• Proceedings of the PSK Conference
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• 2003.04a
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• pp.252.2-252.2
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• 2003

It was difficult that we analysed the polymeric drugs for the physico-chemical properties. Sodium hyaluronate is a linear polysaccharide composed of repeating disaccharides of sodium glucuronate and N-acetyl glucosamine found throughout the tissues of the body with high concentrations in the vitreous humor. synovial fluid and umbilical cord. It has a role in regulating the interaction between adjoining tissues. (omitted)

• Journal of Microbiology and Biotechnology
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• v.33 no.2
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• pp.180-187
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• 2023

The skin is a dynamic ecosystem on which diverse microbes reside. The interkingdom interaction between microbial species in the skin microbiota is thought to influence the health and disease of the skin although the roles of the intra- and interkingdom interactions remain to be elucidated. In this context, the interactions between Malassezia and Staphylococcus, the most dominant microorganisms in the skin microbiota, have gained attention. This study investigated how the interaction between Malassezia and Staphylococcus affected the antifungal susceptibility of the fungus to the azole antifungal drug ketoconazole. The susceptibility was significantly decreased when Malassezia was co-cultured with Staphylococcus. We found that acidification of the environment by organic acids produced by Staphylococcus influenced the decrease of the ketoconazole susceptibility of M. restricta in the co-culturing condition. Furthermore, our data demonstrated that the significant increased ergosterol content and cell membrane and wall thickness of the M. restricta cells grown in the acidic environment may be the main cause of the altered azole susceptibility of the fungus. Overall, our study suggests that the interaction between Malassezia and Staphylococcus influences the antifungal susceptibility of the fungus and that pH has a critical role in the polymicrobial interaction in the skin environment.

• Journal of Pharmaceutical Investigation
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• v.26 no.2
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• pp.113-117
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• 1996

This study was attempted to investigate the pharmacokinetic interaction between sodium valproate (4, 8, 16 mg/kg, i.v.) and phenytoin (4 mg/kg, i.v.) in rabbits. The plasma concentration and area under the curve (AUC) of phenytoin were increased significantly (p<0.05, p<0.01) when coadministered with sodium valproate (4, 8, 16 mg/kg) in rabbits. The volume or distribution and total body clearance of phenytoin were decreased significantly (p<0.05, p<0.01) when coadministered with sodium valproate (8, 16 mg/kg) in rabbit. From the results of this experiment, it is desirable that dosage regimen of phenytoin should be adjusted and therapeutic drug monitoring should be performed for reduction of side or toxic effect when phenytoin will be coadministered with sodium valproate in clinical use.

• Biomolecules & Therapeutics
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• v.17 no.3
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• pp.299-304
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• 2009

Rosiglitazone maleate (RGM) is widely used for improving insulin resistance. RGM is a moderate inhibitor of cytochrome P450 2C8 (CYP2C8) and is also mainly metabolized by CYP2C8. The aim of this study was to determine whether the effect of RGM on CYP2C8 is altered by co-treatment with other drugs, and whether amlodipine camsylate (AC) changes the pharmacokinetics (PK) of RGM. Of the 11 drugs that are likely to be co-administered with RGM in diabetic patients, seven drugs lowered the $IC_{50}$ value of RGM on CYP2C8 by more than 80%. In vitro CYP2C8 inhibitory assays of RGM in combination with drugs of interest showed that the $IC_{50}$ of RGM was decreased by 98.9% by AC. In a pharmacokinetic study, Sprague-Dawley (SD) rats were orally administered 1 mg/kg of RGM following by single or 10-consecutive daily administrations of 1.5 mg/kg/day of AC. No significant changes in the pharmacokinetic parameters of RGM were observed after a single administration of AC, but the AUC and $C_{max}$ values of RGM were significantly reduced by 36% and 31%, respectively, by multiple administrations of AC. In conclusion, RGM was found to be affected by AC by in vitro CYP2C8 inhibition testing, and multiple dosing of AC appreciably changed the pharmacokinetics of RGM. These findings suggest that a drug interaction exists between AC and RGM.

