• Journal of Pharmaceutical Investigation
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• v.35 no.5
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• pp.355-360
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• 2005

The purpose of the present study was to evaluate the bioequivalence of two cetirizine HCl tablets, Zyrtec tablet (UCB Pharm. Co., Ltd. Korea, reference product) and Zyrix tablet (Kukje Pharm. Co., Ltd., Korea, test product), according to the guidelines of Korea Food and Drug Administration (KFDA). After adding an internal standard (diazepam), plasma samples were extracted using 1 mL of dichloromethane. Compounds extracted were analyzed by reverse-phase HPLC with ultra-violet detector. This method for determination cetirizine is proved accurate and reproducible with a limit of quantitation of 10 ng/mL in male plasma. Twenty-four healthy male Korean volunteers received each medicine at the cetirizine HCl dose of 10 mg in a $2{\times}2$ crossover study. There was a one-week wash out period between the doses. Plasma concentrations of cetirizine were monitored for over a period of 24 hr after the administration. AUC (the area under the plasma concentration-time curve) was calculated by the linear trapezoidal rule. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were compiled from the plasma concentration-time data. Analysis of variance was carried out using logarithmically transformed AUC and $C_{max}$. No significant sequence effect was found for all of the bioavailability parameters indicating that the crossover design was properly performed. The 90% confidence intervals for the log transformed data were acceptable range of log 0.8 to log 1.25 $(e.g.,\;log\;0.93-log\;1.08\;for\;AUC_{0-t},\;log\;0.91-log\;1.08\;for\;AUC_{0-{\infty}}\;and\;log\;1.01-log\;1.11\;for\;C_{max})$. The major parameters, AUC and $C_{max}$ met the criteria of KFDA for bioequivalence indicating that Zyrix tablet is bioequivalent to Zyrtec tablet.

• Biomolecules & Therapeutics
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• v.7 no.1
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• pp.59-65
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• 1999

A bioequivalence study of the Dong Wha Cisapril tablets(Dong Wha Pharm. Ind. Co., Ltd.) to the Prepulsid tablets(Janssen Korea Ltd.), formulations of cisapride, was conducted. Twenty four healthy Korean male subjects received each formulation at the dose of 5 mg as cisapride in a 2$\times$2 crossover study. There was a 1-week washout period between the doses. Plasma concentrations of cisapride were monitored by an LC/MS method for over a period of 36 h after each administration. AUC(area under the plasma concentration- time curve from time zero to infinity) was calculated by the linear trapezoidal and extrapolation method. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were compiled from the plasma drug concentration-time data. Analysis of variance (ANOVA) revealed that there are no differences in AUC, $C_{max}$ and $T_{max}$ between the formulations. The apparent differences between the formulations in these parameters were all far less than 20% (i.e., 6.8, -6.6 and 1.8% for AUC, $C_{max}$ and $T_{max}$, respectively). Minimum detectable differences(%) at $\alpha$=0.05 and 1-$\beta$=0.8 were all less than 20% in these parameters between the formulations (i.e., 16.5, 11.4 and 16.4% for AUC, $C_{max}$ and $T_{max}$, respectively). The 90% confidence intervals for these parameters were also within 20% (i.e., -2.9~ 16.4, -13.2~0.1 and -7.8~ 11.4% for AUC, $C_{max}$ and $T_{max}$, respectively). These results satisfy the bioequivalence criteria of the Korea Food and Drug Administration (KFDA) guidelines (No. 98-51). Therefore, these results indicate that the two formulations of cisapride are bioequivalent and, thus, may be prescribed interchangeably.hangeably.y.hangeably.

