Li-Feng Hsu1. 1. Division of Pharmaceutical Science, Center for Drug Evaluation (CDE), 3F, No.465, Sec.6, Zhongxiao E. Rd, Taipei, 11557, Taiwan. Lfhsu@cde.org.tw.
Abstract
PURPOSE: The purpose of the study was to construct a population pharmacokinetic model for pegylated liposomal doxorubicin and use the final model to investigate the discrimination performance of pharmacokinetic metrics (e.g., Cmax, AUC and partial AUC) of various analytes (e.g., liposome encapsulated doxorubicin, free doxorubicin and total doxorubicin) for the identification of formulation differences by means of Monte Carlo simulations. METHODS: A model was simultaneously built to characterize the concentration time profiles of liposome-encapsulated doxorubicin and free doxorubicin using NONMEM. The different scenarios associated with changes in release rate (Rel) were simulated based on the final parameters. 500 simulated virtual bioequivalence (BE) studies were performed for each scenario, and power curves for the probability of declaring BE were also computed. RESULTS: The concentration time profiles of liposome-encapsulated doxorubicin and free doxorubicin were well described by a one- and two-compartment model, respectively. pAUC0-24 h and pAUC0-48 h of free doxorubicin was most responsive to changes in the Rel when the Rel (test)/Rel (reference) ratios decreased. In contrast, when the Rel (test) increased, AUC0-t of liposome-encapsulated doxorubicin was the most responsive metric. CONCLUSIONS: In addition to the traditional metrics, partial AUC should be included for the BE assessment of pegylated liposomal doxorubicin.
PURPOSE: The purpose of the study was to construct a population pharmacokinetic model for pegylated liposomal doxorubicin and use the final model to investigate the discrimination performance of pharmacokinetic metrics (e.g., Cmax, AUC and partial AUC) of various analytes (e.g., liposome encapsulated doxorubicin, free doxorubicin and total doxorubicin) for the identification of formulation differences by means of Monte Carlo simulations. METHODS: A model was simultaneously built to characterize the concentration time profiles of liposome-encapsulated doxorubicin and free doxorubicin using NONMEM. The different scenarios associated with changes in release rate (Rel) were simulated based on the final parameters. 500 simulated virtual bioequivalence (BE) studies were performed for each scenario, and power curves for the probability of declaring BE were also computed. RESULTS: The concentration time profiles of liposome-encapsulated doxorubicin and free doxorubicin were well described by a one- and two-compartment model, respectively. pAUC0-24 h and pAUC0-48 h of free doxorubicin was most responsive to changes in the Rel when the Rel (test)/Rel (reference) ratios decreased. In contrast, when the Rel (test) increased, AUC0-t of liposome-encapsulated doxorubicin was the most responsive metric. CONCLUSIONS: In addition to the traditional metrics, partial AUC should be included for the BE assessment of pegylated liposomal doxorubicin.
Entities:
Keywords:
bioequivalence; modeling and simulation; partial AUC; pegylated liposomal doxorubicin; population pharmacokinetics
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