Random sparse sampling strategy using stochastic simulation and estimation for a population pharmacokinetic study.

The purpose of this study was to use the stochastic simulation and estimation method to evaluate the effects of sample size and the number of samples per individual on the model development and evaluation. The pharmacokinetic parameters and inter- and intra-individual variation were obtained from a population pharmacokinetic model of clinical trials of amlodipine. Stochastic simulation and estimation were performed to evaluate the efficiencies of different sparse sampling scenarios to estimate the compartment model. Simulated data were generated a 1000 times and three candidate models were used to fit the 1000 data sets. Fifty-five kinds of sparse sampling scenarios were investigated and compared. The results showed that, 60 samples with three points and 20 samples with five points are recommended, and the quantitative methodology of stochastic simulation and estimation is valuable for efficiently estimating the compartment model and can be used for other similar model development and evaluation approaches.

A cyclic fluctuation model for 24-h ambulatory blood pressure monitoring in Chinese patients with mild to moderate hypertension.

AIM: The conventional method for analyzing 24-h ambulatory blood pressure monitoring (24-h ABPM) is insufficient to deal with the large amount of data collected. The aim of this study was to develop a novel cyclic fluctuation model for 24-h ABPM in Chinese patients with mild to moderate hypertension. METHODS: The data were obtained from 4 independent antihypertensive drug clinical trials in Chinese patients with mild to moderate hypertension. The measurements of 24-h ABPM at the end of the placebo run-in period in study 1 were used to develop the cyclic fluctuation model. After evaluated, the structural model was used to analyze the measurements in the other 3 studies. Models were fitted using NONMEM software. RESULTS: The cyclic fluctuation model, which consisted of 2 cosine functions with fixed-effect parameters for rhythm-adjusted 24-h mean blood pressure, amplitude and phase shift, successfully described the blood pressure measurements of study 1. Model robustness was validated by the bootstrap method. The measurements in the other 3 studies were well described by the same structural model. Moreover, the parameters from all the 4 studies were very similar. Visual predictive checks demonstrated that the cyclic fluctuation model could predict the blood pressure fluctuations in the 4 studies. CONCLUSION: The cyclic fluctuation model for 24-h ABPM deepens our understanding of blood pressure variability, which will be beneficial for drug development and individual therapy in hypertensive patients.

Limited sampling strategy models for estimating the AUC of gliclazide in Chinese healthy volunteers.

The aim of this work is to reduce the cost of required sampling for the estimation of the area under the gliclazide plasma concentration versus time curve within 60 h (AUC0-60t ). The limited sampling strategy (LSS) models were established and validated by the multiple regression model within 4 or fewer gliclazide concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual prediction check were used as criterion. The results of Jack-Knife validation showed that 10 (25.0 %) of the 40 LSS based on the regression analysis were not within an APE of 15 % using one concentration-time point. 90.2, 91.5 and 92.4 % of the 40 LSS models were capable of prediction using 2, 3 and 4 points, respectively. Limited sampling strategies were developed and validated for estimating AUC0-60t of gliclazide. This study indicates that the implementation of an 80 mg dosage regimen enabled accurate predictions of AUC0-60t by the LSS model. This study shows that 12, 6, 4, 2 h after administration are the key sampling times. The combination of (12, 2 h), (12, 8, 2 h) or (12, 8, 4, 2 h) can be chosen as sampling hours for predicting AUC0-60t in practical application according to requirement.

Race differences: modeling the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients.

AIM: To evaluate race differences in the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients using a population pharmacodynamic (PPD) model generated and validated using published clinical efficacy trials. METHODS: Published studies randomized trials with rosuvastatin treatment for at least 4 weeks in hypercholesterolemia patients were used for model building and validation. Population pharmacodynamic analyses were performed to describe the dose-response relationship with the mean values of LDL-C reduction (%) from dose-ranging trials using NONMEM software. Baseline LDL-C and race were analyzed as the potential covariates. Model robustness was evaluated using the bootstrap method and the data-splitting method, and Monte Carlo simulation was performed to assess the predictive performance of the PPD model with the mean effects from the one-dose trials. RESULTS: Of the 36 eligible trials, 14 dose-ranging trials were used in model development and 22 one-dose trials were used for model prediction. The dose-response of rosuvastatin was successfully described by a simple E(max) model with a fixed E(0), which provided a common E(max) and an approximate twofold difference in ED(50) for Westerners and Asians. The PPD model was demonstrated to be stable and predictive. CONCLUSION: The race differences in the pharmacodynamics of rosuvastatin are consistent with those observed in the pharmacokinetics of the drug, confirming that there is no significant difference in the exposure-response relationship for LDL-C reduction between Westerners and Asians. The study suggests that for a new compound with a mechanism of action similar to that of rosuvastatin, its efficacy in Western populations plus its pharmacokinetics in bridging studies in Asian populations may be used to support a registration of the new compound in Asian countries.

Effect of CYP2C19 genotypes on the pharmacokinetic/pharmacodynamic relationship of rabeprazole after a single oral dose in healthy Chinese volunteers.

AIMS: To explore the pharmacokinetic/pharmacodynamic relationship of rabeprazole and the role of CYP2C19 genotypes after a single oral dose in healthy Chinese volunteers by a population approach. METHODS: Plasma concentration time profile data and intragastric pH values of 19 genotyped healthy male adults after a single oral dose of rabeprazole in an open label randomized fashion were used for this population analysis. Simulation technology was performed to examine the rabeprazole response in subjects with different CYP2C19 genotypes to further investigate the effect of acid inhibition. RESULTS: The pharmacokinetics of rabeprazole was characterized by a two-compartment model with first order absorption and with an absorption lag-time. The results show that clearance of rabeprazole was affected by CYP2C19 genotypes (average clearances of homEM, hetEM, and PM were 13.9, 11.5, and 8.74 L·h(-1) respectively). An effect compartment with a sigmoidal Emax model was considered more rational for analyzing the relationship between rabeprazole concentrations and intragastric pH values. Simulated results suggest that rabeprazole 20 mg once daily for PMs is sufficient, but might be administered more frequently for other genotypes in treating gastro-esophageal reflux disease. CONCLUSION: The CYP2C19 genotype played a considerable role in the pharmacokinetic characteristics of rabeprazole, and this might need to be taken into account for clinical use.

[Limited sampling strategy models for estimating AUC for amlodipine in Chinese healthy volunteers].

This study aims to save cost of sampling for estimating the area under the amlodipine plasma concentration versus time curve in 24 hours (AUC(0-24 h)). Limited sampling strategy (LSS) models was developed and validated by mutiple regression model within 4 or fewer amlodipine concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual predict check were used as criterion. The results of Jackknife validation showed that fifteen (9.4%) of the 160 LSS based on regression analysis were not within an APE of 15% by using one concentration-time point. 156 (97.5%), 159 (99.4%) and 160 (100%) of the 160 LSS model were capable of predicting within an APE 15% by using 2, 3, 4 points, separately. Limited sampling strategies have been developed and validated for estimating AUC(0-24 h) of amlodipine. The present study indicated that the implemention of both 5 mg and 10 mg dosage could enable accurate predictions of AUC(0-24 h) by the same LSS model. This study shows that 12, 4, 24, 2 h after administration are key sampling time points. The combination of (12, 4), (12, 4, 24) or (12, 4, 24, 2 h) might be chosen as sampling hours for predicting AUC(0-24 h) in practical application according to requirement.