• Herbal Formula Science
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• v.32 no.3
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• pp.365-375
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• 2024

Objectives : Herbal formula consist of multiple herbs, which can potentially interact with conventional drugs. If these interactions are not properly understood, they may reduce treatment efficacy or cause unexpected side effects. Thus, this study collected and analyzed papers on herbal formula and conventional drug interactions from PubMed to analyze various research trends. Methods : To analyze research trends on herbal formula and drug interactions, we first created search queries using a dictionary of herbal formula terms and collected related papers from PubMed using the Entrez API. The PubTator API was applied to identify compound names in the abstracts, recognizing compounds registered in the DrugBank as conventional drugs. Sentences describing interactions between herbal formulas and drugs were extracted using pattern matching, and relevant papers were selected. Trends were then analyzed by year, country, major formulas, major drugs, and interaction networks. Results : Yearly analysis showed a gradual increase in paper counts with a significant rise after 2010. Country analysis revealed that China published the most papers (53), followed by Japan (19) and South Korea (8). formula analysis identified 'sosiho-tang' and 'siryung-tang' as the most frequently mentioned (7 times each). Drug analysis showed '5-fluorouracil', 'acetaminophen', 'entecavir', and 'streptozotocin' were the most frequently mentioned (4 times each). Network analysis revealed 'sosiho-tang and tolbutamide' and 'siryung-tang and prednisolone' as the most frequently, mentioned interactions (3 times each). Disease analysis indicated 'urogenital diseases' were the most discussed (32 mentions), Followed by 'pathological conditions, signs, and symptoms' and 'digestive system diseases' (25 mentions each). Conclusions : Analyzing research trends on herbal formula and conventional drug interactions provides basic data for subsequent research, aiming to reduce side effects and enhance treatment efficacy in clinical settings.

• Archives of Pharmacal Research
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• v.7 no.2
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• pp.87-93
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• 1984

The effects of ionic strength and pH on the binding of cefazolin to bovine serum albumin (BSA) were studied by UV difference spectrophotometry. As ionic strength at constant pH and temperature increases, the apparent bining constant decreased but the number of binding sites remained almost constant at 2. The constancy of the number of binding sites with increasing the ionic strength suggests that purely electrostatic forces between BSA and drug do not have great importance in the drug binding, even though there is a decrease in the apparent binding constant. Thus, the effect of ionic strength on the interaction between drug and BSA may be explained by the changes in ionic atmosphere of the aggregated BSA molecules and competitive inhibition by phosphate ions. In addition, the higher apparent binding constant at high ionic strength is explained by conformational changes of BSA from its aggregate forms into subunits. The pH effects on the afinity of interactions indicated that the binding affinity of cefazoline is higher in the neutral region than in the alkaline region. An d at high pH value, the number of binding sites decreased from 2 to 1 because of the conformational change of BSA in the alkaline region.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.6
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• pp.545-553
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• 2021

Fixed-dose combinations development requires pharmacokinetic drugdrug interaction (DDI) studies between active ingredients. For some drugs, pharmacokinetic properties such as long half-life or delayed distribution, make it difficult to conduct such clinical trials and to estimate the exact magnitude of DDI. In this study, the conventional (non-compartmental analysis and bioequivalence [BE]) and model-based analyses were compared for their performance to evaluate DDI using amlodipine as an example. Raw data without DDI or simulated data using pharmacokinetic models were compared to the data obtained after concomitant administration. Regardless of the methodology, all the results fell within the classical BE limit. It was shown that the model-based approach may be valid as the conventional approach and reduce the possibility of DDI overestimation. Several advantages (i.e., quantitative changes in parameters and precision of confidence interval) of the model-based approach were demonstrated, and possible application methods were proposed. Therefore, it is expected that the model-based analysis is appropriately utilized according to the situation and purpose.

