CRII: OAC: A Hybrid Finite Element and Molecular Dynamics Simulation Approach for Modeling Nanoparticle Transport in Human Vasculature

CRII：OAC：一种混合有限元和分子动力学模拟方法，用于模拟人体脉管系统中纳米颗粒的传输

• 批准号: 2326802
• 负责人: Ying Li
• 金额: $ 17.5万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-15 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2326802&HistoricalAwards=false
• 关键词: CRII; OAC; Hybrid; Finite; Element

Through nanomedicine significant methods are emerging to deliver drug molecules directly to diseased areas for cancer treatment. Targeted drug delivery is one of the most promising approaches which relies on nanoparticles (NPs) that carry and release drugs. The therapeutic efficacy of NP-based drug carriers is determined by the proper concentration of drug molecules at the lesion site. NPs need to be delivered directly to the diseased tissues while minimizing their uptake by other tissues, thereby reducing the potential harm to healthy tissue. Therefore, the design of these NPs and hence the efficacy of the targeted drug delivery could be significantly improved by understanding how the drugs carried by NPs are transported and dispersed in human body. This project proposes a set of computational tools to model and investigate the transport and dispersion of NPs in human vasculature. This, in turn, can provide better imaging sensitivity, therapeutic efficacy and lower toxicity of NP-based drug carriers. The multidisciplinary nature of the project also brings together concepts from biology, engineering and computer science to educate the next generation of computational biologists, scientists and engineers. This research, thus, aligns with the NSF mission to promote the progress of science and to advance the national health, prosperity and welfare. The technical objective of this project is to create a hybrid finite element and molecular dynamics computational approach for modeling NP transport and adhesion in human vasculature. The realistic geometry of vascular network and fluid dynamics of blood flow are accurately captured through the finite element model. The microscopic interactions between NPs and red blood cells within blood flow and adhesion of NPs to vessel wall are resolved through the molecular dynamics simulation. A robust and efficient coupling interface is built to couple the finite element and molecular dynamics solvers. Specifically, this project aims to 1) create a multiscale and multiphysics computational model for predicting the vascular dynamics of NPs under the influence of realistic geometrical and physiochemical features of human vasculature; 2) craft an interface coupling technique that enhances computational accuracy and predictability by coupling the finite element and molecular dynamics solvers; 3) build testsuits for multiscale and multiphysics simulations for coupled solution error and convergence analysis; and 4) advance the current cyberinfrastructure to accelerate the material design process and enrich the cyber-enabled materials design community. Such a computational method can be used to explore how the vascular dynamics of NPs will be affected by their size, shape, surface and stiffness properties, as well as complex geometry of human vasculature. The simulation results can further guide experimentalists to design NP-mediated drug delivery platforms that optimally accumulate within diseased tissue to provide better imaging sensitivity, therapeutic efficacy and lower toxicity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

通过纳米医学，正在出现将药物分子直接输送到患病区域进行癌症治疗的重要方法。 靶向药物递送是最有前途的方法之一，它依赖于携带和释放药物的纳米颗粒（NP）。 纳米粒子药物载体的治疗效果取决于病灶部位药物分子的适当浓度。 纳米颗粒需要直接输送到患病组织，同时最大限度地减少其他组织对纳米颗粒的吸收，从而减少对健康组织的潜在危害。 因此，通过了解纳米粒子携带的药物如何在人体内运输和分散，可以显着提高这些纳米粒子的设计以及靶向药物递送的功效。 该项目提出了一套计算工具来模拟和研究纳米颗粒在人体脉管系统中的运输和分散。 这反过来又可以提供更好的成像灵敏度、治疗效果和更低的基于纳米粒子的药物载体的毒性。 该项目的多学科性质还汇集了生物学、工程学和计算机科学的概念，以教育下一代计算生物学家、科学家和工程师。因此，这项研究符合 NSF 促进科学进步和促进国民健康、繁荣和福利的使命。该项目的技术目标是创建一种混合有限元和分子动力学计算方法，用于模拟人体脉管系统中纳米颗粒的运输和粘附。 通过有限元模型准确捕捉血管网络的真实几何形状和血流的流体动力学。 通过分子动力学模拟解决了血流中纳米粒子与红细胞之间的微观相互作用以及纳米粒子与血管壁的粘附。 建立了强大且高效的耦合接口来耦合有限元和分子动力学求解器。 具体来说，该项目的目标是：1）创建一个多尺度和多物理计算模型，用于预测在人体脉管系统的实际几何和物理化学特征影响下纳米颗粒的血管动力学； 2) 设计一种界面耦合技术，通过耦合有限元和分子动力学求解器来提高计算精度和可预测性； 3) 构建多尺度和多物理场仿真测试套件，以进行耦合解误差和收敛分析； 4）推进当前的网络基础设施，以加速材料设计过程并丰富网络支持的材料设计社区。 这种计算方法可用于探索纳米粒子的血管动力学如何受到其尺寸、形状、表面和刚度特性以及人体脉管系统的复杂几何形状的影响。 模拟结果可以进一步指导实验人员设计纳米粒子介导的药物递送平台，使其在病变组织内最佳积聚，以提供更好的成像灵敏度、治疗效果和更低的毒性。该奖项反映了 NSF 的法定使命，并通过使用 NSF 的评估被认为值得支持。基金会的智力价值和更广泛的影响审查标准。

项目成果

Computational investigation on lipid bilayer disruption induced by amphiphilic Janus nanoparticles: combined effect of Janus balance and charged lipid concentration

两亲性 Janus 纳米粒子诱导的脂质双层破坏的计算研究：Janus 平衡和带电脂质浓度的综合影响

• DOI: 10.1039/d3nr00403a
• 发表时间: 2023-10
• 期刊: Nanoscale
• 影响因子: 6.7
• 作者: Nguyen, Danh;Wu, James;Corrigan, Patrick;Li, Ying
• 通讯作者: Li, Ying

Machine learning-based prediction for single-cell mechanics

基于机器学习的单细胞力学预测

• DOI: 10.1016/j.mechmat.2023.104631
• 发表时间: 2023-03-01
• 期刊: Mechanics of Materials
• 影响因子: 3.9
• 作者: Danh;Lei Tao;Huilin Ye;Ying Li
• 通讯作者: Ying Li