• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.183-192
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• 2009

ADESS(Adverse drug event surveillance system) is the system which distinguishes adverse drug events using adverse drug signals. This system shows superior effectiveness in adverse drug surveillance than current methods such as volunteer reporting or char review. In this study, we built clinical data mart(CDM) for the development of ADESS. This CDM could obtain data reliability by applying data quality management and the most suitable clustering number(n=4) was gained through the reproducibility assessment in unsupervised learning techniques of knowledge discovery. As the result of analysis, by applying the clustering number(N=4) K-means, Kohonen, and two-step clustering models were produced and we confirmed that the K-means algorithm makes the most closest clustering to the result of adverse drug events.

• The Monthly Diabetes
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• s.261
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• pp.46-47
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• 2011

서울대병원 약물유해반응 관리센터와 지역약물감시센터가 공동으로 일반인들을 대상으로 '약물유해반응 경험 및 인식도 조사'를 한 결과 우리나라 성인 10명 중 2명은 의약품 부작용을 직접 경험하고도 적극적으로 조치하지 않은 것으로 나타났다. 또 약물유해반응으로 인해 조취를 취한 경우는 20.8%에 그쳐 의약품 부작용에 관한 홍보가 절실한 것으로 드러난다.

• The Magazine of Kiice
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• v.12 no.1
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• pp.42-45
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• 2011

• The Journal of Bigdata
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• v.8 no.2
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• pp.125-131
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• 2023

Globally, drug side effects rank among the top causes of death. To effectively respond to these adverse drug reactions, a shift towards an active real-time monitoring system, along with the standardization and quality improvement of data, is necessary. Integrating individual institutional data and utilizing large-scale data to enhance the accuracy of drug side effect predictions is critical. However, data sharing between institutions poses privacy concerns and involves varying data standards. To address this issue, our research adopts a federated learning approach, where data is not shared directly in compliance with privacy regulations, but rather the results of the model's learning are shared. We employ the Common Data Model (CDM) to standardize different data formats, ensuring accuracy and consistency of data. Additionally, we propose a drug monitoring system that enhances security and scalability management through a cloud-based federated learning environment. This system allows for effective monitoring and prediction of drug side effects while protecting the privacy of data shared between hospitals. The goal is to reduce mortality due to drug side effects and cut medical costs, exploring various technical approaches and methodologies to achieve this.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.106-114
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• 2009

In this study, we are analysing adverse drug events and proposing a technical structure of "adverse drug event surveillance system" using business intelligence technology, hoping that we can use the system commonly and actively. It is the recent trend to adopt both of electronic review and manual review process to surveil adverse drug events and this study construct CDW applying ETL in BI Technology. As the result of analysis, the data pool included 701 doctors who prescribed and 3059 patients(1528 male, 1531 female), of total 318,222 cases, 2,086cases(0.6%) were suspected as having adverse drug events. And the single type of T.bilirubin> 3mg/dL(ADE type-LabR0005) was the most common(548 among 2085 cases) within the framework of signals.

• Journal of Korean Society of Health-System Pharmacists
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• v.35 no.4
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• pp.475-483
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• 2018

• 대한임상약리학회:학술대회논문집
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• 2006.11a
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• pp.53-56
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• 2006

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.465-472
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• 2021

In this paper, we present an approach for detection of adverse drug reactions from drug reviews to compensate limitations of the spontaneous adverse drug reactions reporting system. Considering negative reviews usually contain adverse drug reactions, sentiment analysis on drug reviews was performed and extracted negative reviews. After then, MedDRA dictionary and named entity recognition were applied to the negative reviews to detect adverse drug reactions. For the experiment, drug reviews of Celecoxib, Naproxen, and Ibuprofen from 5 drug review sites, and analyzed. Our results showed that detection of adverse drug reactions is able to compensate to limitation of under-reporting in the spontaneous adverse drugs reactions reporting system.

• Korean Journal of Biological Psychiatry
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• v.2 no.1
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• pp.20-27
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• 1995

Therapeutic montitoring of drugs is a well established clinical 1001. However, the state of art is somewhat less advanced for psychotrpoic agents than it is for other classes of drugs, for several reasons. Most psychotropics have large volumes of distribution and achieve relatively low plasma concentrations following therapeutic doses. Many have one or more active metabolites. As a consequene, the analytical methodologies are often complex and not always reliable; well-controlled clinical studies are difficult to perform; and therapeutic ranges have been difficult to establish. Despite these limitations, prudent and selective monitoring of serum drug concentrations, particularly of the tricyclic antidepressants can be helpful in clinical management. This paper presents an overview of clinical and mothodological issues surrounding the utility of blood level measurement.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1995.04a
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• pp.62-62
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• 1995

한국산 천연자원중 한방이나 민간요법에서 항종양제로 빈번히 사용되어온 생약들 중에서 103종을 선정하여 이들 성분들을 추출하고 시험관내에서 항종양성이 우수하고 정상세포에 손상을 적게 주는 생약 6종을 선별하여 암세포주에 대한 독성능 (in vitro)과 항종양성 면역감시기구(in vivo)및 LD$_{50}$등을 측정하여 항종양제로의 신약개발을 목적으로 수행하였다. 방법: 선별된 6종의 생약유효성분을 METHANOL로 추출하여 조추출물을 얻었으며 이물질들을 순차적으로 각각의 유기용매로 추출, column chromatography법으로 분획하였으며 분획분에 대한 암세포독성능은 MTT colorimetric 검정법을 이용하여 IC$_{50}$값을 구하였다. 면역감시기구 측정방범으로는 Balb/c mouae암,수 각 10수씩에 P388암세포주를 접종한군과 접종하지 않은 실험군에 생약추출분획물 8.6mg/0.2ml씩 20일간 매일 경구 투여시키고 대조군에는 생리식염수 0.2ml씩을 매일 경구 투여시켜 NK cell의 활성 MIF Recombinant IL-2로 유도시킨 NK cell활성능, chemotaxis등을 측정하였다. 생체내 항종양능 시험은 tumor panel system에 따라 mouse leukemia cell을 사용하여 측정하였다. 각분획성분의 투여용량은 실험동물에서 독성실험결과로 LD$_{50}$량을 구해 항암효과 평가시에 Maximum dose로 하였고 최고용량을 기준으로 일정한 공비를 적응하여 3단계의 투여량을 설정하였다. (중략)