• Journal of Pharmaceutical Investigation
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• v.34 no.3
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• pp.209-214
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• 2004

A bioequivalence study of $Roxithrin^{TM}$ tablet (Kukje Pharma. Ind. Co., Ltd.) to $Rulid^{TM}$ tablet (Han Dok Pharma. Ind. Co., Ltd.) was conducted according to the guidelines of Korea Food and Drug Administration (KFDA). Twenty four healthy male Korean volunteers received each medicine at the roxithromycin dose of 300 mg in a $2{\times}2$ crossover study. There was a one-week wash-out period between the doses. Plasma concentrations of roxithromycin were monitored by a high-performance liquid chromatography for over a period of 36 hours after drug administration. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 36 hr) was calculated by the linear trapezoidal rule method. $C_{max}$ (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 $AUC_t$ and $C_{max}$. No significant sequence effect was found for all of the bioavailability parameters indicating that the cross-over design was properly performed. The 90% confidence intervals of the $AUC_t$ ratio and the $C_{max}$ ratio for $Roxithrin^{TM}/Rulid^{TM}$ were 1.00 - 1.13 and 0.98 - 1.10, respectively. These values were within the acceptable bioequivalence intervals of 0.80 - 1.25. Thus, our study demonstrated the bioequivalence of $Roxithrin^{TM}$ and $Rulid^{TM}$ with respect to the rate and extent of absorption.

• Journal of Pharmaceutical Investigation
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• v.38 no.6
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• pp.421-427
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• 2008

The purpose of the present study was to evaluate the bioequivalence of two etodolac capsules, Kuhnillodin capsule (Kuhnil. Co., Ltd., Seoul, Korea) as reference drug and Etodin capsule (Myungmun Pharm. Co., Ltd., Seoul, Korea) as test drug, according to the guidelines of Korea Food and Drug Administration (KFDA). Twenty-three healthy male Korean volunteers received one capsule at the dose of 200 mg etodolac in a $2{\times}2$ crossover study. There was a one-week washout period between the doses. Plasma concentrations of etodolac were monitored by a high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) for over a period of 24 hr after the administration. $AUC_{0-24\;hr}$ was calculated by the linear trapezoidal rule method. $C_{max}$ and $T_{max}$ were compiled from the plasma concentration-time data. Analysis of variance (ANOVA) was carried out using logarithmically transformed $AUC_{0-24\;hr}$ and $C_{max}$. The 90% confidence intervals of the $AUC_{0-24\;hr}$ ratio and the $C_{max}$ ratio for Etodin/Kuhnillodin were $\log\;0.97{\sim}\log\;1.08$ and $\log\;0.89{\sim}\log\;1.19$, respectively. These values were within the acceptable bioequivalence intervals of $\log\;0.80{\sim}\log\;1.25$. Thus, our study demonstrated that Etodin was bioeqiovalent to Kuhnillodin preparation when the rate and extent of absorption between two preparations were compared.

• Journal of Pharmaceutical Investigation
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• v.29 no.3
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• pp.241-245
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• 1999

