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Purpose: Numerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus., Methods: A literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting., Results: Of the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting., Conclusions: Based on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.

Background and Objectives: Diltiazem is a benzothiazepine calcium blocker and widely used in renal transplant patients since it improves the level of tacrolimus or cyclosporine A concentration. Several population pharmacokinetic (PopPK) models had been established for cyclosporine A and tacrolimus but no specific PopPK model was established for diltiazem. The aim of the study is to develop a PopPK model for diltiazem in renal transplant recipients and provide relevant pharmacokinetic parameters of diltiazem for further pharmacokinetic interaction study., Methods: Patients received tacrolimus as primary immunosuppressant agent after renal transplant and started administration of diltiazem 90 mg twice daily on 5th day. The concentration of diltiazem at 0, 0.5, 1, 2, 8, and 12 h was measured by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Genotyping for CYP3A4*1G, CYP3A5*3, and MDR1 3435 was conducted by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). 25 covariates were considered in the stepwise covariate model (SCM) building procedure., Results: One-compartment structural pharmacokinetic model with first-order absorption and elimination was used to describe the pharmacokinetic characteristics of diltiazem. Total bilirubin (TBIL) influenced apparent volume of distribution (V/F) of diltiazem in the forward selection. The absorption rate constant (K a ), V/F, and apparent oral clearance (CL/F) of the final population pharmacokinetic (PopPK) model of diltiazem were 1.96/h, 3550 L, and 92.4 L/h, respectively., Conclusion: A PopPK model of diltiazem is established in Chinese renal transplant recipients and it will provide relevant pharmacokinetic parameters of diltiazem for further pharmacokinetic interaction study.

Objective: Tacrolimus is used clinically for the long-term treatment of antirejection of transplanted organs in liver and kidney transplant recipients, although dose optimization is poorly managed. The aim of this study was to examine the association between tacrolimus pharmacokinetic variability and CYP3A4 and CYP3A5 genotypes by a population pharmacokinetic analysis based on routine drug monitoring data in adult renal transplant recipients., Materials and Methods: Trough tacrolimus concentrations were obtained from 161 adult kidney transplant recipients after transplantation. The population pharmacokinetic analysis was carried out using the nonlinear mixed-effect modeling software NONMEM version 7.2. The CYP3A4*1G and CYP3A5*3 genetic polymorphisms from the patients studied were determined by direct sequencing using a validated automated genetic analyzer., Results: A one-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of tacrolimus. Covariates including CYP3A5*3 and CYP3A4*1G alleles and hematocrit were retained in the final model. The apparent clearance of tacrolimus was about two-fold higher in kidney transplant patients with higher enzymatic activity of CYP3A5*1 and CYP3A4*1G (with the CYP3A5*1/*1 or *1/*3 and CYP3A4*1/*1G or CYP3A4*1G/*1G) compared with those with lower enzymatic activity (CYP3A5*3/*3 and CYP3A4*1/*1)., Conclusion: This is the first study to extensively determine the effect of CYP3A4*1G and CYP3A5*3 genetic polymorphisms and hematocrit value on tacrolimus pharmacokinetics in Chinese renal transplant recipients. The findings suggest that CYP3A5*3 and CYP3A4*1G polymorphisms and hematocrit are determinant factors in the apparent clearance of tacrolimus. The initial dose design is mainly based on CYP3A5 and CYP3A4 genotypes as well as hematocrit. This result may also be useful for maintenance tacrolimus dose optimization and may help to avoid fluctuating tacrolimus levels and improve the efficacy and tolerability of tacrolimus in kidney transplant recipients.