CPT-11: population pharmacokinetic model and estimation of pharmacokinetics using the Bayesian method in patients with lung cancer.

In this study, we aimed to develop a population pharmacokinetic model for CPT-11 and to use the Bayesian method to estimate CPT-11 pharmacokinetic parameters in each of 43 patients who received combined therapy consisting of CPT-11 and etoposide. The group was divided into first and second data sets of 30 and 13 patients, respectively. We developed a population pharmacokinetic model of CPT-11 based on the first data set. The individual pharmacokinetic parameters [area under the concentration curve (AUC) and clearance (CL)] were subsequently estimated by using the Bayesian method on the second data set. Plasma CPT-11 concentrations were measured by high-performance liquid chromatography, and compartmental pharmacokinetic models were fitted by the Bayesian method. The population pharmacokinetic model was developed by using the nonlinear mixed effect model. We selected the volume of the central compartment (Vc), CL, and distribution rate constants (K12, K21) as population pharmacokinetic parameters. The population mean values (CV%) of Vc, CL, K12, and K21 were, respectively, 31.8 (15.7%) liter/m2, 14.1 (27.8%) liter/h/m2, 1.1 (8.4%)/h, and 0.41 (30.3%)/h. Residual intraindividual variability was 22.9%. The optimal sampling regime for estimation of the AUC and CL in using the Bayesian method was the two time points of 1 and 8 h post infusion. The mean predictive error, the mean absolute predictive error, and the root mean squared error were -3.3, 9.4, 3.2% (AUC) and 6.3, 10.0, 3.5% (CL), respectively. We concluded that the AUC and CL of CPT-11 could be estimated from plasma concentrations at two times by using the Bayesian method.