Population pharmacokinetic analysis of the microemulsion formulation of cyclosporin A (Neoral®®) in renal transplant patients. Issue 2 (March 2006)

• Record Type: Journal Article
• Authors: Xuan, Dawei; Nightingale, Charles H; Hull, David; Nicolau, David P
• Is Part Of: Therapy. Volume 3:Issue 2(2006)
• Page Start: 259
• Page End: 264
• Publication Date: 2006-03
• Subjects: Bayesian estimation -- cyclosporin A -- Neoral®® -- organ rejection -- population pharmacokinetics -- renal transplant patients; Therapeutics -- Periodicals; Chemotherapy -- Periodicals; 615.505
• DOI: 10.2217/14750708.3.2.259
• Languages: English
• ISSNs: 1475-0708

Abstract

Aims : Optimizing the use of Cyclosporin A (CsA) has been a challenge due to its large inter- and intraindividual variability in pharmacokinetic (PK) disposition and its narrow therapeutic window. The aim of the current study was to develop a population PK model to characterize CsA steady-state PKs in renal transplant patients and to apply it to the Bayesian estimation of drug exposure using limited sampling.Method: The steady-state PKs of CsA were collected from 60 renal-transplant patients grafted for at least 3 months. Population PK analysis was performed using the nonlinear mixed-effect approach, as implemented in NONMEM (version V). For the final PK model analysis, the bootstrap method with replacement was applied to construct confidence intervals (CIs) for the parameters. Using the post hoc Bayesian option individual PK parameters were estimated in the validation set using the final PK model.Results: The population mean for clearance (CL/F), volume of distribution (V/F), and first-order absorption rate constant (Ka) were 19.9 l/h (95% CI: 13.7––28.1 l/h), 191 l/h (95% CI: 149––378 l/h), and 1.56 l/h (95% CI: 1.11––1.67 l/h), respectively. Interindividual variability of CL/F, V/F, and Ka were 85.4, 55.6 and 90.5%, respectively. Residual variability was 44.9%.Conclusion : The developed population PK model adequately described the CsA profile in renal-transplant patients. Bayesian estimation using this model provided reasonably good estimates on individual patient CsA exposure.