• YAKHAK HOEJI
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• v.45 no.2
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• pp.220-226
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• 2001

A bioequivalence study of Lovastati $n^{TM}$ tablets (Dong Sung Pharmaceutical Co., Korea) to Mevaco $r^{TM}$ tablets (Choong Wae Pharmaceutical Co., Korea) was conducted according to the guidelines (No. 98-56) of Korea Food and Drug Administration (KFDA). Each tablet contained 20 mg of lovastatin. Eighteen healthy Korean male subjects received each formulation at a lovastatin dose of 80 mg (i.e., four tablets) in a 2 $\times$ 2 crossover study. There was a washout period of a week between the dose of the two formulations. Plasma concentrations of lovastatin acid were monitored by a GC/MS method for over a period of 12hr after each administration. The area under the plasma concentration-time curve from time zero to 12hr (AUC) was calculated by a linear trapezoidal method. The maximum plasma drug concentration ( $C_{max}$) and the time to reach $C_{max}$ ( $T_{max}$) were compiled from the plasma drug concentration-time data. Analysis of variance (ANOVA) of these parameters revealed that there are no differences in AUC and $C_{max}$ between the formulations. The apparent differences between the formulations in these parameters were 4.87 and 8.03% for AUC and $C_{max}$, respectively. Minimum detectable differences (%) at $\alpha$=0.1 and 1-$\beta$=0.8 were 17.84 and 15.36% for AUC and $C_{max}$ respectively. The 90% confidence intervals were -15.30~5.56 and -17.02-0.95% for AUC and $C_{max}$, respective1y. Thus, the criteria of the KFDA guidelines for the bioequivalence was satisfied, indicating Mevaco $r^{TM}$ tablets and Dong Sung Lovastati $n^{TM}$ tablets are bioequivalent.ivalent.ent.alent.ent.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.111-116
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• 2022

In this study, the applicability of machine learning for the development of a simulator for general X-ray examination education is evaluated. To this end, k-nearest neighbor(kNN), support vector machine(SVM) and neural network(NN) classification models are analyzed to present the most suitable model by analyzing the results. Image data was obtained by taking 100 photos each corresponding to Posterior anterior(PA), Posterior anterior oblique(Obl), Lateral(Lat), Fan lateral(Fan lat). 70% of the acquired 400 image data were used as training sets for learning machine learning models and 30% were used as test sets for evaluation. and prediction model was constructed for right-handed PA, Obl, Lat, Fan lat image classification. Based on the data set, after constructing the classification model using the kNN, SVM, and NN models, each model was compared through an error matrix. As a result of the evaluation, the accuracy of kNN was 0.967 area under curve(AUC) was 0.993, and the accuracy of SVM was 0.992 AUC was 1.000. The accuracy of NN was 0.992 and AUC was 0.999, which was slightly lower in kNN, but all three models recorded high accuracy and AUC. In this study, right-handed PA, Obl, Lat, Fan lat images were classified and predicted using the machine learning classification models, kNN, SVM, and NN models. The prediction showed that SVM and NN were the same at 0.992, and AUC was similar at 1.000 and 0.999, indicating that both models showed high predictive power and were applicable to educational simulators.

• Biomolecules & Therapeutics
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• v.10 no.4
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• pp.303-308
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• 2002

A bioequivalence study of Shin II Cefadroxil capsule (Shin II Pharm. Co. Ltd.) to Duricef capsule(Bo Ryung Pharm. Co. Ltd.), each containing 500 mg of cefadroxil, was conducted. Twenty three healthy Korean male subjects administered each formulation at the dose of 1 capsule (500 mg as cefadroxil) in 2 $\times$ 2 cross-over study. There was a I-week washout period between the doses. Plasma concentrations of cefadroxil were monitored for a period of 8 hr after each administration by an LC/UV method. Area under the plasma concentration-time curve up to 8 hr ($AUC_t$) was calculated by a linear trapezoidal method. $C_{max}$ was compiled from the plasma drug concentration-time data. ANOVA test was conducted for logarithmically transformed $AUC_t$ and $C_{max}$ The results showed that there are no significant differences in $AUC_t$ and $C_{max}$ between the two formulations: The differences between d1e formulations in these log transformed parameters were all for less than 20% (i.e., －0.57%, 3.84% for $AUC_t$ and $C_{max}$, respectively). The 90% confidence intervals for the log transformed data were within the acceptance range of log 0.8 to log 1.25 (i.e., log 0.94~log 1.04 and log 0.95~log 1.10 for $AUC_t$ and $C_{max}$, respectively). Based on d1e bioequivalence criteria of KFDA guidelines, the two formulations of cefadroxil were concluded to be bioequivalent.

