| 项目编号: | 1706921
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| 项目名称: | Computational platform for predictive magnetohydrodynamic drug targeting |
| 作者: | Andreas Linninger
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| 承担单位: | University of Illinois at Chicago
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| 批准年: | 2017
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| 开始日期: | 2017-09-01
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| 结束日期: | 2020-08-31
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| 资助金额: | 297955
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | drug transport
; magnetic drug
; drug testing
; nanoparticle-drug delivery
; drug delivery method
; therapeutic drug
; simulation platform
; computational platform
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| 英文摘要: | Special blood vessels, for example the blood brain barrier, in the head and spine keep most compounds away from the brain and central nervous system. Certain therapies for brain disorders may be ineffective, simply because the medication cannot reach the brain. To overcome this barrier, this project investigates new methods for the direct administration of therapeutic drugs into the brain. The main strategy is to direct magnetized drugs to specific locations using externally placed magnets, termed magnetic drug targeting to the brain. This research project also seeks to create a computer program for the design, optimization and testing of new therapeutics and delivery techniques. The ability to improve drug delivery methods using computational models potentially benefits all patients suffering from diseases related to the brain and helps pharmaceutical companies meet regulatory demands by enabling them to carefully evaluate potential side effects of new therapeutics. This research project also contributes to the education of a new generation of engineering students. A drug testing and simulation platform built on the University of Illinois at Chicago campus offers research opportunities for undergraduate and high school students and enables virtual experimentation with novel nanomedicine chemistry. In addition, a new graduate course on drug transport within the bioengineering and chemical engineering curricula is being created.
Magnetic drug targeting for brain and central nervous system disorders is a promising delivery method for steering and pinpointing therapeutics to desired locations in the central nervous system. However, determining the parameters for optimal biodistribution inside a living organism poses a formidable engineering challenge. There is critical need to predict biodistribution under magnetic guidance. Currently, two main problems prevent computational fluid dynamics analysis from reliably predicting biodistribution in the central nervous system: (1) magnetohydrodynamic forces acting on nanoparticle suspensions have not been incorporated into existing computational fluid dynamics because they have not been characterized; and (2) existing algorithms require impractical simulation times exceeding central processing unit weeks or months because the mesh sizes necessary to represent central nervous system anatomy are massive, and transport equations exhibit both fast and slow dynamic modes. This research project addresses these obstacles in three parts. First, a magneto-hydrodynamic formulation based on concentrated solution theory is being developed to quantify field effects that steer nanoparticles suspended in pulsating cerebrospinal fluid flow. Then, parametric meshing is being implemented to generate smooth, body-fitted computational grids that represent the anatomical domain concisely at low central processing unit cost. Finally, problem decomposition is being performed that divides fluid flow, magnetic field effects and drug transport into three independently solvable sub-problems. The research results are being used to create a computational platform to optimize targeted nanoparticle-drug delivery to the central nervous system.
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| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/89024
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Andreas Linninger. Computational platform for predictive magnetohydrodynamic drug targeting. 2017-01-01.
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