Early non-steady-state population pharmacokinetics of oral cyclosporine in renal transplant recipients

External evaluation of population pharmacokinetic models for ciclosporin in adult renal transplant recipients

AIMS

Several 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.

METHODS

A 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.

RESULTS

Seventeen 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

Structural model is the predominant factor influencing model predictability. Incorporation of nonlinear kinetics in CsA popPK modelling should be considered. Moreover, Bayesian forecasting substantially improved model predictability.

Pharmacogenetics and drug-induced nephrotoxicity in renal transplant recipients

INTRODUCTION

The advent of calcineurin inhibitors (CNIs), as the leading immunosuppressive agents, not only has revolutionized the transplant medicine but also made it a better therapeutic intervention that guarantees the graft outcome and improves the survival rate of patients. However, genetic polymorphism(s) in the CNIs metabolic substrates genes (CYP3A4, CYP3A5) and their transporter such as P-glycoprotein (P-gp) can influence the CNIs metabolism and elicit some possible systemic and intra-renal exposures to drugs and/or metabolites with differential risk of nephrotoxicity, jeopardizing the transplantation.

METHODS

In the current study, we review the recent literatures to evaluate the effects of genetic polymorphisms of the genes involved in development of chronic calcineurin nephrotoxicity and progression of chronic allograft dysfunction (CAD) providing an extensive overview on their clinical impacts.

RESULTS

Identifying the inherited genetic basis for the inter-individual differences in terms of drug responses and determining the risk of calcineurin-mediated nephrotoxicity and CAD allow optimized personalized administration of these agents whith minimal adverse effects.

CONCLUSION

Pharmacogenetics characteristics of CYP isoforms (CYP3A) and efflux transporters (P-gp and MRP), involved in metabolism and extracellular transportation of the immunosuppressive CNIs, can be of pivotal information in the pharmacotherapy of the renal-transplant recipients. Such information can be used for the successes clinical interventions to attain an improved drug administration strategy with reduced rates of rejection and toxicity.