Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients

Mariam H. Abdel Jalil, Ahmed F. Hawwa, Patrick J. McKiernan, Michael D. Shields, James C. McElnay

Research output: Contribution to journalArticle

Abstract

Aims - To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation.
Methods - The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates.
Results - The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation:

TVCL = 12.9 x (Weight/13.2)0.35 x EXP (-0.0058 x TPT) x EXP (0.428 x CYP3A5)

where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%.

Conclusion

Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.

Original languageEnglish
Pages (from-to)130-140
Number of pages11
JournalBritish Journal of Clinical Pharmacology
Volume77
Issue number1
Early online date20 Dec 2013
DOIs
Publication statusPublished - 31 Jan 2014

Fingerprint

Tacrolimus
Cytochrome P-450 CYP3A
Pharmacokinetics
Pediatrics
Transplants
Liver
Population
Transplantation
Liver Transplantation
Alleles
Drug Monitoring
Pharmacogenomic Testing
Genotype
Body Weight
Demography
Prospective Studies
Weights and Measures

Keywords

  • gene polymorphisms
  • liver transplant
  • nonmem
  • paediatrics
  • population pharmacokinetics
  • tacrolimus

Cite this

Abdel Jalil, Mariam H. ; Hawwa, Ahmed F. ; McKiernan, Patrick J. ; Shields, Michael D. ; McElnay, James C. / Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients. In: British Journal of Clinical Pharmacology. 2014 ; Vol. 77, No. 1. pp. 130-140.
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abstract = "Aims - To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation. Methods - The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates. Results - The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation: TVCL = 12.9 x (Weight/13.2)0.35 x EXP (-0.0058 x TPT) x EXP (0.428 x CYP3A5) where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability ({\%}CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95{\%} CI 0.958, 0.996) and 40.0{\%}, respectively, while the residual variability between the observed and predicted concentrations was 35.4{\%}. Conclusion Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.",
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Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients. / Abdel Jalil, Mariam H.; Hawwa, Ahmed F.; McKiernan, Patrick J.; Shields, Michael D.; McElnay, James C.

In: British Journal of Clinical Pharmacology, Vol. 77, No. 1, 31.01.2014, p. 130-140.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients

AU - Abdel Jalil, Mariam H.

AU - Hawwa, Ahmed F.

AU - McKiernan, Patrick J.

AU - Shields, Michael D.

AU - McElnay, James C.

PY - 2014/1/31

Y1 - 2014/1/31

N2 - Aims - To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation. Methods - The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates. Results - The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation: TVCL = 12.9 x (Weight/13.2)0.35 x EXP (-0.0058 x TPT) x EXP (0.428 x CYP3A5) where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%. Conclusion Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.

AB - Aims - To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation. Methods - The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates. Results - The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation: TVCL = 12.9 x (Weight/13.2)0.35 x EXP (-0.0058 x TPT) x EXP (0.428 x CYP3A5) where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%. Conclusion Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.

KW - gene polymorphisms

KW - liver transplant

KW - nonmem

KW - paediatrics

KW - population pharmacokinetics

KW - tacrolimus

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DO - 10.1111/bcp.12174

M3 - Article

C2 - 23738951

VL - 77

SP - 130

EP - 140

JO - British Journal of Clinical Pharmacology

JF - British Journal of Clinical Pharmacology

SN - 0306-5251

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