• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

• 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.

• Korean Journal of Biological Psychiatry
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• v.7 no.1
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• pp.21-33
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• 2000

As the clinical practice of using more than one drug at a time increase, the clinician is faced with ever-increasing number of potential drug interactions. Although many interactions have little clinical significances, some may interfere with treatment or even be life-threatening. This review provides a better understanding of drug-drug interactions often encountered in pharmacotherapy of depression. Drug interactions can be grouped into two principal subdivisions : pharmacokinetic and pharmacodynamic. These subgroups serve to focus attention on possible sites of interaction as a drug moves from the site of administration and absorption to its site of action. Pharmacokinetic processes are those that include transport to and from the receptor site and consist of absorption, distribution on body tissue, plasma protein binding, metabolism, and excretion. Pharmacodynamic interactions occur at biologically active sites. In this review, emphasis is placed on antidepressant medications, how they are metabolized by the P450 system, and how they alter the metabolism of other drugs. When prescribing antidepressant medications, the clinician must consider the drug-drug interactions that are potentially problematic.

• 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.

• Toxicological Research
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• v.33 no.1
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• pp.25-30
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• 2017

Saccharin, the first artificial sweetener, was discovered in 1879 that do not have any calories and is approximately 200~700 times sweeter than sugar. Saccharin was the most common domestically produced sweetener in Korea in 2010, and it has been used as an alternative to sugar in many products. The interaction between artificial sweeteners and drugs may affect the drug metabolism in patients with diabetes, cancer, and liver damage, this interaction has not been clarified thus far. Here, we examined the effects of the potential saccharin-drug interaction on the activities of 5 cytochrome P450 (CYPs) in male ICR mice; further, we examined the effects of saccharin (4,000 mg/kg) on the pharmacokinetics of bupropion after pretreatment of mice with saccharin for 7 days and after concomitant administration of bupropion and saccharin. Our results showed saccharin did not have a significant effect on the 5 CYPs in the S9 fractions obtained from the liver of mice. In addition, we observed no differences in the pharmacokinetic parameters of bupropion between the control group and the groups pretreated with saccharin and that receiving concomitant administration of saccharin. Thus, our results showed that saccharin is safe and the risk of saccharin-drug interaction is very low.

• Journal of Pharmaceutical Investigation
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• v.19 no.4
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• pp.179-183
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• 1989

Drug release experiments were performed based on pH-sensitive swelling behaviors of polymethacrylic acid. 5-Fluorouracil as a nonionic model drug revealed release patterns depending solely on pH-dependent swelling kinetics of polymethacrylic acid. In contrast, release of propranolol hydrochloride as a cationic model drug was significantly affected by ionic drug-polymer interaction as well as the swelling kinetics. Accordingly, a zero-order release pattern was obtained at pH 7, which was distinguished from the general matrix type drug release pattern.

• Archives of Pharmacal Research
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• v.4 no.2
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• pp.99-107
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• 1981

To investigate the protein binding characteristics of ibuprofenlysine, the effects of drub conentration, pH, ionic strength and protein concentration on the binding of drug to protein concentration on the binding of drug to protein were studied by fluorescence probe method. The conformational change of protein was investigated by circular dichroism (CD) measurement. As the concentration of drug increases, the association constant decreases. These may be due to complex formation of the probe and drug, or the interaction of the protein-probe complex and drug. The association constant for ibuprofenlysine increased with increasing protein concentration. These finding suggest a sharing of one ibuprofenlysine molecule by more than one protein molecule in the binding. The binding between ibuprofenlysine and protein was dependent on pH and ionic strength. It seems that both hydrophobic binding and some electrostatic forces are involved in the binding of ibuprofenlysing to protein.

• Toxicological Research
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• v.23 no.1
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• pp.1-9
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• 2007

Transporters are membrane proteins that mediate the transfer of substrate across the cellular membrane. In this overview, the characteristics and the toxicological relevance were discussed for various types of transporters. For drug transporters, the overview focused on ATP-binding cassette transporters and solute carrier family 21A/22A member transporters. Except for OCTN transporters and OATP transporters, drug transporters tend to have broad substrate specificity, suggesting drug-drug interaction at the level of transport processes (e.g., interaction between methotrexate and non-steroidal anti-inflammatory agents) is likely. For metal transporters, transporters for zinc, copper and multiple metals were discussed in this overview. These metal transporters have comparatively narrow substrate specificity, except for multiple metal transporters, suggesting that inter-substrate interaction at the level of transport is less likely. In contrast, the expressions of the transporters are often regulated by their substrates, suggesting cellular adaptation mechanism exists for these transporters. The drug-drug interactions in drug transporters and the cellular adaptation mechanisms for metal transporters are likely to lead to alterations in pharmacokinetics and cellular metal homeostasis, which may be linked to the development of toxicity. Therefore, the transporter-mediated alterations may have toxicological relevance.

• Korean Journal of Biological Psychiatry
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• v.6 no.1
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• pp.49-66
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• 1999

Polypharmacotherapy, both psychotropic and nonpsychotropic, is widespread in various situations including psychiatric hospitals and general hospitals. As the clinical practice of using more than one drug at a time increase, the clinician is faced with ever-increasing number of potential drug interactions. Although many interactions have little clinical significances, some may interfere with treatment or even be life-threatening. The objective of this review is evaluation for drug-drug interactions often encountered in psychiatric consultation. Drug interactions can be grouped into two principal subdivisions : pharmacokinetic and pharmacodynamic. These subgroups serve to focus attention on possible sites of interaction as a drug moves from the site of administration and absorption to its site of action. Pharmacokinetic processes are those that include transport to and from the receptor site and consist of absorption, distribution on body tissue, plasma protein binding, metabolism, and excretion. Pharmacodynamic interactions occur at biologically active sites. In psychiatric consultation, these two subdivisions of drug interactions between psychotropic drugs and other drugs are likely to happen. We gathered informations of the drugs used in physically ill patients who are consulted to psychiatric department in Korea University Hospital. And we reviewed the related literatures about the drug-drug interactions between psychotropic drugs and other drugs.

• Korean Journal of Clinical Pharmacy
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• v.11 no.2
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• pp.89-96
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• 2001

Ziprasidone is equally effective as haloperidol in treating schizophrenia with fewer side effects and drug interactions. Ziprasidone is an atypical antipsychotic agent and works by blocking serotonin and dopamine receptors in the central nervous system, specifically 5-HT2A and D2 receptors. Low anticholinergic side-effects and low EPS would recommend the drug for use in the elderly. Ziprasidone inhibits reuptake of norepinephrine and serotonin at neurojunction sites in vitro, indicating a potential efficacy for depression and negative symptoms which often follow after exacerbation of schizophrenia. Patients with recent acute myocardial infarction and uncompensated heart failure are contraindicated to the drug due to a possibility of QT prolongation. Although ziprasidone is metabolized by cytochrome P450 3A4, there is no significant drug interaction with the drugs that induce or inhibit the isoenzyme. Ziprasidone is safe with coadministration of lithium and there has been no significant drug interaction reported with oral birth control pills.