| Project/Area Number |
24390126
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Medical sociology
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| Research Institution | Gifu University |
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Principal Investigator |
KINOSADA Yasutomi 岐阜大学, 医学(系)研究科(研究院), 教授 (50161526)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAMURA Mitsuhiro 岐阜薬科大学, 薬学部, 教授 (30433204)
ITOH Yoshinori 岐阜大学, 大学院医学系研究科, 教授 (50159927)
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| Research Collaborator |
NIWA Takashi
TAKAI Mizuki
TOHORI Kyouhei
NISHIMURA Naoto
FUKUDA Hirotsugu
MAEDA Takahide
MATSUDA Yu
SUMINO Akikazu
KOJINA Soshi
GOMI Yousuke
ARUUISU Naziru
ABE Junko
UMETSU Ryogo
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥14,950,000 (Direct Cost: ¥11,500,000、Indirect Cost: ¥3,450,000)
Fiscal Year 2014: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2013: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2012: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
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| Keywords | 医薬品 / 有害事象 / データベース / ビッグデータ / データマイニング / 医薬品適正使用 / 医療専門職 / 人材育成 / FAERS / 医薬品有害事象 / コミュニティ分析 / ネットワーク分析 / SSRI / 抗うつ薬 / 自殺企図 / F-ARES / 有害事象原因候補医薬品 / 知識データベース / 医療専門職人材育成 |
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| Outline of Final Research Achievements |
We have built the original assisting system for appropriate use of drugs by utilizing the large quantities of open adverse event reports (AERs) from FDA in USA. More than 3.5 million AE reports of the latest 15 years are restored into our system, while the data structure of the original AE reports from FDA are modified to fit for our user’s needs such as quick report extracting and summarizing functions. Our system can facilitate gathering combinations of AE reports and summarizing the properties of a set of extracted AE reports according to age, gender, major preferred terms (PTs) and so on, which are related to the target drugs (single drug and/or combination of some drugs) entered by users of our system.
In our system, it is very easy for users to get some excellent outcomes, such as network graphs showing drug-drug interactions or drug-PT interactions, even when users are students, young researchers or advanced clinical professionals in our analysis environments.
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