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Drug Metabolism and Disposition Fast Forward
First published on June 2, 2005; DOI: 10.1124/dmd.105.004358

0090-9556/05/3309-1268-1275$20.00
DMD 33:1268-1275, 2005

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POPULATION PHARMACOKINETICS OF CYCLOSPORINE IN CLINICAL RENAL TRANSPLANT PATIENTS

Ke-Hua Wu, Yi-Min Cui, Jin-Feng Guo, Ying Zhou, Suo-Di Zhai, Fu-De Cui, and Wei Lu

Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, China (K.-H.W., W.L.); Shenyang Pharmaceutical University, Shenyang, China (K.-H.W., F.-D.C.); Department of Pharmacy, Peking University First Hospital Beijing, China (Y.-M.C., J.-F.G., Y.Z.); and Peking University Third Hospital, Beijing, China (S.-D.Z.)

Population pharmacokinetics of cyclosporine (CsA) in clinical renal transplant patients has been reported in the present study. A total of 2548 retrospective drug monitoring data points were collected from 120 renal transplant patients receiving CsA. Population modeling was performed using the NONMEM (nonlinear mixed-effect modeling) program, using a one-compartment model with first-order absorption and elimination. The final regression model for CsA clearance (CL/F) with the influence of six significant covariates, comprising postoperative days (POD), total bilirubin level (TBIL, micromolar concentration), current body weight (CBW, kilograms), age (years), concurrent metabolic inhibitors of cyclosporine (INHI), and hematocrit (HCT, percentage), has been established and expressed as CL/F = 28.5 – 1.24 · POD – 0.252 · (TBIL – 11) + 0.188 · (CBW – 58) –0.191 · (Age – 42) – 2.45 · INHI – 0.212 · (HCT – 28) (liters per hour). The values in parentheses represent the median level for each of the corresponding covariates. The population estimates for CL/F (28.5 l/h), V/F (volume of distribution, 133 l), and interpatient variability (CV% = 19.7%) for CL/F were achieved, respectively. The population model was further validated by internal and external approaches, and was demonstrated to be effective and stable. Moreover, simulation was conducted to facilitate the individualized treatment based on patient information and the final model.

Address correspondence to: Dr. Wei Lu, Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing, People's Republic of China, E-mail: wlu01{at}ureach.com




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