Journal Detail Information

1

Cite

Share

Determination of sumatriptan in human plasma using liquid chromatography-mass spectrometry for pharmacokinetic study in healthy Korean volunteers.

Seungil CHO ; Moonyoung JEGAL ; Boram OHK ; Bo Kyung KIM ; Mi Ri GWON ; Woo Youl KANG ; Sook Jin SEONG ; Hyun Ju KIM ; Hae Won LEE ; Young Ran YOON

Translational and Clinical Pharmacology.2017;25(2):106-111. doi:10.12793/tcp.2017.25.2.106

This study describes the development of an analytical method to determine sumatriptan levels in human plasma using high performance liquid chromatography (HPLC) coupled with triple quadrupole tandem mass spectrometry (MS/MS) and its application to a pharmacokinetic study in healthy Korean volunteers. A single 50 mg dose of sumatriptan was orally administered to twelve healthy volunteers (nine women and three men). The HPLC-MS/MS analytical method was validated with respect to its specificity, linearity, sensitivity, accuracy, precision, recovery, and stability. The calibration curve was linear over a concentration range of 0.3–100 ng/mL (r > 0.999). The lower limit of quantitation for sumatriptan in plasma was 0.3 ng/mL. The accuracy and precision of the analytical method were acceptable within 15% at all quality control levels. We compared plasma concentration-time curves as well as pharmacokinetic parameters such as the area under the curve (AUC) and maximum plasma concentration (C(max)). Both the mean AUC and C(max) of sumatriptan were 1.56 times higher in women than in men. These differences could be largely explained by the difference in body weight (44%) between women and men. The outcomes may provide insights into developing appropriate individualized treatment strategies.
Area Under Curve ; Body Weight ; Calibration ; Chromatography, Liquid ; Female ; Healthy Volunteers ; Humans* ; Male ; Methods ; Plasma* ; Quality Control ; Sensitivity and Specificity ; Spectrum Analysis* ; Sumatriptan* ; Tandem Mass Spectrometry ; Volunteers*

2

Cite

Share

Relationship between body weight and postmenstrual age in a Korean pediatric population.

Jinju GUK ; Dongwoo CHAE ; Kyungsoo PARK

Translational and Clinical Pharmacology.2017;25(2):101-105. doi:10.12793/tcp.2017.25.2.101

Weight is a covariate representative of body size and is known to influence drug disposition. Recently, with increased use of allometric scaling, this variable has become more significant in accounting for variability in pharmacokinetic parameters. In adults, weight can be considered as a time invariant covariate because physical development is complete. As a result, when weight is missing in data, the typical or median value (say, 70 kg) could be imputed. On the contrary, weight continuously changes with age in the pediatric population. In this case, it is more appropriate to consider different median weight for each age group. We constructed a prediction model for weight using postmenstrual age (PMA) with the data consisting of 83,014 Korean pediatric patients. Weight, PMA, and gender information were collected from electronic medical records. Sigmoid models multiplied by exponential or logistic function were tested for basic model structure. Covariate effects on model parameters were then investigated using selection criteria of p < 0.001. All analyses were performed using NONMEM 7.3.0 and R3.2.0. The sigmoid model multiplied by logistic function best described the data and there was a significant difference between boys and girls in model parameters. It is expected that the results obtained in this work can be used for imputation of missing weights in pediatrics when PMA is available. In addition, the developed model can be used for clinical studies in children under 12 years old whose weight change rapidly with age and for model building in dealing with time varying body weight as a covariate.
Adult ; Body Size ; Body Weight* ; Child ; Colon, Sigmoid ; Electronic Health Records ; Female ; Humans ; Patient Selection ; Pediatrics ; Weights and Measures

3

Cite

Share

Bioequivalence data analysis for the case of separate hospitalization.

