Abstract
Aims
The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient.
Methods
Data on tacrolimus exposure were collected for the first three months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modeling (NONMEM). Demographic, clinical and genetic parameters were evaluated as covariates.
Results
A total of 4,527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h‐1, clearance was 23.0 L/h (39% IIV), central volume of distribution (Vd) was 692 L (49% IIV) and the peripheral Vd 5340 L (53% IIV). Inter‐occasion variability was added to CL (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower hematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose:
Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model.
Conclusions
For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters, and can be used to individualize the tacrolimus dose in the early period after transplantation.
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