2016-11-012024-05-13https://scholars.lib.ntu.edu.tw/handle/123456789/652688摘要：近年來，功能性奈米粒子在標靶治療中已被廣泛地使用。由於其高複雜度，在製造與臨床中常耗費可觀的資源。透過多尺度計算模擬，我們將可預測在不同環境中，如何有效地將奈米粒子與負載藥物運送到目的地。本計畫將融合基本的統計力學與膠體流體力學理論，來探究在特定生化結合作用(如:抗體—抗原)的影響下，具有不同表面修飾與官能基的功能性奈米粒子在細胞周圍的自組裝現象以及其與細胞結合之動力行為。在第一年中，我們將利用具有可調參數的平均場自由能理論，來預測奈米粒子在生理條件下所形成的熱力學穩定態，以期能有效率地與臨床或實驗文獻比較。<br> Abstract: Drug delivery using targeted nanoparticles is a potent application of nanotechnology to treat disease. Owing to the high-dimensional parameter space involved, targeted nanoparticle design and medical use are amenable to multiscale computational modeling to provide predictive values of appropriate characteristics for manufacture and clinical application while reducing the time, expense, and other resources necessary for otherwise large scale experimentation. In the past 3 years, Web of Science keyword “functionalized nanoparticle” search return 2481 publications. However, the published literature for associated theoretical/computational aspects of nanoparticle-based targeted drug delivery remains limited. This suggests that a physiologically sound, theoretically robust, and computationally tractable model is critical for rational design of nanoparticles for drug delivery. In this project, we propose combining fundamental principles of statistical mechanics and colloidal hydrodynamics to tackle the design of surface-functionalized nanoparticles that can self-assemble and bind to the target cells. In Year 1, we will predict the thermodynamically-stable state of the self-assembly of spherical nanoparticles in physiological conditions. Utilizing the mean-field free energy formulation with tunable parameters, the developed theoretical framework can communicate with clinical/experimental literature efficiently and yield the first approximation of the phase diagram.統計力學流體力學多尺度模擬標靶藥物傳遞功能性奈米粒子statistical mechanicshydrodynamicsmultiscale modelingtargeted drug deliveryfunctionalized nanoparticles