Kyun Seop BAE ; Seung Ho KANG

Translational and Clinical Pharmacology.2017;25(2):93-100. doi:10.12793/tcp.2017.25.2.93

A bioequivalence study is usually conducted with the same-day drug administration. However, hospitalization is occasionally separated for logistical, operational, or other reasons. Recently, there was a case of separate hospitalization because of difficulties in subject recruitment. This article suggests a better way of bioequivalence data analysis for the case of separate hospitalization. The key features are (1) considering the hospitalization date as a random effect than a fixed effect and 2) using “PROC MIXED” instead of “PROC GLM” to include incomplete subject data.
Hospitalization* ; Statistics as Topic* ; Therapeutic Equivalency*

4

Cite

Share

Pharmacokinetic characteristics of fluticasone, salmeterol and tiotropium after concurrent inhalation.

Jung SUNWOO ; Su jin RHEE ; SeungHwan LEE ; Sang Won LEE ; Jina JUNG ; Hankil SON ; In Jin JANG

Translational and Clinical Pharmacology.2017;25(2):85-92. doi:10.12793/tcp.2017.25.2.85

Chronic obstructive pulmonary disease (COPD) is a type of progressive, obstructive lung disease characterized by long-term poor airflow. The symptoms of COPD may be relieved and its progression delayed by fluticasone (FTS), salmeterol (SM), and tiotropium (TTP). The aim of this study is to investigate pharmacokinetic (PK) characteristics of inhaled FTS, SM, and TTP after co-administration. An open-label, single-arm, three-period, simple ascending dose study was conducted in 10 healthy male subjects. A single dose of FTS/SM (250/50 µg) and TTP (18 µg) were concomitantly inhaled in period 1, and the dose of each drug was escalated to two- and three-fold in periods 2 and 3, respectively, with a 2-week washout between periods. Activated charcoal was co-administered before and after inhalation to block gastrointestinal absorption. Blood samples for PK analysis were collected up to 24 hours. PK parameters were obtained by non-compartmental analysis. FTS, SM, and TTP rapidly reached maximum plasma concentration after inhalation (0.08–3.00 h, 0.03–0.10 h and 0.03–0.10 h, respectively) and were eliminated with mean half-lives of 9.29–10.44 h, 6.09–12.39 h and 0.25–47.42 h, respectively. PK assessment of the lowest dose of TTP was limited due to relatively low systemic exposure compared to the lower limit of quantification. In conclusion, PK characteristics of FTS, SM, and TTP by pulmonary absorption were evaluated after concurrent inhalation. FTS and SM showed dose-proportional PK profiles between 250–750 µg and 50–150 µg, respectively, while TTP presented dose-proportionality in the early phase exposure between 18-54 µg.
Charcoal ; Fluticasone* ; Gastrointestinal Absorption ; Humans ; Inhalation* ; Lung Diseases, Obstructive ; Male ; Pharmacokinetics ; Plasma ; Pulmonary Disease, Chronic Obstructive ; Respiratory Tract Absorption ; Salmeterol Xinafoate* ; Tiotropium Bromide*

5

Cite

Share

Parameter estimation for sigmoid E(max) models in exposure-response relationship.

Sangmin CHOE ; Donghwan LEE

Translational and Clinical Pharmacology.2017;25(2):74-84. doi:10.12793/tcp.2017.25.2.74

The purpose of this simulation study is to explore the limitation of the population PK/PD analysis using data from a clinical study and to help to construct an appropriate PK/PD design that enable precise and unbiased estimation of both fixed and random PD parameters in PK/PD analysis under different doses and Hill coefficients. Seven escalating doses of virtual drugs with equal potency and efficacy but with five different Hill coefficients were used in simulations of single and multiple dose scenarios with dense sampling design. A total of 70 scenarios with 100 subjects were simulated and estimated 100 times applying 1-compartment PK model and sigmoid E(max) model. The bias and precision of the parameter estimates in each scenario were assessed using relative bias and relative root mean square error. For the single dose scenarios, most PD parameters of sigmoid E(max) model were accurately and precisely estimated when the C(max) was more than 85% of EC₅₀, except for typical value and inter-individual variability of EC₅₀ which were poorly estimated at low Hill coefficients. For the multiple dose studies, the parameter estimation performance was not good. This simulation study demonstrated the effect of the relative range of sampled concentrations to EC₅₀ and sigmoidicity on the parameter estimation performance using dense sampling design.
Bias (Epidemiology) ; Clinical Study ; Colon, Sigmoid*

6

Cite

Share

Metabolomic analysis of healthy human urine following administration of glimepiride using a liquid chromatography-tandem mass spectrometry.