• Journal of Ginseng Research
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• v.44 no.2
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• pp.229-237
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• 2020

Background: We investigated the tolerability and pharmacokinetic properties of various ginsenosides, including Rb1, Rb2, Rc, Rd, and compound K, after single or multiple administrations of red ginseng extract in human beings. Methods: Red ginseng extract (dried ginseng > 60%) was administered once and repeatedly for 15 days to 15 healthy Korean people. After single and repeated administration of red ginsengextract, blood sample collection, measurement of blood pressure and body temperature, and routine laboratory test were conducted over 48-h test periods. Results: Repeated administration of high-dose red ginseng for 15 days was well tolerated and did not produce significant changes in body temperature or blood pressure. The plasma concentrations of Rb1, Rb2, and Rc were stable and showed similar area under the plasma concentration-time curve (AUC) values after 15 days of repeated administration. Their AUC values after repeated administration of red ginseng extract for 15 days accumulated 4.5- to 6.7-fold compared with single-dose AUC. However, the plasma concentrations of Rd and compound K showed large interindividual variations but correlated well between AUC of Rd and compound K. Compound K did not accumulate after 15 days of repeated administration of red ginseng extract. Conclusion: A good correlation between the AUC values of Rd and compound K might be the result of intestinal biotransformation of Rb1, Rb2, and Rc to Rd and subsequently to compound K, rather than the intestinal permeability of these ginsenosides. A strategy to increase biotransformation or reduce metabolic intersubject variability may increase the plasma concentrations of Rd and compound K.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.29 no.1
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• pp.5-13
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• 2003

The purpose of this study is to determine the value of serum concentration of C-reactive protein(CRP) in comparison with ESR and leukocyte as the tools for diagnosis and follow-up study of infection. For this study, thirty-one patients with head and neck infection and thirty-two patients performed the orthognathic surgery were selected for experimental and control groups each other. we analyzed the blood sample daily to measure CRP, ESR and leukocytosis. The results of this study are as the following : 1. Serum C-Reactive Protein levels in the experimental group were higher than control group and the pattern of CRP changes continued to decline in both groups(P<0.001). 2. ESR changes in both groups were scattered without any special pattern. 3. Correlation between CRP and Leukocyte was higher than others(r=0.664, P<0.01). 4. In the Receiver Operating Characteristic(ROC) Curve of experimental group, rapid increase of CRP curve and Area under the curve(AUC) value, 0.774, indicate the high accuracy of estimation. 5. In experimental group, sensitivity of CRP, ESR, and Leukocytosis on recovery day were 83%, 17% and 71%. Based on the results of this study, we could conclude that determination of CRP is more useful method to diagnosis and follow-up study of infection than other commonly used variables in oral and maxillofacial region.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.597-607
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• 2016

The goal of this study was to analyze landslide susceptibility using two different models and compare the results. For this purpose, a landslide inventory map was produced from a field survey, and the inventory was divided into two groups for training and validation, respectively. Sixteen landslide conditioning factors were considered. The relationships between landslide occurrence and landslide conditioning factors were analyzed using the FR (Frequency Ratio) and EBF (Evidential Belief Function) models. The LSI (Landslide Susceptibility Index) maps that were produced were validated using the ROC (Relative Operating Characteristics) curve and the SCAI (Seed Cell Area Index). The AUC (Area under the ROC Curve) values of the FR and EBF LSI maps were 80.6% and 79.5%, with prediction accuracies of 72.7% and 71.8%, respectively. Additionally, in the low and very low susceptibility zones, the FR LSI map had higher SCAI values compared to the EBF LSI map, as high as 0.47%p. These results indicate that both models were reasonably accurate, however that the FR LSI map had a slightly higher accuracy for landslide susceptibility mapping in the study area.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.301-312
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• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.