Bioavailability Section
Pharmacokinetic comparison using two tablets of an evogliptin/metformin XR 2.5/500 mg fixed dose combination vs. 1 tablet each of evogliptin 5 mg and metformin XR 1,000 mg
Sumin Yoon, Su-jin Rhee, Sang-In Park, Seo Hyun Yoon, Joo-Youn Cho, In-Jin Jang, SeungHwan Lee, Kyung-Sang Yu
Price
42.00 $
Volume 55 (2017) p. 533 - 539
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 55 – No. 6/2017 (533-539)
Pharmacokinetic comparison using two tablets of an evogliptin/metformin XR 2.5/500 mg fixed dose combination vs. 1 tablet each of evogliptin 5 mg and metformin XR 1,000 mg
Sumin Yoon1, Su-jin Rhee1, Sang-In Park1, Seo Hyun Yoon1, Joo-Youn Cho1, In-Jin Jang1, SeungHwan Lee1,2, Kyung-Sang Yu1
1Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, and 2Clinical Trials Center, Seoul National University Biomedical Research Institute, Seoul, Republic of Korea
Objectives: The aim of this study was to compare the pharmacokinetic (PK) characteristics of evogliptin and metformin following the administration of 2 evogliptin/metformin extended-release (XR) 2.5/500 mg FDC tablets with the coadministration of separate evogliptin 5-mg and metformin XR 1,000-mg tablets (separate formulations). Methods: A randomized, two-period, two-sequence crossover study was conducted. Subjects were randomly assigned to receive 2 FDC tablets or the individual tablets, followed by a 14-day washout period and the administration of the alternate treatment. Blood samples were collected predose and up to 72 hours postdose for each period. PK parameters including Cmax and AUClast were calculated. The geometric mean ratios (GMRs) and the 90% confidence intervals (CIs) between FDC and the separate formulations were calculated for the Cmax and AUClast of evogliptin and metformin. Results: 33 subjects completed the study. The GMR (90% CI) values of Cmax and AUClast for evogliptin were 1.011 (0.959 – 1.066) and 1.010 (0.977 – 1.043), respectively. The GMR (90% CI) values of Cmax and AUClast for metformin were 0.892 (0.827 – 0.963) and 0.893 (0.841 – 0.947), respectively. There was no significant difference between the FDC and separate formulations regarding the occurrence of adverse events. All drug-related adverse events were considered to be mild and resolved without any treatment. Conclusions: Two FDC tablets of evogliptin/metformin XR 2.5/500 mg showed a similar PK profile to the separate formulations of evogliptin 5 mg and metformin XR 1,000 mg. All of the 90% CIs of GMR satisfied the regulatory bioequivalence criteria of 0.800 – 1.250.
Correspondence to:
Kyung-Sang Yu, MD, PhD
Department of Clinical Pharmacology and Therapeutics
Seoul National University College of Medicine and Hospital
101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea
Email: [email protected]
Bioavailability Section
Bioequivalence assessment of tulobuterol transdermal delivery system in healthy subjects
Sang-In Park and Bo-Hyung Kim
Price
42.00 $
Volume 56 (2018) p. 381 - 386
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 56 – No. 8/2018 (381-386)
Bioequivalence assessment of tulobuterol transdermal delivery system in healthy subjects
Sang-In Park1#2, Bo-Hyung Kim1#2#3#4
1Department of Clinical Pharmacology and Therapeutics, Kyung Hee University Hospital, Seoul, 2East-West Medical Research Institute, Kyung Hee University, Seoul, 3Department of Clinical Pharmacology and Therapeutics, College of Medicine, and 4Department of Biomedical Science and Technology, Kyung Hee University, Seoul, Republic of Korea
Objective: The purpose of this study was to evaluate the bioequivalence in the pharmacokinetics of two 2-mg tulobuterol transdermal delivery systems (TDSs) in healthy subjects. Materials and methods: The pharmacokinetic (PK) analysis was performed using data from a randomized, open-label, single-dose, two-way, two-period, crossover study. Eligible subjects received either the Bretol® patch (test drug) or Hokunalin® patch (reference drug) in sequence according to their allocated group. Serial blood samples for PK analyses were collected for up to 48 hours after tulobuterol TDS application. The PK parameters, including the maximum concentration (C<sub>max</sub>) and area under the curve from time zero to the last quantifiable concentration time (AUC<sub>last</sub>), were estimated by using noncompartmental analysis. The geometric mean ratios (GMRs) of the C<sub>max</sub> and AUC<sub>last</sub> and their 90% confidence intervals (CIs) were estimated. Results: A total of 27 subjects completed the study as planned. The concentration-time profiles of tulobuterol were similar in both formulations. The GMRs (90% CIs) of C<sub>max</sub> and AUC<sub>last</sub> were 0.9443 (0.8790 – 1.0144) and 0.9600 (0.8660 – 1.0642), respectively. Conclusion: The PK profiles of both tulobuterol TDSs were comparable. In addition, the 90% CIs of the GMR were within the bioequivalence criteria of 0.800 – 1.250. Therefore, the Bretol® patch can be used as an alternative to the Hokunalin® patch for the treatment of patients with asthma and chronic obstructive pulmonary disease.
