Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone. We simulated 1000 virtual pharmacokinetic clinical trial datasets based on single-period and dense sampling studies, with various study sizes and levels of WSV and interindividual variabilities (IIVs). The estimated residual variability (RV) resulting from population pharmacokinetic methods were compared with WSV values. In addition, 3 × 3 bioequivalence results of eperisone were used to evaluate method performance with a real clinical dataset. With WSV of 40% or less, regardless of IIV magnitude, RV was well approximated by WSV for sample sizes greater than 18 subjects. RV was underestimated at WSV of 50% or greater, even with datasets having low IIV and numerous subjects. Using the eperisone dataset, RV was 44% to 48%, close to the true value of 50%. In conclusion, the estimated RV accurately predicted WSV in single-period studies, validating this method for sample size estimation in clinical trials.

Pharmacokinetics of eperisone following oral administration in healthy Korean volunteers.

Eperisone is an oral muscle relaxant used to treat musculoskeletal diseases, which exhibits high pharmacokinetic (PK) variability in bioequivalence studies. The aim of this study was to characterize the PKs of eperisone following its oral administration to Korean volunteers through the conduct of a noncompartmental and population analysis. A total of 360 concentration-time measurements collected on two separate occasions from 15 healthy volunteers during a bioequivalent study of eperisone 50 mg (Murex® ) were used in the PK analysis. Noncompartmental analysis was performed using WinNonLinTM and population analysis was performed using NONMEM® . The possible influence of thirty demographic and pathophysiological characteristics on the PKs of eperisone were explored. Based on noncompartmental analysis mean eperisone elimination half-life, apparent clearance (CL/F), and apparent volume of distribution were estimated to be 3.81 h, 39.24 × 103  l/h × 103  L, respectively. During population PK modeling a two-compartment model with first-order absorption rate constant (typical population K a  = 1.5 h-1 ) and first-order elimination (typical population CL/F and apparent volume of distribution in the central compartment [V c /F] = 30.8 × 103  l/h and 86.2 × 103  l, respectively) best described the PKs of eperisone. Interindividual variability in CL/F and V c /F were estimated to be 87.9% and 130.3%, respectively and interoccasion variability in CL/F and V c /F were estimated to be 23.8% and 30.8%, respectively. Aspartate aminotransferase level and smoking status were identified as potential covariates that may influence the CL/F of eperisone. This is the first study to develop a disposition model for eperisone and investigate the potential influence of covariate factors on it PK variability.

Clinical Evaluation of Acetaminophen-Galgeuntang Interaction Based on Population Approaches.

Galgeuntang (GGT), a traditional herbal medicine, is widely co-administered with acetaminophen (AAP) for treatment of the common cold, but this combination has not been the subject of investigation. Therefore, we investigated the herb-drug interaction between GGT and AAP by population pharmacokinetics (PKs) modeling and simulation studies. To quantify PK parameters and identify drug interactions, an open label, three-treatment, three-period, one-sequence (AAP alone, GGT alone, and AAP and GGT in combination) clinical trial involving 12 male healthy volunteers was conducted. Ephedrine (EPD), the only GGT component detected, was identified using a one-compartment model. The PKs of AAP were described well by a one-compartment model and exhibited two-phase absorption (rapid followed by slow) and first-order elimination. The model showed that EPD significantly influenced the PKs of AAP. The simulation results showed that at an AAP dose of 1000 mg × 4 times daily, the area under the concentration versus time curve of AAP increased by 16.4% in the presence of GGT compared to AAP only. In conclusion, the PKs of AAP were affected by co-administration of GGT. Therefore, when AAP is combined with GGT, adverse effects related to overdose of AAP could be induced possibly.

Development of a Pharmacokinetic Model Describing Neonatal Fc Receptor-Mediated Recycling of HL2351, a Novel Hybrid Fc-Fused Interleukin-1 Receptor Antagonist, to Optimize Dosage Regimen.

HL2351 (hIL-1Ra-hyFc) is a novel recombinant protein formed by the fusion of two human interleukin-1 receptor antagonist components into one antibody-derived fragment crystallizable portion. Although HL2351 has a pharmacological mechanism of action similar to that of anakinra as a commercialized biopharmaceutical drug, HL2351 has been desired to reduce the dose frequency and improve therapeutic efficacy due to its long circulation half-life. In this study, we aimed to develop a population pharmacokinetic (PK) model for HL2351 using a neonatal Fc receptor (FcRn)-mediated recycling model based on a quasi-steady-state approximation of target-mediated drug disposition (TMDD) for the description of interactions between the drug and FcRn. FcRn recycling was expected in the case of HL2351 because of PK related to the antibody portion. A TMDD model was also applied to describe interactions of IL1R with HL2351 or anakinra. PK data were collected from a phase I study conducted in six groups (1, 2, 4, 8, 12 mg/kg HL2351 and 100 mg anakinra single subcutaneous administration; n = 8 per group). In consequence, the PK of anakinra and HL2351 following administration of multiple doses at different dosages were simulated. Optimized doses were considered based on average concentrations of IL1R bound to anakinra and HL2351. HL2351 at doses of 326 mg or 4.267, 4.982, 5.288, 5.458, or 5.748 mg/kg once weekly or HL2351 at 1726 mg or 21.92, 26.86, 29.10, 30.36, or 32.53 mg/kg once biweekly would have similar therapeutic effects with anakinra at a dose of 100 mg or 1, 2, 3, 4, or 8 mg/kg administered once daily, respectively.

