• CELLMED
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• v.4 no.3
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• pp.17.1-17.8
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• 2014

Herbal remedies are commonly used by patients worldwide. Because these herbal preparations share the same metabolic and transport proteins with prescribed medicines, the potential for a drug-herb interaction is substantial and is an issue of significant concern. This review paper summarizes drug-herb interactions involving inhibition or induction of cytochrome P450 enzymes, drug transporters as well as modulation of drug pharmacodynamics. An increasing number of in vitro and animal studies, case reports and clinical trials evaluating such interactions have been reported, and implications of these studies are discussed in this review. The most commonly implicated drugs in the interaction include anticoagulants, antiplatelets, immunosuppressants, anti-neoplastics, protease inhibitors, and some antidepressants. Pharmacokinetic and/or pharmacodynamic interactions of five commonly used herbal remedies (danshen, garlic, Ginkgo biloba, ginseng, and St John's wort) with these drugs are presented, with focus of discussion being the potentials for interaction, their mechanisms and clinical implications. There is a necessity for adequate pharmacovigilance to be carried out in minimizing unanticipated but often preventable drug-herb interactions.

• Korean Journal of Clinical Pharmacy
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• v.30 no.1
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• pp.31-35
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• 2020

Objective: The 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors (statins) are frequently prescribed medications worldwide for the treatment of hypercholesterolemia. Statins are considered to be well tolerated; however, they have a potential for myotoxicity. Concomitant drugs that inhibit cytochrome P450 3A4 can increase the concentration of statins and thus the risk of developing myotoxicity. The purpose of this study was to evaluate risk factors associated with potential drug-drug interactions in patients receiving statins. Methods: The subjects of this study were patients aged more than 18 years who received at least one prescription of statins in a general hospital located in Chuncheon-si, Korea, between January 1, 2018, and March 31, 2018. Data regarding statin use and baseline characteristics was collected from the computerized hospital database. Logistic regression analysis was used to identify risk factors associated with potential drug-drug interactions. Results: A total of 1061 patients were finally included in the study. The incidence of potential drug-drug interactions was 45% in all subjects. According to the results of the multivariate logistic regression analysis, myocardial infarction as the indication of statin, arrhythmia or heart failure as a comorbidity, and aspartate aminotransferase levels higher than 40 IU/L were significant risk factors for potential drug-drug interactions in study subjects. Diltiazem was the most commonly co-prescribed drug that caused potential drug-drug interactions with statins. Conclusion: There was a considerable rate of potential drug-drug interactions in patients receiving statins. Health care professionals should attempt to reduce potential drug-drug interactions during statin administration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.276-278
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• 2022

All drugs have a specific action in the body, and in many cases, drugs are combinated due to complications or new symptoms during existing drug treatment. In this case, unexpected interactions may occur within the body. Therefore, predicting drug-drug interactions is a very important task for safe drug use. In this study, we propose a deep learning-based predictive model that learns using drug information documents to predict drug interactions that may occur when using multiple drugs. The drug information document was created by combining several properties such as the drug's mechanism of action, toxicity, and target using DrugBank data. And drug information document is pair with another drug documents and used as an input to a deep learning-based predictive model, and the model outputs the interaction between the two drugs. This study can be used to predict future interactions between new drug pairs by analyzing the differences in experimental results according to changes in various conditions.

• CELLMED
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• v.2 no.2
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• pp.18.1-18.16
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• 2012

An oncology-specific database called OncoRx (http://bit.ly/cancerRx) was previously set up in cyberspace to aid clinicians in identifying interactions of anticancer drugs (ACDs) and chemotherapy regimens with traditional Chinese medicines (TCMs) and complementary and alternative medicines (CAMs). Since then, users have requested the drug-CAM interactions (DCIs) of 5 specific CAMs (cranberry, melatonin, co-enzyme Q10, huachansu, reishi mushroom) to be updated in the database. Pharmacokinetic properties (metabolism, enzyme induction/inhibition, elimination), TCM properties and DCIs of each CAM were collated with 117 ACDs using 9 hardcopy compendia and online databases as resources. Additionally, individual ACDs and CAMs were used as keywords for PubMed searches in combination with the terms 'anticancer drugs', 'drug interactions', 'herb-drug/drug-herb interactions', 'pharmacokinetic interactions' and 'pharmacodynamic interactions'. DCI parameters consisted of interaction effects, evidence summaries, proposed management plans and alternative non-interacting CAMs, together with relevant citations and update dates of the DCIs. OncoRx is also used as a case to introduce the "Four Pharmaco-cybernetic Maxims" of quality, quantity, relationship and manner to developers of digital healthcare tools. Its role in Hayne's "5S" hierarchy of research evidence is also presented. OncoRx is meant to complement existing DCI resources for clinicians and alternative medicine practitioners as an additional drug information resource that provides evidence-based DCI information for ACD-CAM interactions.

• Korean Journal of Biological Psychiatry
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• v.7 no.1
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• pp.3-13
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• 2000

There is nothing that is harmless ; the dose alone decides that something is no poison(Paracelsus, 1493-1541). So, in a point of view to maximize the therapeutic efficacy of drug therapy in a way that minimize the drug toxicity, the knowledges of the drug-ineractions as well as the pharmacokinetic and pharmacodynamic principles of every therapeutic drug used in the medical clinic cannot be emphasized too much. Many drug interactions can be predicted if the pharmacokinetic properties, pharmacodynamic mechanisms of action of the interacting drugs are known, and most adverse interactions can be avoided. In this paper, the clinical importance, classification, and general principles of clinical drug-interactions are presentated with a few explanatory examples.

