PK modelling of tacrolimus in paediatric renal transplant recipients identified the tacrolimus formulation type as a significant covariate affecting the blood concentrations and confirmed the previously reported significant effect of CYP3A5 genotype on CL/F. It allowed the design of a proposed dosage based on the final model that is expected to help to improve tacrolimus dosing.
© 2015 The British Pharmacological Society.

Entities:  

Keywords:  CYP3A5; formulation; paediatric; population pharmacokinetics; renal transplant; tacrolimus

Mesh:

Substances:

Year:  2015        PMID: 25846845      PMCID: PMC4594699          DOI: 10.1111/bcp.12649

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


  48 in total

1.  PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM.

Authors:  Lars Lindbom; Pontus Pihlgren; E Niclas Jonsson; Niclas Jonsson
Journal:  Comput Methods Programs Biomed       Date:  2005-09       Impact factor: 5.428

2.  Impact of ABCB1 (MDR1) haplotypes on tacrolimus dosing in adult lung transplant patients who are CYP3A5 *3/*3 non-expressors.

Authors:  Jian Wang; Adriana Zeevi; Kenneth McCurry; Erin Schuetz; Hongxia Zheng; Aldo Iacono; Kevin McDade; Diana Zaldonis; Steven Webber; Richard M Watanabe; Gilbert J Burckart
Journal:  Transpl Immunol       Date:  2005-09-08       Impact factor: 1.708

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

Authors:  Khaled Benkali; Lionel Rostaing; Aurélie Premaud; Jean-Baptiste Woillard; Franck Saint-Marcoux; Saik Urien; Nassim Kamar; Pierre Marquet; Annick Rousseau
Journal:  Clin Pharmacokinet       Date:  2010-10       Impact factor: 6.447

4.  CYP3A5 polymorphism in Mexican renal transplant recipients and its association with tacrolimus dosing.

Authors:  Pilar García-Roca; Mara Medeiros; Herlinda Reyes; Benjamín Antonio Rodríguez-Espino; Josefina Alberú; Lourdes Ortiz; Mayela Vásquez-Perdomo; Guillermo Elizondo; Luis Eduardo Morales-Buenrostro; Eduardo Mancilla Urrea; Gilberto Castañeda-Hernández
Journal:  Arch Med Res       Date:  2012-06-13       Impact factor: 2.235

5.  Association of ABCB1, CYP3A4*18B and CYP3A5*3 genotypes with the pharmacokinetics of tacrolimus in healthy Chinese subjects: a population pharmacokinetic analysis.

Authors:  X-J Shi; F Geng; Z Jiao; X-Y Cui; X-Y Qiu; M-K Zhong
Journal:  J Clin Pharm Ther       Date:  2010-10-05       Impact factor: 2.512

6.  Tacrolimus clearance is age-dependent within the pediatric population.

Authors:  D Przepiorka; D Blamble; S Hilsenbeck; M Danielson; R Krance; K W Chan
Journal:  Bone Marrow Transplant       Date:  2000-09       Impact factor: 5.483

7.  Differences in oral FK506 dose requirements between adult and pediatric liver transplant patients.

Authors:  S V McDiarmid; J O Colonna; A Shaked; J Vargas; M E Ament; R W Busuttil
Journal:  Transplantation       Date:  1993-06       Impact factor: 4.939

8.  The impact of ethnic miscegenation on tacrolimus clinical pharmacokinetics and therapeutic drug monitoring.

Authors:  Claudia R Felipe; Helio T Silva; Paula G P Machado; Riberto Garcia; Silvia R da Silva Moreira; José O M Pestana
Journal:  Clin Transplant       Date:  2002-08       Impact factor: 2.863

9.  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

10.  Pharmacokinetics and pharmacodynamics of FK 506 in pediatric patients receiving living-related donor liver transplantations.

Authors:  M Yasuhara; T Hashida; M Toraguchi; Y Hashimoto; M Kimura; K Inui; R Hori; Y Inomata; K Tanaka; Y Yamaoka
Journal:  Transplant Proc       Date:  1995-02       Impact factor: 1.066

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  11 in total

1.  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

2.  A New CYP3A5*3 and CYP3A4*22 Cluster Influencing Tacrolimus Target Concentrations: A Population Approach.

Authors:  Franc Andreu; Helena Colom; Laure Elens; Teun van Gelder; Ronald H N van Schaik; Dennis A Hesselink; Oriol Bestard; Joan Torras; Josep M Cruzado; Josep M Grinyó; Nuria Lloberas
Journal:  Clin Pharmacokinet       Date:  2017-08       Impact factor: 6.447

3.  Sensitivity of estimated tacrolimus population pharmacokinetic profile to assumed dose timing and absorption in real-world data and simulated data.

Authors:  Michael L Williams; Hannah L Weeks; Cole Beck; Kelly A Birdwell; Sara L Van Driest; Leena Choi
Journal:  Br J Clin Pharmacol       Date:  2022-01-27       Impact factor: 3.716

Review 4.  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

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.  Tacrolimus Population Pharmacokinetics and Multiple CYP3A5 Genotypes in Black and White Renal Transplant Recipients.

Authors:  Olivia Campagne; Donald E Mager; Daniel Brazeau; Rocco C Venuto; Kathleen M Tornatore
Journal:  J Clin Pharmacol       Date:  2018-05-18       Impact factor: 3.126

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

Review 8.  Clinical aspects of tacrolimus use in paediatric renal transplant recipients.

Authors:  Agnieszka Prytuła; Teun van Gelder
Journal:  Pediatr Nephrol       Date:  2018-02-26       Impact factor: 3.714

9.  A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus Following Pediatric Renal Transplantation.

Authors:  Louise M Andrews; Dennis A Hesselink; Teun van Gelder; Birgit C P Koch; Elisabeth A M Cornelissen; Roger J M Brüggemann; Ron H N van Schaik; Saskia N de Wildt; Karlien Cransberg; Brenda C M de Winter
Journal:  Clin Pharmacokinet       Date:  2018-04       Impact factor: 6.447

10.  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
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