Byung-yo Lee

Development and validation of a sensitive LC-MS/MS method for the simultaneous quantitation of theophylline and its metabolites in rat plasma.

A rapid, specific, and reliable LC-MS/MS-based bioanalytical method was developed and validated in rat plasma for the simultaneous quantitation of theophylline and its four metabolites: 1,3-dimethyluric acid (1,3-DMU), 3-methylxanthine (3-MX), 1-methylxanthine (1-MX), and 1-methyluric acid (1-MU). Chromatographic separation of these analytes was achieved on a Gemini C18 column (50 mm × 4.60 mm, 5 μm) using reversed phase chromatography. The analytes were monitored by electrospray ionization in negative ion multiple reaction monitoring mode. Modification of collision energies was performed in parallel with chromatographic separation to further eliminate interference peaks. The method was validated from 0.05 to 30 μg/mL for 1-MX, 1,3-DMU, 1-MU, and theophylline and from 0.1 to 30 μg/mL for 3-MX using 0.2 mL of plasma sample. The intra- and inter-day precision and accuracy of the quality control samples at low, medium, and high concentration levels exhibited relative standard deviations (RSD) of less than 13% and with relative error (RE) values of -8.8% to 9.7%. The method was successfully applied for the quantitation of theophylline and its metabolite in rat plasma samples.

Influence of Dissolved Oxygen Concentration on the Pharmacokinetics of Alcohol in Humans

BACKGROUND Ethanol oxidation by the microsomal ethanol oxidizing system requires oxygen for alcohol metabolism, and a higher oxygen uptake increases the rate of ethanol oxidation. We investigated the effect of dissolved oxygen on the pharmacokinetics of alcohol in healthy humans (n = 49). The concentrations of dissolved oxygen were 8, 20, and 25 ppm in alcoholic drinks of 240 and 360 ml (19.5% v/v). METHODS Blood alcohol concentrations (BACs) were determined by converting breath alcohol concentrations. Breath samples were collected every 30 min when the BAC was higher than 0.015%, 20 min at BAC < or =0.015%, 10 min at BAC < or =0.010%, and 5 min at BAC < or =0.006%. RESULTS The high dissolved oxygen groups (20, 25 ppm) descended to 0.000% and 0.050% BAC faster than the normal dissolved oxygen groups (8 ppm; p < 0.05). In analyzing pharmacokinetic parameters, AUC(inf) and K(el) of the high oxygen groups were lower than in the normal oxygen group, while C(max) and T(max) were not significantly affected. In a Monte Carlo simulation, the lognormal distribution of mean values of AUC(inf) and t(1/2) was expected to be reduced in the high oxygen group compared to the normal oxygen group. CONCLUSIONS In conclusion, elevated dissolved oxygen concentrations in alcoholic drinks accelerate the metabolism and elimination of alcohol. Thus, enhanced dissolved oxygen concentrations in alcohol may have a role to play in reducing alcohol-related side effects and accidents.

Comparison of average, scaled average, and population bioequivalence methods for assessment of highly variable drugs: An experience with doxifluridine in beagle dogs

Several strategies for overcoming the challenge of establishing bioequivalence (BE) for highly variable drugs (HVDs; drugs having within-subject variability >0.3) have been considered in recent years. Within-subject variability of the area under the curve (AUC(4h)) and peak concentration (C(max)) of doxifluridine in the minimal group (n=24) were 0.444 and 0.491, respectively, meeting the criteria for an HVD. For the large group (n=60), within-subject variability of the AUC(4h) and C(max) were 0.431 and 0.493, respectively. The 90% confidence interval for the AUC(4h) and C(max) of the ratio of the test drug to the reference drug exceeded the acceptable BE limits (0.80-1.25) of the ABE (average bioequivalence), in both the minimal and large groups. However, the 90% CI fell within the extended BE limits (0.61-1.64) of the SABE (scaled average bioequivalence), calculated using within-subject variability. The 95% CI of the AUC(4h) and C(max) of the ratio of test to reference drug were within the extended BE limit (<1.73) of the PBE (population bioequivalence), calculated using total variance. Our results suggest that the SABE method may be useful for evaluating the BE of HVDs and for meeting the need for international guidelines for BE.

Development of a pharmacokinetic/pharmacodynamic/disease progression model in NC/Nga mice for development of novel anti-atopic dermatitis drugs.

