Introduction: Tacrolimus (Tac) is effective in preventing acute rejection but has considerable toxicity and inter-individual variability in pharmacokinetics and pharmacodynamics. Part of this is explained by polymorphisms in genes encoding Tac-metabolizing enzymes and transporters. A better understanding of Tac pharmacokinetics and pharmacodynamics may help to minimize different outcomes amongst transplant recipients by personalizing immunosuppression. Areas covered: The pharmacogenetic contribution of Tac metabolism will be examined, with a focus on recent discoveries, new developments and ethnic considerations. Expert opinion: The strongest and most consistent association in pharmacogenetics is between the CYP3A5 genotype and Tac dose requirement, with CYP3A5 expressers having a~40-50% higher dose requirement compared to non-expressers. Two recent randomized-controlled clinical trials using CYP3A5 genotype, however, did not show a decrease in acute rejections nor reduced toxicity. CYP3A4*22, CYP3A4*26, and POR*28 are also associated with Tac dose requirements and may be included to provide the expected improvement of Tac therapy. Studies focusing on the intracellular drug concentrations and on calcineurin inhibitor-induced nephrotoxicity also seem promising. For all studies, however, the ethnic prevalence of genotypes should be taken into account, as this may significantly impact the effect of pre-emptive genotyping.ARTICLE HISTORY

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 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results A total of 4527 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–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit 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: Dose0.25em()mg=2220.25emng0.25emnormalh0.25emml–1*0.5em22.50.25emnormall0.25emnormalh–1*[](),1.0if0.25emCYP3normalA5*3/*30.25emor0.25em(),1.62if0.25emCYP3normalA5*1/*30.25emor0.25emCYP3normalA5*1/*1*[](),1.0if0.25emCYP3normalA4*10.25emor unknown0.25emor0.25em(),0.814if0.25emCYP3normalA4*22*Age56−0.50*BSA1.930.72/1000 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.

Introduction: Tacrolimus (Tac) is the cornerstone of immunosuppressive therapy after solid organ transplantation and will probably remain so. Excluding belatacept, no new immunosuppressive drugs were registered for the prevention of acute rejection during the last decade. For several immunosuppressive drugs, clinical development halted because they weren't sufficiently effective or more toxic. Areas covered: Current methods of monitoring Tac treatment, focusing on traditional therapeutic drug monitoring (TDM), controversies surrounding TDM, novel matrices, pharmacogenetic and pharmacodynamic monitoring are discussed. Expert opinion: Due to a narrow therapeutic index and large interpatient pharmacokinetic variability, TDM has been implemented for individualization of Tac dose to maintain drug efficacy and minimize the consequences of overexposure. The relationship between predose concentrations and the occurrence of rejection or toxicity is controversial. Acute cellular rejection also occurs when the Tac concentration is within the target range, suggesting that Tac whole blood concentrations don't necessarily correlate with pharmacological effect. Intracellular Tac, the unbound fraction of Tac or pharmacodynamic monitoring could be better biomarkers/tools for adequate Tac exposure -research into this has been promising. Traditional TDM, perhaps following pre-emptive genotyping for Tac-metabolizing enzymes, must suffice for a few years before these strategies can be implemented in clinical practice. ARTICLE HISTORY

BackgroundMultiple clinical, demographic, and genetic factors affect the pharmacokinetics of tacrolimus in children, yet in daily practice, a uniform body-weight based starting dose is used. It can take weeks to reach the target tacrolimus pre-dose concentration.ObjectivesThe objectives of this study were to determine the pharmacokinetics of tacrolimus immediately after kidney transplantation and to find relevant parameters for dose individualization using a population pharmacokinetic analysis.MethodsA total of 722 blood samples were collected from 46 children treated with tacrolimus over the first 6 weeks after renal transplantation. Non-linear mixed-effects modeling (NONMEM®) was used to develop a population pharmacokinetic model and perform a covariate analysis. Simulations were performed to determine the optimal starting dose and to develop dosing guidelines.ResultsThe data were accurately described by a two-compartment model with allometric scaling for bodyweight. Mean tacrolimus apparent clearance was 50.5 L/h, with an inter-patient variability of 25%. Higher bodyweight, lower estimated glomerular filtration rate, and higher hematocrit levels resulted in lower total tacrolimus clearance. Cytochrome P450 3A5 expressers and recipients who received a kidney from a deceased donor had a significantly higher tacrolimus clearance. The model was successfully externally validated. In total, these covariates explained 41% of the variability in clearance. From the significant covariates, the cytochrome P450 3A5 genotype, bodyweight, and donor type were useful to adjust the starting dose to reach the target pre-dose concentration. Dosing guidelines range from 0.27 to 1.33 mg/kg/day.ConclusionDuring the first 6 weeks after transplantation, the tacrolimus weight-normalized starting dose should be higher in pediatric kidney transplant recipients with a lower bodyweight, those who express the cytochrome P450 3A5 genotype, and those who receive a kidney from a deceased donor.

BackgroundBodyweight-based dosing of tacrolimus (Tac) is considered standard care, even though the available evidence is thin. An increasing proportion of transplant recipients is overweight, prompting the question if the starting dose should always be based on bodyweight.MethodsFor this analysis, data were used from a randomized-controlled trial in which patients received either a standard Tac starting dose or a dose that was based on CYP3A5 genotype. The hypothesis was that overweight patients would have Tac overexposure following standard bodyweight-based dosing.ResultsData were available for 203 kidney transplant recipients, with a median body mass index (BMI) of 25.6 (range, 17.2-42.2). More than 50% of the overweight or obese patients had a Tac predose concentration above the target range. The CYP3A5 nonexpressers tended to be above target when they weighed more than 67.5 kg or had a BMI of 24.5 or higher. Dosing guidelines were proposed with a decrease up to 40% in Tac starting doses for different BMI groups. The dosing guideline for patients with an unknown genotype was validated using the fixed-dose versus concentration controlled data set.ConclusionsThis study demonstrates that dosing Tac solely on bodyweight results in overexposure in more than half of overweight or obese patients.