Time of Drug Administration, Genetic Polymorphism and Analytical Method Influence Tacrolimus Pharmacokinetics: A Population Pharmacokinetic Approach
Flora Tshinanu Musuamba (1), Michel Mourad (2), Vincent Haufroid (3), Roger K. Verbeeck (1) and Pierre Wallemacq (3).
(1): UCL, Brussels, Belgium, (2): Division of Abdominal Transplantation, Cliniques Universitaires St Luc, Belgium, (3): Laboratory of Clinical Chemistry, Cliniques Universitaires St Luc, Belgium (4).
Objecives: Tacrolimus (TAC) pharmacokinetics (PK) are characterised by a very high unexplained variability that complicates its therapeutic use. The aim of the study was to identify pathophysiological and biochemical determinants of TAC exposure in the absence of drug-drug interactions and yo investigate the impact of the analytical method on TAC variability.
Methods: Data from 19 renal transplant candidates were analyzed. They were given 2 doses of TAC: one at 8.00 am and the other at 8.00 pm. A total of 266 samples (38 pharmacokinetic profiles) were analyzed for tacrolimus by immunoassay and by LC-MS/MS successively. A population pharmacokinetic analysis was performed using NONMEM version VI software. IMx and LC-MS/MS concentrations were modelled in a unique dataset. The following parameters were checked as covariates in the modelling process: weight, age, sex, total plasma protein concentration, analytical method ( IMx OR LC-MS/MS) ABCB1 and CYP3A5 genetic polymorphisms and time of drug administration(daytime or nighttime). Bootstrapping, cross-validations, case deletion diagnostics and simulations were used to validate the final model.
Results: A two compartment model with first order absorption and elimination rates best fitted TAC IMx and LC-MS/MS concentrations but parameter values were significantly different and the residual variabilitywas higher with IMx concentrations. The following covariates were retained in the final model: time of drug administration on the absorption constant and CYP3A5 genotype on TAC clearance. ABCB1 genotype was retained in the final model on LC-MS/MS but not on IMx concentrations. All parameters were well estimated in the final model. The model validation by bootstrapping (2000 bootstraps), case deletion diagnostic, cross-validation and visual predictive check (1000 simulated samples) gave satisfactory results.
Conclusion: The final model was found to be stable and generated parameters with good precision. This is the first POP-PK study confirming the chronopharmacokinetics of TAC and showing an effect of ABCB1 genotype and analytical method on TAC PK parameters. These results may be a helpful for TAC dose individualisation.