Correspondence to:
Bo-Hyung Kim, MD, PhD
Department of Clinical Pharmacology and Therapeutics
Kyung Hee University College of Medicine and Hospital
Seoul 02447,
Republic of Korea
Email: [email protected]
Bioavailability Section
Pharmacokinetic comparison of gemigliptin 50 mg and metformin 500 mg as a fixed-dose combination and loose combination
Sang Won Lee, Sang-In Park, SeungHwan Lee, Jae-Yong Chung, and Kyung-Sang Yu
Price
42.00 $
Volume 57 (2019) p. 117 - 124
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 57 – No. 2/2019 (117-124)
Pharmacokinetic comparison of gemigliptin 50 mg and metformin 500 mg as a fixed-dose combination and loose combination
Sang Won Lee1, Sang-In Park1, SeungHwan Lee1, Jae-Yong Chung2, and Kyung-Sang Yu1
1Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 2Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Bundang Hospital, Seongnam, Korea
Background: Metformin and dipeptidyl peptidase-4 (DPP-IV) inhibitors are commonly combined to treat patients with diabetes mellitus (DM). A new fixed-dose combination (FDC) drug containing gemigliptin, a DPP-IV inhibitor, and sustained-release metformin has been developed. This study aimed to compare the PKs and tolerability of FDC versus loose combination of gemigliptin 50 mg and metformin 500 mg. Materials and methods: A randomized, open-label, two-treatment, two-period, two-sequence, crossover study was conducted in 28 healthy subjects, who received a single oral dose of an FDC tablet of gemigliptin (50 mg) and sustained-release metformin (500 mg) or were coadministered gemigliptin (50 mg) and extended-release metformin (500 mg) with a 1-week washout. Serial blood samples were collected up to 48 hours after study drug administration, and the plasma concentrations of gemigliptin, LC15-0636 (active metabolite of gemigliptin), and metformin were determined using a validated LC-MS/MS method. Pharmacokinetic parameters were derived using a noncompartmental method. Safety and tolerability were evaluated based on vital signs, adverse events, clinical laboratory tests, and electrocardiography. Results: The concentration-time profiles of gemigliptin and metformin were similar when they were administered as FDC or were coadministered. The geometric mean ratio (GMR) and its 90% CIs of C<sub>max</sub> for gemigliptin, LC15-0636, and metformin were 0.93 (0.85 – 1.02), 1.00 (0.94 – 1.06), and 1.03 (0.98 – 1.09), respectively. The corresponding values of AUC<sub>last</sub> were 0.97 (0.93 – 1.01), 1.00 (0.97 – 1.04), and 1.00 (0.95 – 1.05), respectively. There were no clinically meaningful differences in safety and tolerability. Conclusion: When comparing the AUC<sub>last</sub> and C<sub>max</sub> of gemigliptin, LC15-0636, and metformin, the 90% CIs were all within the range of 0.8 – 1.25, which is the commonly accepted range for evaluating bioequivalence.Correspondence to:
Kyung-Sang Yu, MD, PhD
Department of Clinical Pharmacology and Therapeutics
Seoul National University College of Medicine and Hospital
101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
Email: [email protected]
Original
Occurrence of metabolic diseases associated with antipsychotic use among Korean patients with schizophrenia
Sunghee Kuk, Seoyoung Kim, Euitae Kim, Bo-Hyung Kim, Woojoo Lee, and Sang-In Park
Price
42.00 $
Volume 59 (2021) p. 298 - 307
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 59 – No. 4/2021 (298-307)
Occurrence of metabolic diseases associated with antipsychotic use among Korean patients with schizophrenia
Sunghee Kuk1, Seoyoung Kim2, Euitae Kim2, Bo-Hyung Kim3#4#5#6, Woojoo Lee7, and Sang-In Park8