• Korean Journal of Clinical Pharmacy
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• v.21 no.3
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• pp.249-255
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• 2011

Objective: To examine the drug use (prescribing) pattern of serious drug-drug interactions (DDIs, contraindicated drug interactions) using real world data. Prescription patterns were examined in terms of dispensing types. Method: Retrospective drug utilization review (DUR) study was performed. One hundred and six datasets of serious DDIs (DDI pairs) were determined among DDI datasets that Ministry of Health & Welfare announced for the DUR system from 2004 to 2005. Electronically transacted ambulatory patients' prescription database to Health Insurance Assessment and Review Services (HIRA) from July, 2005 to June, 2006 was collected with personal information deidentified and analyzed in terms of types of dispensing as a contributing factor. Results: After prescription data analysis per each patient, total number of DDI cases using 95 DDI pairs was 5,511, which accounted for 2.6 cases per patients. DDI cases between two drugs from each of community pharmacy dispensing- type prescription were considerable (63% vs. 24% in those from each of in-institutional dispensing-type prescription and vs. 13% in those from a community pharmacy dispensing-type prescription and an in-institutional dispensingtype prescription). Conclusions: DDI cases from different prescribers were found to be significant. Thus, the concurrent DUR process between prescriptions from different physicians and institutions should be implemented for the safe drug use.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.115-123
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• 2016

In this study, we collect various side effect pairs which are appeared frequently at many drugs, and select side effect pairs that have higher severity. For every selected side effect pair, we extract common genetic networks which are shared by side effects' genes and drugs' target genes based on PPI(Protein-Protein Interaction) network. For this work, firstly, we gather drug related data, side effect data and PPI data. Secondly, for extracting common genetic network, we find shortest paths between drug target genes and side effect genes based on PPI network, and integrate these shortest paths. Thirdly, we develop a classification model which uses this common genetic network as a classifier. We calculate similarity score between the common genetic network and genetic network of a drug for classifying the drug. Lastly, we validate our classification model by means of AUC(Area Under the Curve) value.

• Korean Journal of Community Nutrition
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• v.3 no.1
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• pp.76-93
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• 1998

Three hundred sixty-two(male 131, female 231) elderly aged over 65 in Chungb- uk area were interviewed to determine the disease states and drug usage patterns. The prebalence of disease was 78% and women reported more chronic diseases(83%) than men(71%). Elderly who live with spouse and have an occupation have a lower rate of disease. Average number of diseases of the elderly was $1.8\pm{1.1}$, and women$(2.1\pm{1.3)}$ have significantly higher average number of diseases than that of men$(1.4\pm{0.7)}$. Also the elderly in urban areas$(2.1\pm{1.4)}$ have significantly higher number of diseases than that of the elderly in rural areas$(1.6\pm{0.9)}$. Arthritis, hypertension, cardiovascular and gastric diseases were the most frequently listed chronic diseases in order for both men and women. Anemia and fracture of bone were relatively higher in women than in men. Particularly, the arthritis of the urban elderly have a rate of 1.5 times higher than that of the rural elderly. Fifty-two percent of the elderly were currently using drugs ; among drug users 71.2% used prescription drugs and 20.5% used nonprescription drugs. The average number taken per person was 2.1$\pm$1.4 and there was no sex or age difference. However, the elderly in rural areas $(2.7\pm{1.7)}$ consumed a significantly higher number of drugs than those in urban areas$(1.7\pm{0.7)}$. The average number of prescripti- on drugs taken was 2.0$\pm$1.4 while the average of nonprescription drugs taken was $(1.3\pm{0.6)}$. Analgesics and antihypertensive drugs were most commonly used. Vitamin and analgesics were the most frequently used self-prescribed drugs. It was noted that potential adverse drug interaction by concominant drug consumption for arthritis and antihypensive drug, abuse of digestants and antiacid without treatment of the underlying disease, and misuse of quick-acting bowel medications were problematic for the elderly. In addition drugs used for the elderly have some adverse effect on the digestive system. The types and composition of drugs used by the elderly were identified and presented. Medication compliance was poor and 13.5% reported adverse reactions such as edema, heartburn, nausea, and difficulty with eating. Seventeen percent of the elderly obtained drugs arranged by those other than medical staff. Also, even among those elderly who obtained drugs prescribed by a doctor, 69.1% of subjects had not receive instruction about potential adverse reactions. These results suggest that nutritional problems related to drug usage might exist and so dietitians, either individually or as members of health teams, need to have a better understanding of drug-nutrient interaction and closer supervision, and drug information/education service should therefore be provided to prevent or minimize adverse drug reaction in elderly users of medication.