To evaluate the effect of components in Guanxin Ⅱ prescription on the pharmacokinetic profiles of paeoniflorin. Plasma concentration of Paeoniflorin in rats after intravenous injection of Paronia Pall Extract (PPE)...To evaluate the effect of components in Guanxin Ⅱ prescription on the pharmacokinetic profiles of paeoniflorin. Plasma concentration of Paeoniflorin in rats after intravenous injection of Paronia Pall Extract (PPE) and oral administration of PPE and three types of decoctions in Guanxin Ⅱ prescription, respectively, were determined by HPLC analyses. NONMEM (nonlinear mixed-effect modeling) method was used to analyze full set of pharmacokinetic data directly. A two-compartment model with first-order degradation in absorption compartment was employed for the data analysis. The mean of population parameters, CL1, V1, CL2, V2, Ka0, and Kal, were measured to be 0.509 L/h, 0.104 L, 0.113 L/h, 0.123 L, 0.135/h, and 0.0135/h, respectively. Inter-individual variabilities were estimated and dose formulation (DF) was identified as a significant covariate of Ka 1, Ka0, and V1. It is concluded that the pharmacokinetic behaviors of paeoniflorin in rats can alter with different dose formulations.展开更多
The nonlinear mixed-effects model with stochastic differential equations (SDEs) is used to model the population pharmacokinetic (PPK) data that are extended from ordinary differential equations (ODEs) by adding ...The nonlinear mixed-effects model with stochastic differential equations (SDEs) is used to model the population pharmacokinetic (PPK) data that are extended from ordinary differential equations (ODEs) by adding a stochastic term to the state equation. Compared with the ODEs, the SDEs can model correlated residuals which are ubiquitous in actual pharmacokinetic problems. The Bayesian estimation is provided for nonlinear mixed-effects models based on stochastic differential equations. Combining the Gibbs and the Metropolis-Hastings algorithms, the population and individual parameter values are given through the parameter posterior predictive distributions. The analysis and simulation results show that the performance of the Bayesian estimation for mixed-effects SDEs model and analysis of population pharmacokinetic data is reliable. The results suggest that the proposed method is feasible for population pharmacokinetic data.展开更多
Population pharmacokinetic meta-analysis method was used in order to obtain the pharmacokinetic characteristics of risperidone and its active metabolite. Eighteen studies were selected from published papers from 1995 ...Population pharmacokinetic meta-analysis method was used in order to obtain the pharmacokinetic characteristics of risperidone and its active metabolite. Eighteen studies were selected from published papers from 1995 to 2011. A model consisted of two compartments for parent drug and one compartment for its active metabolite combined with a flexible absorption process was developed based on the meta-dataset. The population-predicted apparent clearance for risperidone and 9-hydroxyrisperidone, the active metabolite was 7.66 L/h and 7.38 L/h, and the apparent volume of distribution in the central compartment was 70.6 L and 117 L, respectively. The final model was evaluated by visual predictive check(VPC) based on 1000 times model simulation. This model was adequately used to predict clinical therapeutic drug monitoring(TDM) data from 42 Chinese inpatients. Bias(mean prediction errors, MPE) and precision(root mean squared prediction errors, RMSE) were calculated to statistically analysis the population prediction error. It was demonstrated that the model developed from the meta-dataset was reliable and can be used to facilitate the individualized treatment for a target population.展开更多
The aim of this study was to develop a combined population pharmacokinetic (PPK) model for losartan and its active metabolite E-3174 in five Chinese ethnicities for individualized drug therapy in clinical practice. ...The aim of this study was to develop a combined population pharmacokinetic (PPK) model for losartan and its active metabolite E-3174 in five Chinese ethnicities for individualized drug therapy in clinical practice. HPLC method was used to determine the blood levels of losartan and E-3174 simultaneously. One-, two- and three-compartment models were fitted to plasma concentration time data of 50 Chinese healthy subjects (including Han, Mongolian, Korean, Hui and Uigur) using nonlinear mixed-effect modeling (NONMEM). From the basic model of losartan, the effects of demography and biochemical covariates were investigated, which were added one by one by the forward inclusion and backward elimination. The final models of losartan and E-3174 