1Department of Statistics, Inha University, Incheon, 2Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 3Department of Clinical Pharmacology and Therapeutics, Seoul, 4East-West Medical Research Institute, 5Department of Clinical Pharmacology and Therapeutics, College of Medicine, 6Department of Biomedical Science and Technology, Kyung Hee University, 7Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, and 8Department of Pharmacology, College of Medicine, Kangwon National University, Chuncheon, Republic of Korea
Objective: Metabolic side effects of antipsychotics significantly affect adherence to medication. We aimed to identify factors associated with the occurrence of metabolic diseases among Korean patients with schizophrenia (SCZ) from the national health insurance system database. We evaluated the frequency of antidiabetic and antihyperlipidemic use after diagnosis of SCZ according to typical or atypical antipsychotic use.
Materials and methods: Among the 43,800 patients diagnosed with SCZ between 2008 and 2012, 29,591 patients who had no metabolic diseases before the diagnosis were included in the analysis to investigate the occurrence of metabolic diseases associated with antipsychotic use. The associations between the development of metabolic diseases and patient characteristics were evaluated using logistic regression analysis.
Results: Use of both typical and atypical antipsychotics (multivariate-adjusted odds ratio (OR), 1.2513; 95% confidence interval (CI), 1.0953 – 1.4294) was associated with higher incidence of metabolic diseases than without their use. Among the atypical antipsychotics, use of clozapine (multivariate-adjusted OR, 1.1959; 95% CI, 1.0086 – 1.4179) and quetiapine (multivariate-adjusted OR, 1.1284; 95% CI, 1.0446 – 1.2189) showed higher incidence of metabolic diseases compared to that without their use. Among the patients using ≥ 1 type of antidiabetic or antihyperlipidemic agents within 6 years after diagnosis of SCZ, the proportion of patients using only atypical antipsychotics was greater than those using only typical antipsychotics.
Conclusion: The use of both typical and atypical antipsychotics, and clozapine and quetiapine treatment, may be associated with the occurrence of metabolic diseases in patients with SCZ. Additional prospective studies with accurate dosage information are needed to validate our findings.Correspondence to:
Sang-In Park, MD, PhD
1 Gangwondaehakgil, Chuncheon-si,
Gangwon-do 24341, Republic of Korea
Email: [email protected]
Original
Comparison of vancomycin area under the curve calculated based on Bayesian approach versus equation-based approach
Eojin Lee, Uijeong Yu, Ji In Park, and Sang-In Park
Price
42.00 $
Volume 62 (2024) p. 204 - 212
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 62 – No. 5/2024 (204-212)
Comparison of vancomycin area under the curve calculated based on Bayesian approach versus equation-based approach
Eojin Lee1, Uijeong Yu2, Ji In Park3, and Sang-In Park2#4
1Department of Applied Animal Science, College of Animal Life Sciences, 2Department of Pharmacology, College of Medicine, Kangwon National University, 3Department of Internal Medicine, Kangwon National University College of Medicine and Kangwon National University Hospital, and 4Biomedical Research Institute, Kangwon National University Hospital, Chuncheon, Republic of Korea
Objective: Area under the curve (AUC)-based vancomycin dose adjustment is recommended to treat methicillin-resistant Staphylococcus aureus (MRSA) infections. AUC estimation methods include Bayesian software programs and simple analytical equations. This study compared the AUC obtained using the Bayesian approach with that obtained using an equation-based approach.
