ABSTRACT
Carisbamate is an antiepileptic drug and it also has broad neuroprotective activity and anticonvulsant reaction. In this study, a liquid chromatography-quadrupole time-of-flight mass spectrometric (LC-qTOF-MS) method was developed and applied for the determination of carisbamate in rat plasma to support in vitro and in vivo studies. A quadratic regression (weighted 1/concentration2), with an equation y = ax2 + bx + c, was used to fit calibration curves over the concentration range from 9.05 to 6,600 ng/mL for carisbamate in rat plasma. Preclinical in vitro and in vivo studies of carisbamate have been studied through the developed bioanalytical method. Based on these study results, human pharmacokinetic (PK) profile has been predicted using physiologically based pharmacokinetic (PBPK) modeling. The PBPK model was optimized and validated by using the in vitro and in vivo data. The human PK of carisbamate after oral dosing of 750 mg was simulated by using this validated PBPK model. The human PK parameters and profiles predicted from the validated PBPK model were similar to the clinical data. This PBPK model developed from the preclinical data for carisbamate would be useful for predicting the PK of carisbamate in various clinical settings.
ABSTRACT
Carisbamate is an antiepileptic drug and it also has broad neuroprotective activity and anticonvulsant reaction. In this study, a liquid chromatography-quadrupole time-of-flight mass spectrometric (LC-qTOF-MS) method was developed and applied for the determination of carisbamate in rat plasma to support in vitro and in vivo studies. A quadratic regression (weighted 1/concentration2), with an equation y = ax2 + bx + c, was used to fit calibration curves over the concentration range from 9.05 to 6,600 ng/mL for carisbamate in rat plasma. Preclinical in vitro and in vivo studies of carisbamate have been studied through the developed bioanalytical method. Based on these study results, human pharmacokinetic (PK) profile has been predicted using physiologically based pharmacokinetic (PBPK) modeling. The PBPK model was optimized and validated by using the in vitro and in vivo data. The human PK of carisbamate after oral dosing of 750 mg was simulated by using this validated PBPK model. The human PK parameters and profiles predicted from the validated PBPK model were similar to the clinical data. This PBPK model developed from the preclinical data for carisbamate would be useful for predicting the PK of carisbamate in various clinical settings.
ABSTRACT
Over the last decade, physiologically based pharmacokinetics (PBPK) application has been extended significantly not only to predicting preclinical/human PK but also to evaluating the drug-drug interaction (DDI) liability at the drug discovery or development stage. Herein, we describe a case study to illustrate the use of PBPK approach in predicting human PK as well as DDI using in silico, in vivo and in vitro derived parameters. This case was composed of five steps such as: simulation, verification, understanding of parameter sensitivity, optimization of the parameter and final evaluation. Caffeine and ciprofloxacin were used as tool compounds to demonstrate the “fit for purpose” application of PBPK modeling and simulation for this study. Compared to caffeine, the PBPK modeling for ciprofloxacin was challenging due to several factors including solubility, permeability, clearance and tissue distribution etc. Therefore, intensive parameter sensitivity analysis (PSA) was conducted to optimize the PBPK model for ciprofloxacin. Overall, the increase in C(max) of caffeine by ciprofloxacin was not significant. However, the increase in AUC was observed and was proportional to the administered dose of ciprofloxacin. The predicted DDI and PK results were comparable to observed clinical data published in the literatures. This approach would be helpful in identifying potential key factors that could lead to significant impact on PBPK modeling and simulation for challenging compounds.