were connected by first order or transit compartment model. Pharmacokinetic parameters of losartan and its active metabolite E-3174 were assessed simultaneously in one integrated model with the plausible covariates on the key pharmacokinetic parameters of E-3174. Nonparametric bootstrap was used for the model stability validation. The data of losartan were best described using a two-compartment model with linear elimination. The time to reach Cmax of losartan and E-3174 were obtained to be 0.9 and 3.8 h, respectively. Two transit compartments were chosen with adequate fit of the delayed Tmax of E-3174. The population estimates for transformation of losartan to E-3174 was about 73.9%. Ethnicity factor showed significant influence on the non-metabolizing E-3174 clearance CL10, the peripheral compartment clearance CL2 and the central compartment volume Vj of losartan and also has a significant effect on the transit rate (Kt). A total of 925 out of 1000 iterations succeeded in minimization. The PPK models were steady and reliable. Ethnicity factor showed significant influence on both losartan clearance and the transition from losartan to E-3174, no covariate influencing the PK parameters of E-3174 was identified.展开更多
A new HPLC method has been developed for determining donepezil in human plasma. To find the optimum conditions, a derivatization reaction was performed in different media, and the reaction product was identified by NM...A new HPLC method has been developed for determining donepezil in human plasma. To find the optimum conditions, a derivatization reaction was performed in different media, and the reaction product was identified by NMR and GC-MS after a semi-preparative HPLC separation. Under optimized conditions, donepezil was derivatized by 9-fluorenylmethyl chloroformate in chloroform and carbonate buffer at pH 9.5 in the presence of NaI after solid-phase extraction from a plasma sample. The reaction product was quantified on a reversed-phase TRACER EXCEL ODS-A, 5 μm column using a mixture of acetonitrile–10 mM acetate buffer(pH 6.0)–THF(60:35:5, v/v/v) as the mobile phase with fluorescence detection at 264 nm(ex) and 313 nm(em). Fluoxetine was used as the internal standard. The total run-time of the analysis was about 10 min, and a clean chromatogram was obtained. The developed method was linear over the range of 1–100 ng/mL in 500 μL of plasma samples(r2>0.998). The intra-day and inter-day precision values were in the range of 2.6%–11.6%. The limit of quantification was 1 ng/mL.展开更多
基金National Natural Science Foundation (Grant No. 30472165)
文摘To evaluate the effect of components in Guanxin Ⅱ prescription on the pharmacokinetic profiles of paeoniflorin. Plasma concentration of Paeoniflorin in rats after intravenous injection of Paronia Pall Extract (PPE) and oral administration of PPE and three types of decoctions in Guanxin Ⅱ prescription, respectively, were determined by HPLC analyses. NONMEM (nonlinear mixed-effect modeling) method was used to analyze full set of pharmacokinetic data directly. A two-compartment model with first-order degradation in absorption compartment was employed for the data analysis. The mean of population parameters, CL1, V1, CL2, V2, Ka0, and Kal, were measured to be 0.509 L/h, 0.104 L, 0.113 L/h, 0.123 L, 0.135/h, and 0.0135/h, respectively. Inter-individual variabilities were estimated and dose formulation (DF) was identified as a significant covariate of Ka 1, Ka0, and V1. It is concluded that the pharmacokinetic behaviors of paeoniflorin in rats can alter with different dose formulations.
基金The National Natural Science Foundation of China(No.11171065,81130068)the Natural Science Foundation of Jiangsu Province(No.BK2011058)the Fundamental Research Funds for the Central Universities(No.JKPZ2013015)
文摘The nonlinear mixed-effects model with stochastic differential equations (SDEs) is used to model the population pharmacokinetic (PPK) data that are extended from ordinary differential equations (ODEs) by adding a stochastic term to the state equation. Compared with the ODEs, the SDEs can model correlated residuals which are ubiquitous in actual pharmacokinetic problems. The Bayesian estimation is provided for nonlinear mixed-effects models based on stochastic differential equations. Combining the Gibbs and the Metropolis-Hastings algorithms, the population and individual parameter values are given through the parameter posterior predictive distributions. The analysis and simulation results show that the performance of the Bayesian estimation for mixed-effects SDEs model and analysis of population pharmacokinetic data is reliable. The results suggest that the proposed method is feasible for population pharmacokinetic data.
