Population pharmacokinetic and limited sampling models for carboplatin administered in high-dose combination regimens...

By means of a nonlinear mixed effect modeling technique, a population pharmacokinetic (PK) model was developed to evaluate the effects of a variety of covariates on clearance and other pharmacokinetic parameters of ultrafilterable carboplatin administered in high-dose combination regimens with peripheral blood stem cell support. In addition, single-sample and two-sample limited sampling models (LSMs) were derived to estimate carboplatin's AUC that could be used in the design of drug dosing regimens.

A total of 44 female patients with advanced ovarian cancer participated in two phase I studies. All 44 patients received a high-dose carboplatin chemotherapy with other anticancer drugs. A population PK model was applied to the plasma concentration-time data of ultrafilterable carboplatin using the NONMEM and Xpose computer programs. The Xpose program utilized a general additive modeling technique to identify significant patient covariates and PK parameter relationships. The resultant PK model was validated using a bootstrap method. Stepwise linear regression analyses were used to develop LSMs based on the correlation between carboplatin's AUC and plasma concentrations.

The best structural covariate-free model for high-dose carboplatin was a linear two-compartment model with an exponential error model to account for intersubject variability and a CCV error model to account for intrasubject variability. Subsequently, a final covariate model for clearance (l/min) was obtained as follows: TVCL=0.101+0011*(WT-62.35)-0.0658*(SCR-0.65) where WT is body weight (kg) and SCR is serum creatinine (mg/dl). Both WT and SCR were found to significantly influence carboplatin's total clearance. It was determined that the best single-sample LSM was AUC(LSM)=0.553*C(240min) ( r=0.998).

Both a population PK model and a LSM for high-dose carboplatin were developed following its administration in combination chemotherapeutic regimens with peripheral blood stem cell support. In both cases, the models performed well when analyzed in the context of the retrospective and bootstrap analyses. Prospective studies in ovarian cancer patients should be conducted to further tailor the current models.