Byungjeong Song

Development of a population pharmacokinetic model to describe olmesartan medoxomil/ hydrochlorothiazide (20/12.5 mg) FDC tablet in male healthy South Korean subjects.

AIM The objective of the present study was to develop population pharmacokinetic models for olmesartan medoxomil and hydrochlorothiazide and to investigate the influence of demographic factors on these population pharmacokinetics. METHODS Plasma concentrations of olmesartan medoxomil and hydrochlorothiazide were measured in 41 healthy volunteers enrolled in our bioequivalence study by LC-MS/MS following oral administration of an olmesartan medoxomil/hydrochlorothiazide (20/12.5 mg) fixed-dose combination tablet. This data and covariates were subjected to nonlinear mixed-effect modeling analysis using the NONMEM software. Evaluation featured a visual predicted check and bootstrapping. RESULTS The distributions of olmesartan medoxomil and hydrochlorothiazide were best fitted using a two-compartment model with no lag time and first-order elimination. When analyzing hydrochlorothiazide kinetics, we found that TCHO and CL/F were correlated, while. HB and Ka influenced olmesartan medoxomil modeling. All evaluations indicated that the pharmacokinetic profiles of olmesartan medoxomil and hydrochlorothiazide were adequately described using our PPK model. CONCLUSIONS This study indicates that demographic factors influence the inter-individual variability in the disposition of the combination drug, and it might be more useful to apply it to the PK of olmesartan medoxomil/hydrochlorothiazide (20/12.5 mg) FDC tablets administered to patients with hypertension. *These two authors contributed equally to this work.

Effects of food intake on pharmacokinetics of mosapride in beagle dogs

This study was performed to determine the pharmacokinetic profile of mosapride in fasting and fed states. A single 5-mg oral dose of mosapride was administered to fasted (n = 15) and fed (n = 12) beagle dogs, and the plasma concentrations of mosapride were measured by liquid chromatography-tandem mass spectrometry. The resultant data were analyzed by noncompartmental analysis (NCA). Mosapride was absorbed in fasted and fed dogs with similar Tmax . Both Cmax and AUC were significantly higher in the fasting group than in fed dogs, being four times (10.51 μg/mL vs. 2.76 μg/mL) and 3.5 times higher (38.53 h · μg/mL vs. 10.22 h · μg/mL), respectively. These findings suggest that food intake affects the pharmacokinetics of mosapride and that the dosage regimen for this drug need to be reconsidered.

A novel HPLC–MS/MS method for the simultaneous determination of astemizole and its major metabolite in dog or monkey plasma and application to pharmacokinetics

Astemizole (AST), a second-generation antihistamine, is metabolized to desmethyl astemizole (DEA), and although it has been removed from the market for inducing QT interval prolongation, it has reemerged as a potential anticancer and antimalarial agent. This report describes a novel high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for simultaneously determining the concentrations of AST and DEA in beagle dog and cynomolgus monkey plasma with simple preparation method and short retention time. Prior to HPLC analyses, the plasma samples were extracted with simple liquid-liquid extraction method. The isocratic mobile phase was 0.025% trifluoroacetic acid (TFA dissolved in acetonitrile) and 20 mM ammonium acetate (94:6) at a flow rate of 0.25 mL/min and diphenhydramine used as internal standard. In MS/MS analyses, precursor ions of the analytes were optimized as protonated molecular ions: [M+H](+). The lower limit of quantification of astemizole was 2.5 ng/mL in both species and desmethyl astemizole were 7.5 ng/mL and 10 ng/mL in dog and monkey plasma, respectively. The accuracy, precision, and stability of the method were in accordance with FDA guidelines for the validation of bioanalytical methods. Finally this validated method was successfully applied to a pharmacokinetic study in dogs and monkeys after oral administration of 10 mg/kg AST.

Performance comparison of first-order conditional estimation with interaction and Bayesian estimation methods for estimating the population parameters and its distribution from data sets with a low number of subjects

BackgroundExploratory preclinical, as well as clinical trials, may involve a small number of patients, making it difficult to calculate and analyze the pharmacokinetic (PK) parameters, especially if the PK parameters show very high inter-individual variability (IIV). In this study, the performance of a classical first-order conditional estimation with interaction (FOCE-I) and expectation maximization (EM)-based Markov chain Monte Carlo Bayesian (BAYES) estimation methods were compared for estimating the population parameters and its distribution from data sets having a low number of subjects.MethodsIn this study, 100 data sets were simulated with eight sampling points for each subject and with six different levels of IIV (5%, 10%, 20%, 30%, 50%, and 80%) in their PK parameter distribution. A stochastic simulation and estimation (SSE) study was performed to simultaneously simulate data sets and estimate the parameters using four different methods: FOCE-I only, BAYES(C) (FOCE-I and BAYES composite method), BAYES(F) (BAYES with all true initial parameters and fixed ω2), and BAYES only. Relative root mean squared error (rRMSE) and relative estimation error (REE) were used to analyze the differences between true and estimated values. A case study was performed with a clinical data of theophylline available in NONMEM distribution media. NONMEM software assisted by Pirana, PsN, and Xpose was used to estimate population PK parameters, and R program was used to analyze and plot the results.ResultsThe rRMSE and REE values of all parameter (fixed effect and random effect) estimates showed that all four methods performed equally at the lower IIV levels, while the FOCE-I method performed better than other EM-based methods at higher IIV levels (greater than 30%). In general, estimates of random-effect parameters showed significant bias and imprecision, irrespective of the estimation method used and the level of IIV. Similar performance of the estimation methods was observed with theophylline dataset.ConclusionsThe classical FOCE-I method appeared to estimate the PK parameters more reliably than the BAYES method when using a simple model and data containing only a few subjects. EM-based estimation methods can be considered for adapting to the specific needs of a modeling project at later steps of modeling.

Determination of Matrine in Rat Plasma after Oral Administration of Novel Korean Herbal Medicine KIOM-MA128 and Application of PK

KIOM-MA128 is a novel Korean herbal medicine with antiatopic, anti-inflammatory, and antiasthmatic effects. Matrine is thought to be a potential chemical marker of KIOM-MA128, but pharmacokinetic studies on KIOM-MA128 had not been performed. This study describes a simple and rapid method using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) to determine the concentration of matrine in rats plasma after administration of KIOM-MA128. The isocratic mobile phase consisted of methanol and distilled water, and the flow rate was 0.15 mL/min. The accuracy and precision of the assay, as well as stability tests, were performed in accordance with FDA regulations for the validation of bioanalytical methods. The half-life and T max of matrine after administration of KIOM-MA128 were 4.29 ± 2.20 h and 1.8 ± 1.23 h, respectively. C max and AUCinf of matrine after administration of KIOM-MA128 at 4 g/kg and 8 g/kg were 595.10 ± 182.91 ng/mL, 5336.77 ± 1503.84 ng/mL·h and 850.46 ± 120 ng/mL, 9583.10 ± 888.92 ng/mL·h, respectively. The validated method was successfully applied to a pharmacokinetic study in rats after oral administration of KIOM-MA128.