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

2017 ◽  
Vol 84 (1) ◽  
pp. 153-171 ◽  
Author(s):  
Jun-Jun Mao ◽  
Zheng Jiao ◽  
Hwi-Yeol Yun ◽  
Chen-Yan Zhao ◽  
Han-Chao Chen ◽  
...  
Keyword(s):  
Renal Transplant ◽  
Population Pharmacokinetic ◽  
Renal Transplant Recipients ◽  
Pharmacokinetic Models ◽  
Transplant Recipients ◽  
External Evaluation

scholarly journals Incorporating Nonlinear Kinetics to Improve the Predictive Performance of Population Pharmacokinetic Models for Ciclosporin in Adult Renal Transplant Recipients: A Comparison of Modelling Strategies

2020 ◽  
Author(s):  
Jun-Jun Mao ◽  
Zheng Jiao ◽  
Xiao-Yan Qiu ◽  
Ming Zhang ◽  
Ming-Kang Zhong
Keyword(s):  
Renal Transplant ◽  
Predictive Performance ◽  
Population Pharmacokinetic ◽  
List Type ◽  
Renal Transplant Recipients ◽  
Transplant Recipients ◽  
Inhibitory Effects ◽  
Nonlinear Kinetics ◽  
Nonlinear Properties ◽  
Modelling Strategies

AbstractAimCiclosporin (CsA) has been shown to follow nonlinear pharmacokinetics in renal transplant recipients who received Neoral-based triple immunosuppressive therapy. Some of these nonlinear properties have not been fully considered in population pharmacokinetic (popPK) analysis. Therefore, the aim of this study was to determine the potential influence of nonlinearity and the functional forms of covariates on model predictability.MethodsA total of 2969 CsA whole-blood measurements, including 1328 pre-dose and 1641 2-h post-dose concentrations, were collected from 173 patients who underwent their first renal transplantation. Four popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based, linear and nonlinear compartmental kinetic models and empirical formulae on model predictability. Prediction-based and simulation-based diagnostics (prediction-corrected visual predictive checks) were performed to determine the stability and predictive performance of these four models.ResultsModel predictability improved when nonlinearity was considered. The theory-based nonlinear model which incorporated nonlinear property based on known theoretical relationships performed better than the other two compartmental models. The nonlinear Michaelis-Menten model showed a remarkable improvement in predictive performance over that of the other three compartmental models. The saturated binding of CsA to erythrocytes, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may have contributed to the nonlinearity.ConclusionsIncorporating nonlinear properties are likely to be a promising approach for improving CsA model predictability. However, CsA nonlinear kinetics resources need further investigation. Until then, Michaelis-Menten empirical model can be used for CsA dose adjustments.What is already known about this subjectCsA in renal transplant recipients receiving Neoral-based triple immunosuppressive therapy followed nonlinear pharmacokinetics.Nonlinearity is rarely incorporated into CsA population pharmacokinetic (popPK) modelling processes.What this study addsFour popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based compartmental kinetic models and empirical formulae, as well as the effect of nonlinearity on CsA model predictability.Based on the four models, incorporating nonlinear properties is likely to be a promising approach for improving CsA model predictability.Saturated distribution into red blood cells, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may be the main sources of CsA PK nonlinearity.Principal Investigator statementThe authors confirm that the Principal Investigator for this paper is Zheng Jiao and that he had direct clinical responsibility for patients.

Tacrolimus Population Pharmacokinetic-Pharmacogenetic Analysis and Bayesian Estimation in Renal Transplant Recipients

2009 ◽  
Vol 48 (12) ◽  
pp. 805-816 ◽  
Author(s):  
Khaled Benkali ◽  
Aurelie Prémaud ◽  
Nicolas Picard ◽  
Jean-Philippe Rérolle ◽  
Olivier Toupance ◽  
...  
Keyword(s):  
Renal Transplant ◽  
Bayesian Estimation ◽  
Population Pharmacokinetic ◽  
Renal Transplant Recipients ◽  
Transplant Recipients
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