Pharmacokinetic Modeling of the Impact of P-glycoprotein on Ondansetron Disposition in the Central Nervous System.

PURPOSE: Modulation of 5-HT3 receptor in the central nervous system (CNS) is a promising approach for treatment of neuropathic pain. The goal was to evaluate the role of P-glycoprotein (Pgp) in limiting exposure of different parts of the CNS to ondansetron (5-HT3 receptor antagonist) using wild-type and genetic knockout rat model. METHODS: Plasma pharmacokinetics and CNS (brain, spinal cord, and cerebrospinal fluid) disposition was studied after single 10 mg/kg intravenous dose. RESULTS: Pgp knockout resulted in significantly higher concentrations of ondansetron in all tested regions of the CNS at most of the time points. The mean ratio of the concentrations between KO and WT animals was 2.39-5.48, depending on the region of the CNS. Male and female animals demonstrated some difference in ondansetron plasma pharmacokinetics and CNS disposition. Mechanistic pharmacokinetic model that included two systemic disposition and three CNS compartments (with intercompartmental exchange) was developed. Pgp transport was incorporated as an efflux from the brain and spinal cord to the central compartment. The model provided good simultaneous description of all data sets, and all parameters were estimated with sufficient precision. CONCLUSIONS: The study provides important quantitative information on the role of Pgp in limiting ondansetron exposure in various regions of the CNS using data from wild-type and Pgp knockout rats. CSF drug concentrations, as a surrogate to CNS exposure, are likely to underestimate the effect of Pgp on drug penetration to the brain and the spinal cord.

Pharmacokinetics of Shikimic Acid Following Intragastric and Intravenous Administrations in Rats.

Shikimic acid, a critical starting material for the semi-total synthesis of oseltamivir to treat and prevent influenza, exerts many pharmacological effects. However, the optimal bioanalytical method has not been adequately defined. We used liquid chromatography-tandem mass spectrometry to quantitate shikimic acid in rat plasma and studied its pharmacokinetics after intragastric and intravenous administration. Plasma was spiked with an internal standard, and the proteins were precipitated with acetonitrile, followed by solvent evaporation and reconstitution of the mobile phase. Shikimic acid was separated on a hydrophilic reverse-phase column and showed a mass transition ([M-H]-) at m/z 173.4→136.6. Shikimic acid exhibited bi-exponential decay after intravenous dosing, with a rapid distribution (5.57 h-1) up to 1 h followed by slow elimination (0.78 h-1). The steady state distribution and clearance volumes were 5.17 and 1.79 L/h/kg, respectively. After intragastric administration, the shikimic acid level peaked at about 3 h, and the material then disappeared mono-exponentially with a half-life of 1.3 h. A double peak phenomenon was observed. The absolute oral bioavailability was about 10% in rats. We explored the relationship between the pharmacokinetics and pharmacodynamics of shikimic acid.

Redox Imbalance and Oxidative DNA Damage During Isoniazid Treatment of HIV-Associated Tuberculosis: A Clinical and Translational Pharmacokinetic Study.

BACKGROUND: The potential for hepatotoxicity during isoniazid-based tuberculosis (TB) treatment presents a major challenge for TB control programs worldwide. We sought to determine whether pharmacokinetic exposures of isoniazid and its metabolites were related to cellular oxidation/reduction status and downstream markers of oxidative DNA damage. METHODS: We performed intensive pharmacokinetic sampling among isoniazid-treated patients to determine the relative plasma exposures of isoniazid, acetylisoniazid, hydrazine, and acetylhydrazine. Physiologically-based pharmacokinetic modeling was used to estimate liver tissue exposures during a 24-h dosing interval for each compound. We experimentally treated HepG2 cells with isoniazid and metabolites at equimolar concentrations corresponding to these exposures for 7, 14, and 28-day periods, and performed assays related to redox imbalance and oxidative DNA damage at each timepoint. We related a urine marker of oxidative DNA damage to serum isoniazid pharmacokinetic exposures and pharmacogenetics in a clinical study. RESULTS: Among isoniazid-treated patients, serum concentrations of hydrazine and isoniazid concentrations were highly correlated. At equimolar concentrations that approximated hepatic tissue exposures during a 24-h dosing interval, hydrazine demonstrated the highest levels of redox imbalance, mitochondrial injury, and oxidative DNA damage over a 28-day treatment period. In a clinical validation study of isoniazid-treated TB patients, peak isoniazid serum concentrations were positively associated with a urine biomarker of oxidative DNA damage. CONCLUSIONS: Isoniazid and its metabolites share the potential for oxidative cellular damage, with the greatest effects observed for hydrazine. Future studies should investigate the clinical consequences of oxidative stress with regards to clinical episodes of drug induced liver injury during isoniazid treatment.