Eun Young DO ; Mi Ri GWON ; Bo Kyung KIM ; Boram OHK ; Hae Won LEE ; Woo Youl KANG ; Sook Jin SEONG ; Hyun Ju KIM ; Young Ran YOON

Translational and Clinical Pharmacology.2017;25(2):67-73. doi:10.12793/tcp.2017.25.2.67

Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3′, 5′-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.
Adenosine ; Diabetes Mellitus, Type 2 ; Histidine ; Humans* ; Insulin ; Least-Squares Analysis ; Male ; Mass Spectrometry* ; Metabolism ; Metabolomics* ; Principal Component Analysis ; Quercetin ; Statistics as Topic ; Tyramine ; Tyrosine ; Urocanic Acid ; Volunteers

7

Cite

Share

Allopurinol-induced severe cutaneous adverse reactions: A report of three cases with the HLA-B*58:01 allele who underwent lymphocyte activation test.

Eun Young KIM ; Jung Eun SEOL ; Jae Hyeog CHOI ; Na Yul KIM ; Jae Gook SHIN

Translational and Clinical Pharmacology.2017;25(2):63-66. doi:10.12793/tcp.2017.25.2.63

Allopurinol-induced severe cutaneous adverse reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome are reportedly associated with the HLA-B*58:01 genotype. Three patients who developed SCARs after allopurinol administration were subjected to HLA-B genotyping and lymphocyte activation test (LAT) to evaluate genetic risk and to detect the causative agent, respectively. All three patients given allopurinol to treat gout were diagnosed with DRESS syndrome. Symptom onset commenced 7-24 days after drug exposure; the patients took allopurinol (100–200 mg/d) for 2-30 days. HLA-B genotyping was performed using a polymerase chain reaction (PCR)-sequence-based typing (SBT) method. All patients had a single HLA-B*58:01 allele: HLA-B*13:02/*58:01 (a 63-year-old male), HLA-B*48:01/*58:01 (a 71-year-old female), and HLA-B*44:03/*58:01 (a 22-year-old male). Only the last patient yielded a positive LAT result, confirming that allopurinol was the causative agent. These findings suggest that patients with HLA-B*58:01 may develop SCARs upon allopurinol administration. Therefore, HLA-B genotyping could be helpful in preventing serious problems attributable to allopurinol treatment, although PCR-SBT HLA-B genotyping is time consuming. A simple genotyping test is required in practice. LAT may help to identify a causative agent.
Aged ; Alleles* ; Allopurinol ; Cicatrix ; Drug Hypersensitivity Syndrome ; Genotype ; Gout ; HLA-B Antigens ; Humans ; Lymphocyte Activation* ; Lymphocytes* ; Methods ; Middle Aged ; Polymerase Chain Reaction ; Stevens-Johnson Syndrome ; Young Adult

8

Cite

Share

Mixed?effects analysis of increased rosuvastatin absorption by coadministered telmisartan.

Wan Su PARK ; Dooyeon JANG ; Seunghoon HAN ; Dong Seok YIM

Translational and Clinical Pharmacology.2016;24(1):55-62. doi:10.12793/tcp.2016.24.1.55