基金Guangzhou Municipality Medical and Technology Project(Grant No.20131A011087)Beijing Key Lab of Diagnostics and Therapeutics for Psychiatric disorders 2013 Open Foundation(Grant No.2013JSJB01)Beijing Municipal Education Commission Science and Technology Development Program(Grant No.KM201110025025)
文摘Population pharmacokinetic meta-analysis method was used in order to obtain the pharmacokinetic characteristics of risperidone and its active metabolite. Eighteen studies were selected from published papers from 1995 to 2011. A model consisted of two compartments for parent drug and one compartment for its active metabolite combined with a flexible absorption process was developed based on the meta-dataset. The population-predicted apparent clearance for risperidone and 9-hydroxyrisperidone, the active metabolite was 7.66 L/h and 7.38 L/h, and the apparent volume of distribution in the central compartment was 70.6 L and 117 L, respectively. The final model was evaluated by visual predictive check(VPC) based on 1000 times model simulation. This model was adequately used to predict clinical therapeutic drug monitoring(TDM) data from 42 Chinese inpatients. Bias(mean prediction errors, MPE) and precision(root mean squared prediction errors, RMSE) were calculated to statistically analysis the population prediction error. It was demonstrated that the model developed from the meta-dataset was reliable and can be used to facilitate the individualized treatment for a target population.
基金The 115th Project of Legionary Medical Treatment and Public Health(Grant No.06G023)
文摘The aim of this study was to develop a combined population pharmacokinetic (PPK) model for losartan and its active metabolite E-3174 in five Chinese ethnicities for individualized drug therapy in clinical practice. HPLC method was used to determine the blood levels of losartan and E-3174 simultaneously. One-, two- and three-compartment models were fitted to plasma concentration time data of 50 Chinese healthy subjects (including Han, Mongolian, Korean, Hui and Uigur) using nonlinear mixed-effect modeling (NONMEM). From the basic model of losartan, the effects of demography and biochemical covariates were investigated, which were added one by one by the forward inclusion and backward elimination. The final models of losartan and E-3174 were connected by first order or transit compartment model. Pharmacokinetic parameters of losartan and its active metabolite E-3174 were assessed simultaneously in one integrated model with the plausible covariates on the key pharmacokinetic parameters of E-3174. Nonparametric bootstrap was used for the model stability validation. The data of losartan were best described using a two-compartment model with linear elimination. The time to reach Cmax of losartan and E-3174 were obtained to be 0.9 and 3.8 h, respectively. Two transit compartments were chosen with adequate fit of the delayed Tmax of E-3174. The population estimates for transformation of losartan to E-3174 was about 73.9%. Ethnicity factor showed significant influence on the non-metabolizing E-3174 clearance CL10, the peripheral compartment clearance CL2 and the central compartment volume Vj of losartan and also has a significant effect on the transit rate (Kt). A total of 925 out of 1000 iterations succeeded in minimization. The PPK models were steady and reliable. Ethnicity factor showed significant influence on both losartan clearance and the transition from losartan to E-3174, no covariate influencing the PK parameters of E-3174 was identified.
文摘A new HPLC method has been developed for determining donepezil in human plasma. To find the optimum conditions, a derivatization reaction was performed in different media, and the reaction product was identified by NMR and GC-MS after a semi-preparative HPLC separation. Under optimized conditions, donepezil was derivatized by 9-fluorenylmethyl chloroformate in chloroform and carbonate buffer at pH 9.5 in the presence of NaI after solid-phase extraction from a plasma sample. The reaction product was quantified on a reversed-phase TRACER EXCEL ODS-A, 5 μm column using a mixture of acetonitrile–10 mM acetate buffer(pH 6.0)–THF(60:35:5, v/v/v) as the mobile phase with fluorescence detection at 264 nm(ex) and 313 nm(em). Fluoxetine was used as the internal standard. The total run-time of the analysis was about 10 min, and a clean chromatogram was obtained. The developed method was linear over the range of 1–100 ng/mL in 500 μL of plasma samples(r2>0.998). The intra-day and inter-day precision values were in the range of 2.6%–11.6%. The limit of quantification was 1 ng/mL.