• YAKHAK HOEJI
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• v.47 no.6
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• pp.390-397
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• 2003

It is common that geriatric patients are on several medications at the same time. With this situation on hand, this study has collected prescriptions of individual geriatric patient and investigated possible drug interactions. In order to minimize the drug interactions and protect those patients from adverse reactions of medication, the gradual implementation and management of the medication history of each individual patient, the establishment of medication counseling system on medicines particularly in need of obligatory advice, the use of an inspection system on drug interactions at the time of prescription, and the implementation of a patient monitoring system on the drugs with narrow margin of safety at hospitals.

• 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.

• Mass Spectrometry Letters
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• v.8 no.4
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• pp.98-104
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• 2017

Ginseng (Panax ginseng Meyer) is a well-known health functional food used as a traditional herbal drug in Asian countries owing to its diverse pharmacological effects. Herb-drug interactions may cause unexpected side effects of co-administered drugs by the alteration of pharmacokinetics through effects on cytochrome P450 activity. In this study, we investigated the herb-drug interactions between Korean red ginseng extract (KRG) and five CYP-specific probes in mice. The pharmacokinetics of KRG extract induced-drug interactions were studied by cassette dosing of five CYP substrates for CYP1A, 2B, 2C, 2D, and 3A and the LC-MS/MS analysis of the blood concentration of metabolites of each of the five probes. The linearity, precision, and accuracy of the quantification method of the five metabolites were successfully confirmed. The plasma concentrations of five metabolites after co-administration of different doses of the KRG extract (0, 0.5, 1, and 2 g/kg) were quantified by LC-MS/MS and dose-dependent pharmacokinetic parameters were determined. The pharmacokinetic parameters of the five metabolites were not significantly altered by the dose of the KRG extract. In conclusion, the single co-administration of KRG extract up to 2 g/kg in vivo did not cause any significant herb-drug interactions linked to the modulation of CYP activity.

• Korean Journal of Clinical Pharmacy
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• v.23 no.1
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• pp.49-56
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• 2013

Objective: The purpose of this study was to evaluate the patterns of Over-the-Counter (OTC) drugs and their interactions with prescription drugs in adults visiting a community pharmacy. Method: The subjects were 151 adults aged over 20 years visiting a community pharmacy in Asan-si from December 16th 2011 to February 1st 2012. We used a survey questionnaire. The survey inquired about the prevalence and the details of any OTC drug use and the characteristics of the study subjects. The drug interaction classification system from Lexicomp's Lexi-interact data fields was used to identify OTC drugs likely to have clinically significant interactions with prescription drugs. Results: The patterns of OTC drug use were related to thirties (from 30 to 40 years old), female gender, higher education, non-smoking, sometimes use of alcohol, and self-perceived normal health status. The most commonly used OTC drug category was antipyretic-analgesics (n=104, 53.3%), and the most commonly used ingredient was acetaminophen (n=67, 64.4%). The biggest motivation for taking OTC drugs was suggestion by pharmacists, reported by 55.6%. After reviewing each patient's prescription drugs and OTC drugs, 14 patients (36.8%) of 38 patients using prescription drugs were taking drug combinations with potential for clinically significant interactions. The concomitant use of OTC drugs with prescription drugs may lead to increased potentially harmful interactions. Conclusion: It is suggested that health-care professionals should be more aware of the potential and possible interactions and take into better account their patients' OTC drug use.

• Korean Journal of Clinical Pharmacy
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• v.25 no.3
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• pp.138-144
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• 2015

Objective: It is to evaluate the drug interaction monitoring program as a pilot project to develop a pharmaceutical care model in a medical intensive care unit and to analyze the influencing factors of drug interactions. Method: Electronic medical records were retrospectively investigated for 116 patients who had been hospitalized in a medical intensive care unit from October to December in 2014. The prevalence of adverse reaction with risk rating higher than 'D' was investigated by Lexi-$Comp^{(R)}$ Online database. The factors related with potential drug interaction and with treatment outcomes were analyzed. Results: The number of patients with a potential interaction of drug combination was 92 (79.3%). Average ages, the length of stay in the intensive care unit and the numbers of prescription drugs showed significant differences between drug interaction group and non-drug interaction group. Opioids (14.4%), antibiotics (7.2%), and diuretics (7.2%) were most responsible drug classes for drug interactions and the individual medications included furosemide (6.4%), tramadol (4.9%), and remifentanil (4.5%). There were 950 cases with a risk rating of 'C' (84.6%), 142 cases with a risk rating of 'D' (12.6%), and 31 cases with a risk rating of 'X' (avoid combination) (2.8%). The factors affecting drug interactions were the number of drugs prescribed (p < 0.0001) and the length of stay at intensive care unit (p < 0.01). The patients in intensive care unit showed a high incidence of adverse reactions related to potential drug interaction. Therefore, drug interaction monitoring program as a one of pharmaceutical care services was successfully piloted and it showed to prevent adverse reaction and to improve therapeutic outcomes. Conclusion: Active participation of a pharmacist in the drug management at the intensive care unit should be considered.