This tacrolimus population PK model will be a valuable tool in developing rational guidelines and provides a basis for individualized therapy after kidney transplantation in clinical settings of Korea.

AIMSSeveral population pharmacokinetic (popPK) models for ciclosporin (CsA) in adult renal transplant recipients have been constructed to optimize the therapeutic regimen of CsA. However, little is known about their predictabilities when extrapolated to different clinical centres. Therefore, this study aimed to externally evaluate the predictive ability of CsA popPK models and determine the potential influencing factors. METHODSA literature search was conducted and the predictive performance was determined for each selected model using an independent data set of 62 patients (471 predose and 500 2-h postdose concentrations) from our hospital. Prediction-based diagnostics and simulation-based normalized prediction distribution error were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting. Additionally, potential factors influencing model predictability were investigated. RESULTSSeventeen models extracted from 17 published popPK studies were assessed. Prediction-based diagnostics showed that ethnicity potentially influenced model transferability. Simulation-based normalized prediction distribution error analyses indicated misspecification in most of the models, especially regarding variance. Bayesian forecasting demonstrated that the predictive performance of the models substantially improved with 2-3 prior observations. The predictability of nonlinear Michaelis-Menten models was superior to that of linear compartmental models when evaluating the impact of structural models, indicating the underlying nonlinear kinetics of CsA. Structural model, ethnicity, covariates and prior observations potentially affected model predictability. CONCLUSIONS WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Several ciclosporin population pharmacokinetic models for adult renal transplant recipients have been established to facilitate dose individualization.• Body weight, postoperative days, age and haematocrit, among other factors, have been identified as contributors to the large variability in ciclosporin pharmacokinetics. WHAT THIS STUDY ADDS• The transferability of relevant models was systematically evaluated using an independent data set.• Structural model was the predominant factor that influenced model predictability.• Incorporating nonlinear kinetics into modelling might be a promising approach to improving model transferability.

As tacrolimus has a rather narrow therapeutic range and high individual variability in its pharmacokinetics, it is important to determine the cause of the variation in tacrolimus pharmacokinetics. The purpose of this study was to establish a population pharmacokinetic-pharmacogenetic model of tacrolimus and identify covariates that affect pharmacokinetic parameters to prevent fluctuations in the tacrolimus trough concentration during the early period after transplantation. Data from 1501 trough concentrations and 417 densely collected concentrations were compiled from 122 patients who were on post-operative days 10-20 and analysed with a nonlinear mixed-effect model. The first-order conditional estimation (FOCE) with interaction method was used to fit the model using the NONMEM program. Clinical/laboratory data were also collected for the same period, and CYP3A5 and ABCB1 genotypes were analysed for use in modelling from all included patients. An empirical Bayesian approach was used to estimate individual pharmacokinetic profiles. A one-compartment model with first absorption and elimination and lag time best described the data. The estimated population mean of clearance (CL/F), volume of distribution (V/F) and absorption rate (K a ) were 21.9 L/hr, 205 L, and 3.43/hr, respectively, and the lag time was fixed at 0.25 hr. Clearance increased with days after transplantation and decreased with CYP3A5*3/*3 about 18.4% compared with CYP3A5*1 carriers (p < 0.001). A population pharmacokinetic model was developed for tacrolimus in early post-kidney transplantation recipients to identify covariates that affect tacrolimus pharmacokinetics. Post-operative days and CYP3A5 genotype were confirmed as critical factors of tacrolimus pharmacokinetics.

In this study, Caco-2 permeability results from different laboratories were compared. Six different sets of apparent permeability coefficient (Papp) values reported in the literature were compared to experimental Papp obtained in our laboratory. The differences were assessed by determining the root mean square error (RMSE) values between the datasets, which reached levels as high as 0.581 for the training set compounds, i.e. ten compounds with known effective human permeability (Peff). The consequences of these differences in Papp for prediction of oral drug absorption were demonstrated by introducing the Papp into the absorption and pharmacokinetics simulation software application GastroPlus TM for prediction of the fraction absorbed (Fa) in humans using calibrated "user-defined permeability models". The RMSE were calculated to assess the differences between the simulated Fa and experimental values reported in the literature. The RMSE for Fa simulated with the permeability model calibrated using experimental Papp from our laboratory was 0.128. When the calibration was performed usingPapp from literature datasets, the RMSE values for Fa were higher in all cases except one. This study shows quantitative lab-to-lab variability of Caco-2 permeability results and the potential consequences this can have in the use of these results for predicting intestinal absorption of drugs.

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CLcr, UGT1A9 and SLCO1B1 genotypes seem to be promising parameters to predict the pharmacokinetics with flip-flop phenomenon of EC-MPS in transplant recipient having stable renal function. This model on clinical practice may help prevent overexposure and achieve a proper AUC in the Korean population.

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