2023 Fiscal Year Final Research Report
Development and validation of mathematical model of nanomedicine for cancer treatment by using zebrafish
| Project/Area Number |
20K20532
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| Research Category |
Grant-in-Aid for Challenging Research (Pioneering)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 19:Fluid engineering, thermal engineering, and related fields
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
中嶋 洋行 国立研究開発法人国立循環器病研究センター, 研究所, 室長 (10467657)
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| Project Period (FY) |
2020-07-30 – 2024-03-31
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| Keywords | 血流シミュレーション / ナノメディシン / ライブイメージング / ゼブラフィッシュ |
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| Outline of Final Research Achievements |
We developed a new methodology to reconstruct three-dimensional complex vascular network from a series of two-dimensional confocal microscope images taken from young zebrafish. The reconstructed three-dimensional structure and the movies of red blood cells at the two-dimensional planes are integrated into deep neural network for estimating the three-dimensional velocity field inside the vascular network. We have also established dissipative particle dynamics (DPD) simulation, and validated its capability of predicting complex interaction between red blood cells and plasma by comparing with experimental data. We also coated nano particles by PEG with different lengths, and demonstrated the possibility of controlling the residence time of nano particles in the blood flow, and thereby providing them the opportunity to reach a target tissue. The present experimental and numerical methods will be useful for the optimal design of nano particles used in the future drag delivery systems.
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| Free Research Field |
熱流体工学
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| Academic Significance and Societal Importance of the Research Achievements |
これまで毛細血管内部における赤血球や血漿の相互作用やナノ粒子の挙動については、十分な知識が得られておらず、そのことが狙った患部に薬剤を選択的に届けるドラッグデリバリーシステムの確立の大きな障害となっていた。本研究では、ライブイメージングが可能なゼブラフィッシュを生体モデルとして、その内部にナノ粒子を注入し、その血管内の流動特性を直接観察する技術を構築するとともに、赤血球の動力学を考慮した数理モデルの構築、および計算コードの開発を実施した。本研究で構築したツールは、ドラッグデリバリーシステム構築のためのナノ粒子最適設計に大きく貢献することが期待される。
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