Abstract 1. JHL45, a novel immune modulator against atopic dermatitis (AD), was synthesized from decursin isolated from Angelica gigas. The goal is to evaluate the lead compound using quantitative modeling approaches to novel anti-AD drug development. 2. We tested the anti-inflammatory effect of JHL45 by in vitro screening, characterized its in vitro pharmacokinetic (PK) properties. The dose-dependent efficacy of JHL45 was developed using a pharmacokinetics/pharmacodynamics/disease progression (PK/PD/DIS) model in NC/Nga mice. 3. JHL45 has drug-like properties and pharmacological effects when administered orally to treat atopic dermatitis. The developed PK/PD/DIS model described well the rapid metabolism of JHL45, double-peak phenomenon in the PK of decursinol and inhibition of IgE generation by compounds in NC/Nga mice. Also, a quantitative model was developed and used to elucidate the complex interactions between serum IgE concentration and atopic dermatitis symptoms. 4. Our findings indicate that JHL45 has good physicochemical properties and powerful pharmacological effects when administered orally for treatment of AD in rodents.

Population PK/PD analysis of metformin using the signal transduction model

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT Metformin, a biguanide glucose lowering agent, is commonly used to manage type 2 diabetes. The molecular mechanisms of metformin have not been fully identified, but turnover of biomarkers such as glucose and signalling pathways or translocation of glucose transporters are closely related to the glucose-lowering effects of metformin. The PK/PD of metformin have been investigated in healthy humans and patients with type 2 diabetes mellitus and modelling has been performed using an indirect response model. WHAT THIS STUDY ADDS The purpose of this investigation was to develop a population PK/PD model for metformin using a signal transduction model in healthy humans and predict the PK/PD profile in patients with type 2 diabetes. The aim was to compare a previous model (a biophase model) with the signal transduction model, and use a more appropriate model to follow the actions of metformin. Additionally, our developed model was appropriate to predict the time course of plasma metformin and fasting plasma glucose (FPG) concentrations in patients with type 2 diabetes. To our knowledge, this is the first published population PK/PD analysis using the signal transduction model for metformin. AIMS To develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model for metformin (500 mg) using the signal transduction model in healthy humans and to predict the PK/PD profile in patients with type 2 diabetes. METHODS Following the oral administration of 500 mg metformin to healthy humans, plasma concentrations of metformin were measured using LC-MS/MS. A sequential modelling approach using NONMEM VI was used to facilitate data analysis. Monte Carlo simulation was performed to predict the antihyperglycaemic effect in patients with type 2 diabetes. RESULTS Forty-two healthy humans were included in the study. Population mean estimates (relative standard error, RSE) of apparent clearance, apparent volume of distribution and the absorption rate constant were 52.6 l h(-1) (4.18%), 113 l (56.6%) and 0.41 h(-1) , respectively. Covariate analyses revealed that creatinine clearance (CL(CR) ) significantly influenced metformin: CL/F= 52.6 × (CL(cr) /106.5)(0.782) . The signal transduction model was applied to describe the antihyperglycaemic effect of metformin. The population means for efficacy, potency, transit time and the Hill coefficient were estimated to be 19.8 (3.17%), 3.68 µg ml(-1) (3.89%), 0.5 h (2.89%) and 0.547 (9.05%), respectively. The developed model was used to predict the antihyperglycaemic effect in patients with type 2 diabetes. The predicted plasma glucose concentration value was similar to previous values. CONCLUSIONS The population signal transduction model was developed and evaluated for metformin use in healthy volunteers. Model evaluation by non-parametric bootstrap analysis suggested that the proposed model was robust and parameter values were estimated with good precision.

A simple pharmacokinetic model of alendronate developed using plasma concentration and urine excretion data from healthy men

Abstract The study of pharmacokinetics of alendronate has been hampered by difficulties in accurately and reproducibly determining their concentrations in serum and urine. Thus, pharmacokinetic characteristics of alendronate have been described in many reports based on urinary excretion data; and plasma pharmacokinetics and the simultaneous pharmacokinetic models of alendronate in plasma and urine are not available. The aims of this study were to measure alendronate concentration in plasma and excretion in urine concurrently and to develop compartmental pharmacokinetic model using urine data. In open-label, single-dose pharmacokinetic study, 10 healthy male volunteers received oral dose of alendronate (70 mg tablet). Blood and urine alendronate concentrations were determined using validated high-performance liquid chromatography method. Non-compartmental analysis was performed using WinNonlin program (Pharsight Inc., Apex, NC). A one-compartment pharmacokinetic model was applied to describe pharmacokinetics of alendronate. A peak plasma alendronate concentration of 33.10 ± 14.32 ng/mL was attained after 1.00 ± 0.16 h. The cumulative amount of alendronate excreted in urine and peak excretion rate were 731.28 ± 654.57 μg and 314.68 ± 395.43 μg/h, respectively. The model, which included first-order absorption rate for oral dosing, showed good fit to alendronate data obtained from plasma and urine. The absorption rate constant was 2.68 ± 0.95 h–1. The elimination rate constants Kurine and Knon-ur were 0.005 ± 0.004 h−1 and 0.42 ± 0.08 h−1, respectively. The pharmacokinetics of alendronate in plasma and urine of healthy men can be predicted using one-compartment model, and thus the behavior of drug in plasma can be estimated from urinary excretion data.

