A New Search Method Using Association Rule Mining for Drug-Drug Interaction Based on Spontaneous Report System

By a News Reporter-Staff News Editor at Pharma Investments, Ventures & Law Weekly -- A new study on Obesity, Fitness and Wellness is now available. According to news reporting originating in Gifu, Japan, by NewsRx journalists, research stated, “Adverse events (AEs) can be caused not only by one drug but also by the interaction between two or more drugs. Therefore, clarifying whether an AE is due to a specific suspect drug or drug-drug interaction (DDI) is useful information for proper use of drugs.”

Financial support for this research came from Japan Society for the Promotion of Science.

The news reporters obtained a quote from the research from Gifu Pharmaceutical University, “Whereas previous reports on the search for drug-induced AEs with signal detection using spontaneous reporting systems (SRSs) are numerous, reports on drug interactions are limited. This is because in methods that use ‘a safety signal indicator’ (signal), which is frequently used in pharmacovigilance, a huge number of combinations must be prepared when signal detection is performed, and each risk index must be calculated, which makes interaction search appear unrealistic. In this paper, we propose association rule mining (AR) using large dataset analysis as an alternative to the conventional methods (additive interaction model (AI) and multiplicative interaction model (MI)). The data source used was the Japanese Adverse Drug Event Report database. The combination of drugs for which the risk index is detected by the ‘combination risk ratio (CR)’ as the target was assumed to be true data, and the accuracy of signal detection using the AR methods was evaluated in terms of sensitivity, specificity, Youden’s index, -score. Our experimental results targeting Stevens-Johnson syndrome indicate that AR has a sensitivity of 99.05%, specificity of 92.60%, Youden’s index of 0.917, -score of 0.876, AI has a sensitivity of 95.62%, specificity of 96.92%, Youden’s index of 0.925, and -score of 0.924, and MI has a sensitivity of 65.46%, specificity of 98.78%, Youden’s index of 0.642, and -score of 0.771. This result was about the same level as or higher than the conventional method. If you use similar calculation methods to create combinations from the database, not only for SJS, but for all AEs, the number of combinations would be so enormous that it would be difficult to perform the calculations. However, in the AR method, the ‘Apriori algorithm’ is used to reduce the number of calculations.”

According to the news reporters, the research concluded: “Thus, the proposed method has the same detection power as the conventional methods, with the significant advantage that its calculation process is simple.”

For more information on this research see: A New Search Method Using Association Rule Mining for Drug-Drug Interaction Based on Spontaneous Report System. Frontiers In Pharmacology , 2018;9():197.

Our news correspondents report that additional information may be obtained by contacting Y. Noguchi, Laboratory of Clinical Pharmacy, Gifu Pharmaceutical University, Gifu, Japan. Additional authors for this research include A. Ueno, M. Otsubo, H. Katsuno, I. Sugita, Y. Kanematsu, A. Yoshida, H. Esaki, T. Tachi and H. Teramachi.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.3389/fphar.2018.00197. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2018, NewsRx LLC

CITATION: (2018-04-22), Researchers at Gifu Pharmaceutical University Describe Findings in Obesity, Fitness and Wellness (A New Search Method Using Association Rule Mining for Drug-Drug Interaction Based on Spontaneous Report System), Pharma Investments, Ventures & Law Weekly, 52, ISSN: 0000-0000, BUTTER® ID: 015486182

From the newsletter Pharma Investments, Ventures & Law Weekly.
https://www.newsrx.com/Butter/#!Search:a=15486182


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