Creation of high-risk adverse event signals using data mining based on computational science

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K20731
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 90140:Medical technology assessment-related
• Research Institution: Gifu Pharmaceutical University
• Principal Investigator: Noguchi Yoshihiro 岐阜薬科大学, 薬学部, 講師 (80724608)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 計算科学 / データマイニング / 有害事象

Outline of Final Research Achievements

A comprehensive analysis using two different databases in Japan, the JADER and the JMDC Claims Database, showed that DPP-4 inhibitors, which are widely used in Japan, have a non-inferior risk of cardiovascular events compared to metformin, which is used as the first-line drug in the United States and Europe.
The signal detected in the spontaneous reporting database is the creation of a clinical hypothesis. I believe that this study has created an environment for validation using databases with higher levels of evidence in order to make the signals more evidence-based.

Free Research Field

薬剤疫学

Academic Significance and Societal Importance of the Research Achievements

本研究では、臨床的仮説生成である「自発報告データベースにより検出されたシグナル」をよりエビデンスの高いものにするため検証する環境を構築できた。この研究成果により、よりエビデンスの高いシグナル創出が可能となった。