OBJECTIVES: The aim of this study was to construct the population pharmacokinetic model in Chinese adult patients and to characterize the factors that affect the parameters of remifentanil pharmacokinetics. METHODS:15 patients were divided randomly into two groups: Index (modeling) group and validation group. 10 patients including 99 blood samples were in the Index group and 5 patients including 56 blood samples were in the Validation group. A LC-MS/MS method was developed to determine the whole blood concentration of remifentanil. Meanwhile, population modeling was performed using the NONMEM (nonlinear mixed-effect modeling) program with a 2-compartment pharmacokinetic model. The forward inclusion-backward elimination method was used to investigate the different covariates, including age, height, total bilirubin, etc. RESULTS: Liquid-liquid extraction was used to extract remifentanil from the blood. The calibration curve was linear from 0.5 to 50 ng/ml and the lowest limit of quantification (LOQ) was 0.5 ng/ml. The analytical method was rapid, selective and highly sensitive. The population pharmacokinetic results indicated that total bilirubin, age, alkaline phosphatase activity and gender significantly affected the parameters of remifentanil. The estimation of CL1, V1, CL2 and V2 were 1.85 l/min, 8.47 l, 1.28 l/min and 29.7 l, respectively. The population model was validated by another group of patients indicating that the model was effective and robust. CONCLUSION: The LC-MS/MS method for the quantification of remifentanil in human whole blood was rapid, selective and highly sensitive. The population model was acceptable and would be helpful for clinicians to assess the remifentanil pharmacokinetic parameters based on patient's specific demographic characteristics.
RCT Entities:
OBJECTIVES: The aim of this study was to construct the population pharmacokinetic model in Chinese adult patients and to characterize the factors that affect the parameters of remifentanil pharmacokinetics. METHODS: 15 patients were divided randomly into two groups: Index (modeling) group and validation group. 10 patients including 99 blood samples were in the Index group and 5 patients including 56 blood samples were in the Validation group. A LC-MS/MS method was developed to determine the whole blood concentration of remifentanil. Meanwhile, population modeling was performed using the NONMEM (nonlinear mixed-effect modeling) program with a 2-compartment pharmacokinetic model. The forward inclusion-backward elimination method was used to investigate the different covariates, including age, height, total bilirubin, etc. RESULTS: Liquid-liquid extraction was used to extract remifentanil from the blood. The calibration curve was linear from 0.5 to 50 ng/ml and the lowest limit of quantification (LOQ) was 0.5 ng/ml. The analytical method was rapid, selective and highly sensitive. The population pharmacokinetic results indicated that total bilirubin, age, alkaline phosphatase activity and gender significantly affected the parameters of remifentanil. The estimation of CL1, V1, CL2 and V2 were 1.85 l/min, 8.47 l, 1.28 l/min and 29.7 l, respectively. The population model was validated by another group of patients indicating that the model was effective and robust. CONCLUSION: The LC-MS/MS method for the quantification of remifentanil in human whole blood was rapid, selective and highly sensitive. The population model was acceptable and would be helpful for clinicians to assess the remifentanil pharmacokinetic parameters based on patient's specific demographic characteristics.