| Project/Area Number |
16K19175
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Medical sociology
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| Research Institution | Gifu Pharmaceutical University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | シグナル検出 / アソシエーション分析 / 併発疾患 / 医薬品相互作用 / association rule mining / signal detection / Pharmacovigilance / drug-drug interaction / Association rule mining / signal detectuion / JADER / 薬学 / 社会医学 |
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| Outline of Final Research Achievements |
This study aimed to construct a simple method to search for side effect agents using side effect spontaneous report database. Since the first problem with the conventional evaluation method is “the number of combinations to be investigated is huge”, we focus on the association analysis, which is one of the analysis methods for big data, in consideration of shortening the analysis time. By the Apriori algorithm used in this analysis method, it was possible to simplify the calculation for calculating the signal value.
Additionally, this analysis method showed the same power as the conventional evaluation method for the signal considering the primary disease and the signal of drug-drug interaction.
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| Academic Significance and Societal Importance of the Research Achievements |
本解析法で用いたAprioriアルゴリズムにより、シグナル値の算出のための演算の簡略化を実施し、原疾患を考慮したケースや医薬品相互作用のシグナルの検出が簡便化された。この成果により、未知の有害事象シグナルを効率よく検出できるようになったと考える。
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