Bioequivalence study of two cefpodoxime preparations, the test drug ($Banan^{\circledR}$: Hanil Pharmaceutical Co., Ltd.) and the reference drug ($Podox^{\circledR}$: Chong Kun Dang Pharmaceutical Co., Ltd.), was conducted according to the guidelines of Korea Food and Drug Administration (KFDA). Sixteen healthy male volunteers, $23.8{\pm}2.13$ years old and $63.34{\pm}4.84kg$ of body weight in average, were divided randomly into two groups and administered the drug orally at the dose of 200 mg as cefpodoxime proxetil in a $2{\times}2$ crossover study. Plasma concentrations of cefpodoxime were analysed by HPLC method for 12 hr after administration. The $AUC_{0-12hr}$ was calculated by the linear trapezoidal rule method. The $C_{max}$, and $T_{max}$ were compiled directly from the plasma drug concentration-time data. Student's t-test indicated no significant differences between the formulations in these parameters. Analysis of variance (ANOVA) revealed that there were no differences in AUC, $C_{max}$, and $T_{max}$ between the formulations. The apparent differences between the formulations were far less than 20% (e.g., 4.31, 1.99 and 4.30% for AUC, $C_{max}$, and $T_{max}$, respectively). Minimum detectable differences (%) between the formulations at ${\alpha}=\;0.05$ and $1-{\beta}=\;0.8$ were less than 20% (e.g., 13.89, 13.88, and 16.97% for AUC, $C_{max}$, and $T_{max}$, respectively). The 90% confidence intervals for these parameters were also within ${\times}20%$ (e.g., $-5,58{\sim}14.20$, $-7.89{\sim}11.88$, and $-7.78{\sim}16.38%$ for AUC, $C_{max}$, and $T_{max}$, respectively). These results satisfied the bioequivalence criteria of KFDA guidelines, indicating that the two formulations of cefpodoxime were bioequivalent.

• Journal of Pharmaceutical Investigation
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• v.34 no.4
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• pp.319-325
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• 2004

A bioequivalence of $Etodol^{TM}$ tablets (Yuhan corporation) and $Kuhnillodine^{TM}$ tablets (Kuhnil Pharm. Co., Ltd.) was evaluated according to the guideline of Korea Food and Drug Administration (KFDA). Single 200 mg dose of etodolac of each medicine was administered orally to 24 healthy male volunteers. This study was performed in a $2{\times}2$ crossover design. Concentrations of etodolac in human plasma were monitored by a high-performance liquid chromatography. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 24 hr) was calculated by the linear trapezoidal rule method. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were compiled from the plasma concentration-time data. Analysis of variance was performed using logarithmically transformed $AUC_t$ and $C_{max}$. No significant sequence effect was found for all of the bioavailability parameters. The 90% confidence intervals of the $AUC_t$ ratio and the $C_{max}$ ratio for $Etodol^{TM}/Kuhnillodine^{TM}$ were 1.01-1.10 and 0.87-1.06, respectively. This study demonstrated a bioequivalence of $Etodol^{TM}$ and $Kuhnillodine^{TM}$ with respect to the rate and extent of absorption.

• Journal of Pharmaceutical Investigation
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• v.34 no.6
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• pp.505-511
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• 2004

A bioequivalence study of $Bestidine^{TM}$ tablets (Choong Wae Pharma. Corp., Korea) to Dong-A $Gaster^{TM}$ (Dong-A Pharmaceutical Co., Ltd., Korea) tablets was conducted according to the guidelines of Korea Food and Drug Administration (KFDA). Twenty four healthy male Korean volunteers received each medicine at the famotidine dose of 40 mg in a $2{\times}2$ crossover study. There was a one-week wash out period between the doses. Plasma concentrations of famotidine were monitored by a high-performance liquid chromatography for over a period of 12 hours after the administration. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 12 hr) was calculated by the linear trapezoidal rule method. $C_{max}$ (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 $AUC_t$ 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 of the $AUC_t$ ratio and the Cmax ratio for $Bestidine^{TM}/Gaster^{TM}$ were log 0.90-log 1.06 and log 0.98-log 1.20, respectively. These values were within the acceptable bioequivalence intervals of 0.80-1.25. Thus, our study demonstrated the bioequivalence of $Bestidine^{TM}$ and $Gaster^{TM}$ with respect to the rate and extent of absorption.

