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Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients
Author(s) -
Abdel Jalil Mariam H.,
Hawwa Ahmed F.,
McKiernan Patrick J.,
Shields Michael D.,
McElnay James C.
Publication year - 2014
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.12174
Subject(s) - tacrolimus , nonmem , liver transplantation , population , medicine , pharmacokinetics , transplantation , cyp3a5 , therapeutic drug monitoring , pharmacogenetics , pharmacology , genotype , biology , biochemistry , environmental health , gene
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 × (Weight / 13.2) 0.75 × EXP ( − 0.00158 × TPT ) × EXP ( 0.428 × CYP 3 A 5 )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.