Exposure-Response and Clinical Outcome Modeling of Inhaled Budesonide/Formoterol Combination in Asthma Patients.

Exposure-response and clinical outcome (CO) model for inhaled budesonide/formoterol was developed to quantify the relationship among pharmacokinetics (PK), pharmacodynamics (PD) and CO of the drugs and evaluate the covariate effect on model parameters. Sputum eosinophils cationic proteins (ECP) and forced expiratory volume (FEV1) were selected as PD markers and asthma control score was used as a clinical outcome. One- and two-compartment models were used to describe the PK of budesonide and formoterol, respectively. The indirect response model (IDR) was used to describe the PD effect for ECP and FEV1. In addition, the symptomatic effect on the disease progression model for CO was connected with IDR on each PD response. The slope for the effect of ECP and FEV1 to disease progression were estimated as 0.00008 and 0.644, respectively. Total five covariates (ex. ADRB2 genotype etc.) were searched using a stepwise covariate modeling method, however, there was no significant covariate effect. The results from the simulation study were showed that a 1 puff b.i.d. had a comparable effect of asthma control with a 2 puff b.i.d. As a result, the 1 puff b.i.d. of combination drug could be suggested as a standardized dose to minimize the side effects and obtain desired control of disease compared to the 2 puff b.i.d.

Beyond the Michaelis-Menten: Accurate Prediction of In Vivo Hepatic Clearance for Drugs With Low KM.

Clearance (CL) is the major pharmacokinetic parameter for evaluating systemic exposure of drugs in the body and, thus, for developing new drugs. To predict in vivo CL, the ratio between the maximal rate of metabolism and Michaelis-Menten constant (Vmax /KM estimated from in vitro metabolism study has been widely used. This canonical approach is based on the Michaelis-Menten equation, which is valid only when the KM value of a drug is much higher than the hepatic concentration of the enzymes, especially cytochrome P450, involved in its metabolism. Here, we find that such a condition does not hold for many drugs with low KM , and, thus, the canonical approach leads to considerable error. Importantly, we propose an alternative approach, which incorporates the saturation of drug metabolism when concentration of the enzymes is not sufficiently lower than KM . This new approach dramatically improves the accuracy of prediction for in vivo CL of high-affinity drugs with low KM . This indicates that the proposed approach in this study, rather than the canonical approach, should be used to predict in vivo hepatic CL for high-affinity drugs, such as midazolam and propafenone.

Application of an Inter-Species Extrapolation Method for the Prediction of Drug Interactions between Propolis and Duloxetine in Humans.

Duloxetine (DLX) is a potent drug investigated for the treatment of depression and urinary incontinence. DLX is extensively metabolized in the liver by two P450 isozymes, CYP2D6 and CYP1A2. Propolis (PPL) is one of the popular functional foods known to have effects on activities of CYPs, including CYP1A2. Due to the high probability of using DLX and PPL simultaneously, the present study was designed to investigate the potent effect of PPL on pharmacokinetics (PKs) of DLX after co-administration in humans. A PK study was first conducted in 18 rats (n = 6/group), in which the plasma concentration of DLX and its major metabolite 4-hydroxy duloxetine (4-HD) with or without administration of PPL was recorded. Population PKs and potential effects of PPL were then analyzed using NONMEM software. Lastly, these results were extrapolated from rats to humans using the allometric scaling and the liver blood flow method. PPL (15,000 mg/day) exerts a statistically significant increase in DLX exposures at steady state, with a 20.2% and 24.6% increase in DLX C m a x , s s and the same 28.0% increase in DLX A U C s s when DLX (40 or 60 mg) was administered once or twice daily, respectively. In conclusion, safety issues are required to be attended to when individuals simultaneously use DLX and PPL at high doses, and the possibility of interactions between DLX and PPL might be noted.

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.

Dose Optimization Based on Population Pharmacokinetic Modeling of High-Dose Cyclosporine, a P-glycoprotein Inhibitor, in Combination with Systemic Chemotherapy in Pediatric Patients with Retinoblastoma.