The Cmax and AUC of rosuvastatin increase when it is coadministered with telmisartan. The aim of this study was to explore which of the pharmacokinetic (PK) parameters of rosuvastatin are changed by telmisartan to cause such an interaction. We used data from drug–drug interaction (DDI) studies of 74 healthy volunteers performed in three different institutions. Rosuvastatin population PK models with or without telmisartan were developed using NONMEM (version 7.3). The plasma concentration–time profile of rosuvastatin was best described by a two-compartment, first-order elimination model with simultaneous Erlang and zero-order absorption when given rosuvastatin alone. When telmisartan was coadministered, the zero-order absorption fraction of rosuvastatin had to be omitted from the model because the absorption was dramatically accelerated. Notwithstanding the accelerated absorption, the relative bioavailability (BA) parameter estimate in the model demonstrated that the telmisartan-induced increase in BA was only about 20% and the clearance was not influenced by telmisartan at all in the final PK model. Thus, our model implies that telmisartan may influence the absorption process of rosuvastatin rather than its metabolic elimination. This may be used as a clue for further physiologically based PK (PBPK) approaches to investigate the mechanism of rosuvastatin–telmisartan DDI.
Absorption* ; Area Under Curve ; Biological Availability ; Healthy Volunteers ; Plasma

9

Cite

Share

Screening study for genetic polymorphisms affecting pharmacokinetics of simvastatin.

Sohee IM ; Bo Hyung KIM ; Kidong LEE ; Kyubum KWACK ; Sung Vin YIM

Translational and Clinical Pharmacology.2016;24(1):43-54. doi:10.12793/tcp.2016.24.1.43

Simvastatin reduces plasma cholesterol by inhibiting HMG-CoA reductase (HMGR) and is widely used in the treatment of hypercholesterolemia. To screening the possible genetic factors affecting the pharmacokinetics (PK) of simvastatin, 35 male Korean volunteers were enrolled from two separate bioequivalence studies. Each subject was administered 20 mg simvastatin and reference drug PK parameters were used. We used Illumina Human610Quad v1.0 DNA Analysis BeadChip for whole genome SNPs analysis and whole genome genotyping data was processed by linear regression analysis for PK parameters of drug metabolizing enzymes and transporters. We found 145 significant SNPs (P < 0.01) in C(max), 135 significant SNPs (P < 0.01) in T(max) and 85 significant SNPs (P < 0.01) in AUC(inf) from whole genome analysis. In particular, we found that the ABCC2 gene had a significant effect on C(max) and AUC(inf). These results could provide information of possible candidate genes for personalized simvastatin therapy.
Cholesterol ; DNA ; Genome ; Humans ; Hypercholesterolemia ; Linear Models ; Male ; Mass Screening* ; Oxidoreductases ; Pharmacogenetics ; Pharmacokinetics* ; Plasma ; Polymorphism, Genetic* ; Polymorphism, Single Nucleotide ; Simvastatin* ; Therapeutic Equivalency ; Volunteers

10

Cite

Share

HPLC-UV method for the simultaneous determinations of ascorbic acid and dehydroascorbic acid in human plasma.

Yunjeong KIM ; Min Gul KIM

Translational and Clinical Pharmacology.2016;24(1):37-42. doi:10.12793/tcp.2016.24.1.37

A high performance liquid chromatography (HPLC) paired with UV-vis detection method to determine ascorbic acid and its oxidation product, dehydroascorbic acid, in human plasma was developed. Ascorbic acid in human plasma was extracted and stabilized using 10% metaphosphoric acid, and was analyzed by a Symmetry C18 column with 5 mM Hexadecyltrimethylammonium bromide and 50 mM KH2PO4 solution as the mobile phase (1.0 mL/min flow rate). Isoascorbic acid served as the internal standard and ultraviolet detector wavelength was 254 nm and 265 nm. Dehydroascorbic acid concentration was calculated from the differences in ascorbic acid concentration before and after reduction by dithiothreitol reagent. Quantification for ascorbic acid in human plasma was linear from 1–100 µg/mL. The inter- and intra-day precisions and accuracy were determined and the results were found to be within ±15%. This method was successfully applied to a human pharmacokinetic study of ascorbic acid as well as dehydroascorbic acid after oral administration of 4,000 mg vitamin C tablets to healthy Korean volunteers.
Administration, Oral ; Ascorbic Acid* ; Chromatography, High Pressure Liquid ; Chromatography, Liquid ; Dehydroascorbic Acid* ; Dithiothreitol ; Humans* ; Plasma* ; Tablets ; Volunteers

DISPLAY OPTIONS

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share

Cite

Share