2019 Fiscal Year Final Research Report
Clarification of novel antiepileptic effects using clinical big data
| Project/Area Number |
17K17922
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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 pharmacy
Psychiatric science
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| Research Institution | The University of Tokushima |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Keywords | てんかん / ビッグデータ / キンドリング |
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| Outline of Final Research Achievements |
A study was conducted to clarify the effect of a candidate compound by database analysis in basic experiment. It was found that the combination of existing antiepileptic drugs and candidate compound potentiated the antiepileptic effects of the kindling model. Chronic administration of the candidate compound during the formation of the Kindling model resulted in delayed acquisition of epilepsy, suggesting that this compound may have an antiepileptogenic effect. From the above, it is suggested that a compound with antiepileptic effects was found by the medical big data. It may be that the compound had an inhibitory effect on epileptogenic activity in intractable epilepsy.
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| Free Research Field |
中枢薬理
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| Academic Significance and Societal Importance of the Research Achievements |
難治性てんかんは、てんかん患者の約20％存在しており、複数の抗てんかん薬を服用してもコントロールが困難であり、新規抗てんかん薬の開発が望まれている。しかし、「難治性てんかん」の病態メカニズムおよび確実な治療法は未だ明らかにされておらず、基礎研究および臨床研究を取り入れた科学的根拠に基づく薬物治療法を確立することが喫緊の課題である。本研究により医療ビッグデータを活用し、抗てんかん作用をもつ化合物を見出されたことは非常に社会的意義がある。また、本化合物がてんかん原生に対し効果を示し、難治性てんかんの治療に貢献しうる可能性は学術的意義があると考えられる。
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