Materials and methods: Patients receiving intravenous vancomycin for MRSA infection were included. Peak and trough levels were measured for each patient on days 3, 7, and 10 post vancomycin dosing (day 1). AUC was calculated using software based on the Bayesian method (MwPharm Online) and an equation-based calculator, Stanford Health Care (SHC) calculator.
Results: The AUC estimated using MwPharm Online was similar to that estimated using the SHC calculator. The geometric mean ratio (GMR) and their 90% confidence intervals (90% CI) were 1.08 (1.05 – 1.11), 1.03 (0.99 – 1.07), and 0.99 (0.94 – 1.05) at days 3, 7, and 10, respectively. Furthermore, according to the software used, there were no significant differences in the proportions of patients in the categories “within” and “below or above” the AUC target range. Additionally, trough levels predicted by both software programs were lower than the observed ones. Still, there was no significant difference between the predicted and observed peak levels for both software programs on day 10.
Conclusion: AUC calculated using the Bayesian software allows for calculation with samples at a non-steady state, can integrate covariates, and is interconvertible with that estimated using an equation-based calculator, which is simpler and relies on fewer assumptions. Therefore, either method can be used, considering each method’s strengths and limitations.Correspondence to:
Sang-In Park, MD, PhD
Department of Pharmacology, College of Medicine
Kangwon National University
1 Gangwondaehak-gil, Chuncheon-si,
Gangwon-do 24341, Republic of Korea
Email: [email protected]
Original
Identification of factors associated with vancomycin-induced acute kidney injury: A retrospective analysis using the Common Data Model
Sang-In Park, Jung-Kyeom Kim, Uijeong Yu, and Ji In Park
Price
42.00 $
Volume 62 (2024) p. 560 - 568
Abstract
International Journal of Clinical Pharmacology and Therapeutics, Vol. 62 – No. 12/2024 (560-568)
Identification of factors associated with vancomycin-induced acute kidney injury: A retrospective analysis using the Common Data Model
Sang-In Park1#2, Jung-Kyeom Kim3, Uijeong Yu1, and Ji In Park4
1Department of Pharmacology, College of Medicine, Kangwon National University, 2Biomedical Research Institute, Kangwon National University Hospital, 3Department of Medical Bigdata Convergence, Kangwon National University, and 4Department of Internal Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine, Gangwon-do, Chuncheon, Republic of Korea
Objective: Previous findings on predictors of vancomycin-induced acute kidney injury (AKI) are inconsistent. We aimed to identify the predictors of vancomycin-induced AKI using the Observational Medical Outcome Partnership Common Data Model.
Materials and methods: We analyzed data from patients treated with vancomycin between January 1, 2012, and May 31, 2022, who were positive for Staphylococcus aureus and had undergone oxacillin susceptibility tests. After excluding patients without data for vancomycin or baseline serum creatinine levels, 116 patients were included in the final dataset. Data up to the third measured vancomycin concentration were collected for each patient. Logistic regression models were used to estimate the odds ratio and 95% confidence interval for each variable associated with vancomycin-induced AKI.
Results: High baseline serum creatinine levels, intensive care unit admission, and concurrent renal disorders were significantly associated with vancomycin-induced AKI. Although high trough levels or area under the curve values were not significantly associated with vancomycin-induced AKI, both were significantly higher in patients with AKI than in those without AKI at the second vancomycin concentration measurement. The proportion with trough levels > 20 mg/L was higher in patients with AKI than in those without AKI at the third measurement.
Conclusion: Our findings revealed that underlying renal disease and intensive care unit admission are more significantly associated with vancomycin-induced AKI than vancomycin pharmacokinetic parameters or dosage, likely due to vancomycin concentration-based dosage adjustment in clinical settings. Our findings may help develop strategies for reducing the incidence of vancomycin-induced AKI; however, further prospective studies are essential.Correspondence to:
Sang-In Park, MD, PhD
Department of Pharmacology, College of Medicine
Kangwon National University
1 Gangwondaehak-gil, Chuncheon-si,
Gangwon-do 24341, Republic of Korea
Email: [email protected]
