Population pharmacokinetic study of cyclosporine based on NONMEM in Chinese liver transplant recipients. 2010

Bo Sun, and Xiao-Yu Li, and Jun-Wei Gao, and Jian-Zhong Rui, and Yan-Kun Guo, and Zhi-Hai Peng, and Gao-Lin Liu
Department of Pharmacology, First People's Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China.

A population pharmacokinetic study of cyclosporine (CsA) was performed in liver transplant recipients. A total of 3731 retrospective drug monitoring data points at predose (C0) and 2 hours postdose (C2) were collected from 124 liver transplant recipients receiving CsA microemulsion. Population pharmacokinetic analysis was performed using the program NONMEM (nonlinear mixed-effect modeling). Various covariates potentially related to CsA pharmacokinetics were explored, and the final model was validated by a bootstrap method and by assessing the predictive performance using empiric Bayesian estimates. A one-compartment model with first-order absorption was considered. Population parameters of apparent clearance (CL/F) and volume of distribution were estimated as 23.1 L/h and 105 L, respectively. CL/F was influenced by four covariates: duration of CsA therapy (DT), hematocrit (HCT), and concurrent prednisone dose (PR). The final model for CL/F was fitted as follows: CL/F = 23.1 + 0.5 × (DT/200) - 0.07 × HCT + 0.04 × PR. The interindividual variability in CL/F, volume of distribution, and Ka calculated as coefficient of variation were 15.1%, 9.3%, and 66.0%, respectively. The intraindividual variability was 18.6%. The model fitted well with the observed data, and the bootstrap method guaranteed robustness of the population pharmacokinetic study model. Model validation was performed by a visual predictive check. Moreover, simulation was conducted to facilitate the individualized treatment based on patient information and the final model. The model to characterize population pharmacokinetic study of CsA provided better clinical individualization of CsA dosing in liver transplant recipients based on patient information and to assess patients' suitability for CsA therapy.

UI MeSH Term Description Entries
D007166 Immunosuppressive Agents Agents that suppress immune function by one of several mechanisms of action. Classical cytotoxic immunosuppressants act by inhibiting DNA synthesis. Others may act through activation of T-CELLS or by inhibiting the activation of HELPER CELLS. While immunosuppression has been brought about in the past primarily to prevent rejection of transplanted organs, new applications involving mediation of the effects of INTERLEUKINS and other CYTOKINES are emerging. Immunosuppressant,Immunosuppressive Agent,Immunosuppressants,Agent, Immunosuppressive,Agents, Immunosuppressive
D008297 Male Males
D008657 Metabolic Clearance Rate Volume of biological fluid completely cleared of drug metabolites as measured in unit time. Elimination occurs as a result of metabolic processes in the kidney, liver, saliva, sweat, intestine, heart, brain, or other site. Total Body Clearance Rate,Clearance Rate, Metabolic,Clearance Rates, Metabolic,Metabolic Clearance Rates,Rate, Metabolic Clearance,Rates, Metabolic Clearance
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D004305 Dose-Response Relationship, Drug The relationship between the dose of an administered drug and the response of the organism to the drug. Dose Response Relationship, Drug,Dose-Response Relationships, Drug,Drug Dose-Response Relationship,Drug Dose-Response Relationships,Relationship, Drug Dose-Response,Relationships, Drug Dose-Response
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D012189 Retrospective Studies Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons. Retrospective Study,Studies, Retrospective,Study, Retrospective

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