Semi-mechanistic modelling and simulation of inhibition of platelet aggregation by antiplatelet agents.

Antiplatelet agents are a class of pharmaceuticals that decrease platelet aggregation and thus inhibit thrombus formation. We examined the relationships between plasma concentrations of antiplatelet agents (triflusal, clopidogrel and cilostazol) and the platelet aggregation inhibitory effect after dosing. We used triflusal, cilostazol and clopidogrel for the development of a semi‐mechanistic PK/PD model. The drugs chosen are used widely and reflect various mechanisms of antiplatelet agents. Time courses of plasma concentrations of the antiplatelet agents and their platelet aggregation effects were analysed using ADPAT V. Pharmacokinetic profiles were fitted to an extended parent–metabolite pharmacokinetic model, based on a two‐compartment model, and the pharmacodynamic effects of the agents were fitted to a platelet aggregation effect model that consisted of the following parameters: Ks, the active‐form platelet synthesis rate constant; K, the apparent reaction rate constant of the agent and active‐form platelets; Kel‐PRP, the apparent rate constant of platelets; and ε, an intrinsic activity parameter. This semi‐mechanistic PK/PD model described well the relationship between plasma concentrations of antiplatelet agents and platelet aggregation effects. In addition, the estimated parameters were suitable for the explanation of the agents and also have a good correlation with platelet characteristics, such as platelet half‐life and platelet aggregation baseline effects. Specifically, we discovered the strong correlations between estimated K parameter and in vitro drug activity. We conclude that this semi‐mechanistic PK/PD model explained drug PK/PD characteristics well and will be useful for accurate predictions of antiplatelet effect in the clinical situations.

Effect of food intake on the pharmacokinetics of sarpogrelate and its active metabolite following oral administration to beagle dogs

Abstract 1. The objectives of this study were to develop a pharmacokinetic model for sarpogrelate and its metabolite M-1 and to identify the effect of food on sarpogrelate and M-1 pharmacokinetics in beagle dogs. 2. A single 100 mg oral dose of sarpogrelate was administered to fasted and fed beagle dogs and the plasma concentrations of sarpogrelate and M-1 were measured simultaneously by liquid chromatography tandem mass spectrometry. The resultant data were analyzed by modeling approaches using ADAPT5. 3. The plasma concentration time course of sarpogrelate and M-1 were described using a parent-metabolite compartment model with first-order absorption and elimination. The systemic exposure of sarpogrelate and its metabolite after the administration of a single 100 mg oral dose was significantly decreased under the fed condition compared to that under the fasting condition. Modeling approaches have sufficiently explained the food effect of sarpogrelate, i.e. an increased Vc and decreased Ka, in fed dogs. The food effect of sarpogrelate was due to its pH-dependent dissolution. 4. These findings suggest that food intake affects both the rate and extent of absorption of sarpogrelate, and that the pharmacological effect of sarpogrelate can differ significantly according to food intake.

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.

Pharmacokinetics of angiotensin II receptor blockers in the dog following a single oral administration.

Angiotensin II receptor blockers (ARBs) are effective and well-tolerated orally active anti-hypertensive agents. The purpose of this study was to investigate the pharmacokinetic properties of typical ARBs in the dog. 60 beagles were administered a single oral dose of Micardis® 80 mg (telmisartan), Cozaar® 50 mg (losartan), or Diovan® 80- and 160-mg (valsartan). The plasma concentrations of these ARBs were measured using liquid chromatography/tandem mass spectrometry and their pharmacokinetic properties were analyzed using both non-compartmental and compartmental approaches. The half-life and volume of distribution in dogs were in the order losartan>valsartan>telmisartan after oral administration. Systemic exposure was estimated by calculating the area under the plasma concentration-vs.-time curve from time zero to infinity (AUC inf ), and resulted in the order telmisartan>valsartan>losartan. The values of C max and AUC increased in proportion to the dose of valsartan. In compartmental analysis, the pharmacokinetics of telmisartan and losartan pharmacokinetics fit a 2-compartment model, while valsartan fit a 1-compartment model. These results provide detailed pharmacokinetic information of ARBs in the dog, and may aid in future development of improved formulations or fixed-dose combinations.