Population Pharmacokinetics of Sulindac and Genetic Polymorphisms of FMO3 and AOX1 in Women with Preterm Labor.

PURPOSE: This prospective study aimed to evaluate the effects of genetic polymorphisms in sulindac-related metabolizing enzyme genes including FMO3 and AOX1 on the population pharmacokinetics of sulindac in 58 pregnant women with preterm labor. METHODS: Plasma samples were collected at 1.5, 4, and 10 h after first oral administration of sulindac. Plasma concentrations of sulindac and its active metabolite (sulindac sulfide) were determined, and pharmacokinetic analysis was performed with NONMEM 7.3. RESULTS: The mean maternal and gestational ages at the time of dosing were 32.5 ± 4.4 (range, 20-41) years and 27.4 ± 4.4 (range, 16.4-33.4) weeks, respectively. In the population pharmacokinetic analysis, one depot compartment model of sulindac with absorption lag time best described the data. The metabolism of sulindac and sulindac sulfide was described using Michaelis-Menten kinetics. In stepwise modeling, gestational age impacted volume of distribution (Vc), and FMO3 rs2266782 was shown by the Michaelis constant to affect conversion of sulindac sulfide to sulindac (KM32); these were retained in the final model. CONCLUSIONS: Genetic polymorphisms of FMO3 and AOX1 could affect the pharmacokinetics of sulindac in women who undergo preterm labor. The results of this study could help clinicians develop individualized treatment plans for administering sulindac.

Application of Size and Maturation Functions to Population Pharmacokinetic Modeling of Pediatric Patients.

Traditionally, dosage for pediatric patients has been optimized using simple weight-scaled methods, but these methods do not always meet the requirements of children. To overcome this discrepancy, population pharmacokinetic (PK) modeling of size and maturation functions has been proposed. The main objective of the present study was to evaluate a new modeling method for pediatric patients using clinical data from three different clinical studies. To develop the PK models, a nonlinear mixed effect modeling method was employed, and to explore PK differences in pediatric patients, size with allometric and maturation with Michaelis-Menten type functions were evaluated. Goodness of fit plots, visual predictive check and bootstrap were used for model evaluation. Single application of size scaling to PK parameters was statistically significant for the over one year old group. On the other hand, simultaneous use of size and maturation functions was statistically significant for infants younger than one year old. In conclusion, population PK modeling for pediatric patients was successfully performed using clinical data. Size and maturation functions were applied according to established criteria, and single use of size function was applicable for over one year ages, while size and maturation functions were more effective for PK analysis of neonates and infants.

Prediction of Methionine and Homocysteine levels in Zucker diabetic fatty (ZDF) rats as a T2DM animal model after consumption of a Methionine-rich diet.

BACKGROUND: Although alterations in the methionine metabolism cycle (MMC) have been associated with vascular complications of diabetes, there have not been consistent results about the levels of methionine and homocysteine in type 2 diabetes mellitus (T2DM). The aim of the current study was to predict changes in plasma methionine and homocysteine concentrations after simulated consumption of methionine-rich foods, following the development of a mathematical model for MMC in Zucker Diabetic Fatty (ZDF) rats, as a representative T2DM animal model. METHOD: The model building and simulation were performed using NONMEM® (ver. 7.3.0) assisted by Perl-Speaks-NONMEM (PsN, ver. 4.3.0). Model parameters were derived using first-order conditional estimation method with interactions permitted among the parameters (FOCE-INTER). NCA was conducted using Phoenix (ver. 6.4.0). For all tests, we considered a P-value < 0.05 to reflect statistical significance. RESULTS: Our model featured seven compartments that considered all parts of the cycle by applying non-linear mixed effects model. Conversion of S-adenosyl-L-homocysteine (SAH) to homocysteine increased and the metabolism of homocysteine was reduced under diabetic conditions, and consequently homocysteine accumulated in the elimination phase.Using our model, we performed simulations to compare the changes in plasma methionine and homocysteine concentrations between ZDF and normal rats, by multiple administrations of the methionine-rich diet of 1 mmol/kg, daily for 60 days. The levels of methionine and homocysteine were elevated approximately two- and three-fold, respectively, in ZDF rats, while there were no changes observed in the normal control rats. CONCLUSION: These results can be interpreted to mean that both methionine and homocysteine will accumulate in patients with T2DM, who regularly consume high-methionine foods.

A mechanism-based pharmacokinetic model of fenofibrate for explaining increased drug absorption after food consumption.

