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
Target-mediated drug disposition (TMDD)model is one of the main modeling theories for studying nonlinear pharmacokinetics (PK)ofmonoclonal antibodies.However,there are too many parameters in full TMDD model to be esti...Target-mediated drug disposition (TMDD)model is one of the main modeling theories for studying nonlinear pharmacokinetics (PK)ofmonoclonal antibodies.However,there are too many parameters in full TMDD model to be estimated based on limited clinical data,leading to instability of the final model.In the present study,we analyzed the predictive ability and applicability of a simplified quasi-steady state (QSS)model with the assumption that the total target concentration was a constant parameter during treatment with monoelonal antibody in clinical data modeling.Based on the parameters of a published TMDD model of denosumab,simulations were performed at population and individual levels.Then,a simplified TMDD model,QSS model, was used to examine the effects of hypotheses,in which the total receptor concentration was constant or variable on model fit and stability of parameter estimation.Both simulations at the population level and model fit results of simulated individual data showed that at the therapeutic doses,the total receptor concentration had little influence on changes in drug concentration,and the model with constant total receptor concentration had the same predictive power.The validated hypothesis could be applied to clinical trial design and selection of the optimal PK model in the development of monoclonal antibodies.展开更多
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Target-mediated drug disposition (TMDD)model is one of the main modeling theories for studying nonlinear pharmacokinetics (PK)ofmonoclonal antibodies.However,there are too many parameters in full TMDD model to be estimated based on limited clinical data,leading to instability of the final model.In the present study,we analyzed the predictive ability and applicability of a simplified quasi-steady state (QSS)model with the assumption that the total target concentration was a constant parameter during treatment with monoelonal antibody in clinical data modeling.Based on the parameters of a published TMDD model of denosumab,simulations were performed at population and individual levels.Then,a simplified TMDD model,QSS model, was used to examine the effects of hypotheses,in which the total receptor concentration was constant or variable on model fit and stability of parameter estimation.Both simulations at the population level and model fit results of simulated individual data showed that at the therapeutic doses,the total receptor concentration had little influence on changes in drug concentration,and the model with constant total receptor concentration had the same predictive power.The validated hypothesis could be applied to clinical trial design and selection of the optimal PK model in the development of monoclonal antibodies.