• Journal of Pharmaceutical Investigation
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• v.38 no.2
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• pp.135-142
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• 2008

The present study describes the evaluation of the bioequivalence of two atorvastatin tablets, Lipitor $Tablet^{(R)}$ (Pfizer, reference drug) and Atorva $Tablet^{(R)}$ (Yuhan, test drug), according to the guidelines of Korea Food and Drug Administration (KFDA). Forty-nine healthy male Korean volunteers received each medicine at the atorvastatin dose of 40 mg in a $2{\times}2$ crossover study with a two weeks washout interval. After drug administration, serial blood samples were collected at a specific time interval from 0-48 hours. The plasma atorvastatin concentrations were monitored by an high performance liquid chromatography -tandem mass spectrometer (LC-MS/MS) employing electrospray ionization technique and operating in multiple reaction monitoring (MRM) and positive ion mode. The total chromatographic run time was 4.5 min and calibration curves were linear over the concentration range of 0.1-100 ng/mL for atorvastatin. The method was validated for selectivity, sensitivity, linearity, accuracy and precision. $AUC_t$ (the area under the plasma concentration-time curve from time zero to 48hr) was calculated by the linear log trapezoidal rule method. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were complied trom the plasma concentration-time data. Analysis of variance was carried out using logarithmically transformed $AUC_t$ 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 of the $AUC_t$ ratio and the $C_{max}$ ratio for Atorva $Tablet^{(R)}$ / Lipitor $Tablet^{(R)}$ were ${\log}\;0.9413{\sim}{\log}\;1.0179$ and ${\log}\;0.831{\sim}{\log}\;1.0569$, respectively. These values were within the acceptable bioequivalence intervals of ${\log}\;0.8{\sim}{\log}\;1.25$. Based on these statistical considerations, it was concluded that the test drug, Atorva $Tablet^{(R)}$ was bioequivalent to the reference drug, Lipitor $Tablet^{(R)}$.

• Archives of Pharmacal Research
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• v.29 no.4
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• pp.328-332
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• 2006

The bioequivalence and pharmacokinetics of alendronate sodium tablets were examined by determining the plasma concentration of alendronate. Two groups, consisting of 24 healthy volunteers, each received a 70 mg reference alendronate sodium tablet and a test tablet in a $2{\times}2$ crossover study. There was a 6-day washout period between doses. The plasma alendronate concentration was monitored for 7 h after the dose, using HPLC-Fluorescence Detector (FD). The area under the plasma concentration-time curve from time 0 to the last sampling time at 7 h $(AUC_{0-7h})$ was calculated using the linear-log trapezoidal rule. The maximum plasma drug concentration $(C_{max})$ and the time to reach $C_{max}(T_{max})$ were derived from the plasma concentration-time data. Analysis of variance was performed using logarithmically transformed $AUC_{0-7h}\;and\;C_{max}$, and untransformed $T_{max}$. For the test medication versus the reference medication, the $AUC_{0-7h}\;were\;87.63{\pm}29.27\;vs.\;102.44{\pm}69.96ng\;h\;mL^{-1}$ and the $C_{max}$ values were $34.29{\pm}13.77\;vs.\;38.47{\pm}24.39ng\;mL^{-1}$ respectively. The $90\%$ confidence intervals of the mean differences of the logarithmic transformed $AUC_{0-7h}$ and $C_{max}$ values were log 0.8234-log 1.1597 and log 0.8222-log 1.1409, respectively, satisfying the bioequivalence criteria guidelines of both the US Food and Drug Administration and the Korea Food and Drug Administration. The other pharmacokinetic parameters for the test drug versus reference drug, respectively, were: $t_{1/2},\;1.87{\pm}0.62\;vs.\;1.77{\pm}0.54\;h;\;V/F,\;2061.30{\pm}986.49\;vs.\;2576.45{\pm}1826.05\;L;\;CL/F,\;835.32{\pm}357.35\;vs.\;889.48{\pm}485.87\;L\;h^{-1}; K_{el},\;0.42{\pm}0.14\;vs.\;0.40{\pm}0.18\;h^{-1};\;Ka,\;4.46{\pm}3.63\;vs.\;3.80{\pm}3.64\;h^{-1};\;and\;T_{lag},\;0.19{\pm}0.09\;vs.\;0.18{\pm}0.06\;h$. These results indicated that two alendronate formulations(70-mg alendronate sodium) were biologically equivalent and can be prescribed interchangeably.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].