PURPOSE: Retinoblastoma is a childhood malignancy of the retina. To increase the exposures of systemic chemotherapy, high-dose cyclosporine, as a P-glycoprotein modulating agent, has been combined with a standard chemotherapy. However, the effective and safe dose of cyclosporine has not been well evaluated. This study is to optimize cyclosporine dose using population pharmacokinetic modeling. METHODS: Clinical data were obtained from 161 systemic chemotherapy cycles of 34 pediatric retinoblastoma patients between December 2006 and April 2015. Total 15 scenarios were simulated by 5 different doses (12, 14, 15, 17, and 20 mg/kg) of cyclosporine in 3 different weight groups (5-10, 10-15, and 15-20 kg). Numerical success ratio was obtained after assessing the simulated target cyclosporine concentration in the range of 2,000-2,500 ng/mL using NONMEM version 7.3 software. RESULTS: A final model was built based on a 1-compartment model with weight-normalized allometric scaling to minimize the variability of pediatric size. In simulations, numeric success ratio with 15 mg/kg/day and the above were higher than that of traditional doses in all of the scenario groups. No significant adverse responses were reported. Conclusion and Relevance: High-dose cyclosporine regimen as a P-gp modulator is required to improve the efficacy of systemic chemotherapy with caution in pediatric patients with retinoblastoma. Clearance, volume of distribution, and body weight are important parameters to consider in selecting adequate dosing regimen.

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.

BSA and ABCB1 polymorphism affect the pharmacokinetics of sunitinib and its active metabolite in Asian mRCC patients receiving an attenuated sunitinib dosing regimen.

PURPOSE: An attenuated dosing (AD) sunitinib regimen of 37.5 mg daily has been suggested to reduce the toxicity reported with the standard dosing regimen to metastatic renal cell carcinoma (mRCC) patients. The aim of this study was to characterize the population pharmacokinetic (PK) properties of sunitinib and SU12662, the active metabolite, in patients receiving the AD regimen and to ascertain significant covariates influencing PK parameters. METHODS: Thirty-one mRCC patients receiving AD sunitinib regimen were included. Plasma samples were collected on day 29 of each treatment cycle after the start of the therapy. Nonlinear mixed-effects modeling was applied to estimate the population PK properties of sunitinib and SU12662 as well as the effect of covariates on PK parameters. Monte Carlo simulation was also performed to predict the total trough level (TTL) of sunitinib and SU12662. RESULTS: Sunitinib population means for CL/F and V d /F central were 13.8 L/h and 1720 L, respectively. SU12662 population means for CL/F and V d /F were 42.1 L/h and 1410 L, respectively. Body surface area (BSA) and ABCB1 polymorphism significantly influenced the CL/F variability of sunitinib: CL/F parent = 13.8 × exp((BSA - 1.75) × 2.08 + (ABCB1 genotype - 0.67) × 0.61), ABCB1-0: wild genotype, 1: mutant genotype. The effect size of ABCB1 mutant genotype and BSA greater than 1.75 m(2) in relation to sunitinib clearance was 31.14 % (p = 0.006) and 22.11 % (p = 0.011), respectively, relative to the reference group. CONCLUSIONS: Adjusting doses of sunitinib according to BSA and ABCB1 polymorphism in Asian mRCC patients may be recommended for sufficient attainment of a target TTL of sunitinib and its metabolite.

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.

Development of QTc prolongation model incorporating circadian rhythm using harmonic model.

1. QT prolongation is one of the major safety tests used in the development of a new drug. The ICH guidelines for the evaluation of QT prolongation recommend the use of the in vitro hERG assay and the in vivo telemetry test. However, QT intervals change under normal conditions due to circadian rhythm and can affect the results of the tests. In this study, we developed a PK/PD model to describe the QT interval after the administration of astemizole allowing for the normal changes by circadian rhythm. 2. The typical PK parameters of absorption rate constant (ka), volume of distribution (Vc and Vm), metabolism (km), and elimination rate constant (kel and kel-m) were 0.49 h(-1), 4950 L, 20 L, 0.0127 h(-1), 0.0095 h(-1), and 0.95 h(-1), respectively. The final PK/PD model was the biophase model with the modified harmonic model. The typical PK/PD parameters, base QTc interval (QT0), amplitude (T1, T3), period of QTc interval changing (T2, T4), and EC50 were 233 ms, 3.31, 1.5, -9.24 h, 1.85 h, and 0.81 ng/ml, respectively. 3. The PK/PD model to explain the changes of the QT interval that allows normal changes in the circadian rhythm after the administration of astemizole was developed successfully. This final model can be applied to the development of a human model.

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.