2013 Fiscal Year Final Research Report
Data-mining approach for prediction of the drug safety in humans
| Project/Area Number |
23590185
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Medical pharmacy
|
|---|
| Research Institution | The University of Tokushima |
|---|
Principal Investigator |
YAMAUCHI Aiko 徳島大学, ヘルスバイオサイエンス研究部, 教授 (30122253)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
SATO Youichi 徳島大学, ヘルスバイオサイエンス研究部, 准教授 (10363160)
SAKAMOTO Kumiko 徳島大学, 大学病院, 薬剤師 (80403749)
|
|---|
| Project Period (FY) |
2011 – 2013
|
| Keywords | 医薬品安全性情報 / データマイニング / ヒト毒性予測 |
|---|
| Research Abstract |
The aim of this study was to investigate whether the data-mining approach is useful for predicting the drug safety in humans, or not. The results showed that the drug transfer into breast milk and placental drug transfer in human were significantly predicted by the quantitative structure activity relationship (QSAR) models. The SVM method was revealed to be one of highly effective tools for classifying human toxicities of drugs into positive or negative, in silico.
|
