| Budget Amount *help |
¥44,460,000 (Direct Cost: ¥34,200,000、Indirect Cost: ¥10,260,000)
Fiscal Year 2021: ¥6,760,000 (Direct Cost: ¥5,200,000、Indirect Cost: ¥1,560,000)
Fiscal Year 2020: ¥10,140,000 (Direct Cost: ¥7,800,000、Indirect Cost: ¥2,340,000)
Fiscal Year 2019: ¥11,180,000 (Direct Cost: ¥8,600,000、Indirect Cost: ¥2,580,000)
Fiscal Year 2018: ¥16,380,000 (Direct Cost: ¥12,600,000、Indirect Cost: ¥3,780,000)
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| Outline of Final Research Achievements |
In this study, we constructed a machine learning model in which cell survival curves under anti-cancer drugs exposures can be calculated from molecular information in cells by utilizing large-scale public database. The quantitative accuracy of this model is, however, limited since we experimentally observed that the cellular sensitivity was varied by experimental environments. Therefore, a future challenge for this study is to construct a model in which environmental difference can be calibrated. Although there remains such a challenge, we confirmed that our current model could provide qualitative factors related to cellular sensitivity. Thus, our constructed model in this study can be used as a base model to reasonably select anti-cancer drugs by using molecular information about cancer cells.
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