BACKGROUND: Oral administration of drugs is convenient and shows good compliance but it can be affected by many factors in the gastrointestinal (GI) system. Consumption of food is one of the major factors affecting the GI system and consequently the absorption of drugs. The aim of this study was to develop a mechanistic GI absorption model for explaining the effect of food on fenofibrate pharmacokinetics (PK), focusing on the food type and calorie content. METHODS: Clinical data from a fenofibrate PK study involving three different conditions (fasting, standard meals and high-fat meals) were used. The model was developed by nonlinear mixed effect modeling method. Both linear and nonlinear effects were evaluated to explain the impact of food intake on drug absorption. Similarly, to explain changes in gastric emptying time for the drug due to food effects was evaluated. RESULTS: The gastric emptying rate increased by 61.7% during the first 6.94 h after food consumption. Increased calories in the duodenum increased the absorption rate constant of the drug in fed conditions (standard meal = 16.5%, high-fat meal = 21.8%) compared with fasted condition. The final model displayed good prediction power and precision. CONCLUSIONS: A mechanistic GI absorption model for quantitatively evaluating the effects of food on fenofibrate absorption was successfully developed, and acceptable parameters were obtained. The mechanism-based PK model of fenofibrate can quantify the effects of food on drug absorption by food type and calorie content.

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.

BACKGROUND: Exploratory 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. METHODS: In 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 ω 2 ), 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. RESULTS: The 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. CONCLUSIONS: The 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.

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.

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.

Bioequivalence Comparison of Two Formulations of Fixed-Dose Combination Glimepiride/Metformin (2/500 mg)Tablets in Healthy Volunteers.

Glimepiride/metformin (2/500 mg) is an oral antihyperglycemic agent for the treatment of type 2 diabetes. A generic glimepiride/metformin (2/500 mg) fixed-dose combination (FDC) tablet was developed recently. This study was designed to collect data for submission to Korean regulatory authorities to allow the marketing of the test formulation. We evaluated the comparative bioavailability and tolerability of the test and reference formulations in healthy male adult volunteers. This single-dose, randomized, double-blind, two-way crossover trial was conducted at Bestian Medical Center in Bucheon, Korea. In total, 40 male Korean volunteers were enrolled. The subjects were randomized to receive an FDC tablet containing the glimepiride/metformin (2/500 mg) test or reference formulation, and pharmacokinetic(PK) parameters were measured. After a 1-week washout period, the other formulation was administered and the PK parameters were measured again. The Cmax and AUCt were determined from blood samples obtained at 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 5, 6, 8, 12, and 24 h after drug administration. Bioequivalence was considered established if the 90% CIs of the geometric mean ratios(GMRs) of the test-to-reference formulations for Cmax and AUCt were within the predetermined regulatory range of 80-125%. In total, 40 healthy male subjects were enrolled and completed the study (mean [SD] age, 23.2[2.26]years[range, 19-30years];weight, 68.95[8.30]Kg[range, 52.0-87.0 Kg]; and height, 175.4[5.34] cm[range, 164-189 cm]). The GMRs(90% CI) of the glimepiride Cmax and AUCt were 1.006(0.947-1.069) and 1.010(0.953-1.071), respectively. For metformin, the values were 1.019(0.959-1.083) and 1.035(0.989-1.084), respectively. The test and reference formulations had similar PK parameters. The test formulation of glimepiride/metformin (2/500 mg) FDC tablets met the Korean regulatory criteria for bioequivalence.

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.

Effect of dissolved oxygen in alcoholic beverages and drinking water on alcohol elimination in humans.

Oxygen plays an important role in the metabolism of alcohol. An increased dissolved oxygen level in alcoholic beverages reportedly accelerates the elimination of alcohol. Therefore, we evaluated the effect of dissolved oxygen in alcohol and the supportive effect of oxygenated water on alcohol pharmacokinetics after the excessive consumption of alcohol, i.e., 540 ml of 19.5% alcohol (v/v). Fifteen healthy males were included in this randomized, 3 × 3 crossover study. Three combinations were tested: X, normal alcoholic beverage and normal water; Y, oxygenated alcoholic beverage and normal water; Z, oxygenated alcoholic beverage and oxygenated water. Blood alcohol concentrations (BACs) were determined by conversion of breath alcohol concentrations. Four pharmacokinetic parameters (C(max), T(max), K(el), and AUCall) were obtained using non-compartmental analysis and the times to reach 0.05% and 0.03% BAC (T(0.05%) and T(0.03%)) were compared using one-way analysis of variance (ANOVA) and Duncan's post hoc test. With combination Z, the BAC decreased to 0.05% significantly faster (p < 0.05) than with combination X. Analyzing the pharmacokinetic parameters, the mean K(el) was significantly higher for combination Z than for combinations X and Y (p < 0.05), whereas the mean values of C(max), T(max) and AUCall did not differ significantly among the combinations. Dissolved oxygen in drinks accelerates the decrease in BAC after consuming a large amount of alcohol. However, the oxygen dissolved in the alcoholic beverage alone did not have a sufficient effect in this case. We postulate that highly oxygenated water augments the effect of oxygen in the alcoholic beverage in alcohol elimination. Therefore, it is necessary to investigate the supportive effect of ingesting additional oxygenated water after heavy drinking of normal alcoholic beverages.