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STTR Phase I: Development of a Computational Tool for Modeling, Simulation, and Design of Next Generation Discrete Droplet Microfluidic Systems

STTR Phase I: Development of a Computational Tool for Modeling, Simulation, and Design of Next Generation Discrete Droplet Microfluidic Systems
STTR 第一阶段:开发用于下一代离散液滴微流体系统建模、仿真和设计的计算工具
批准号:
1321506
负责人:
Jeevan Maddala
金额:
$22.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-07-01 至 2014-06-30

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英文摘要
This Small Business Technology Transfer (STTR) Phase I project proposes to develop a simulation and design software for droplet-based microfluidic devices. Designing microfluidic platforms for biological and biochemistry applications is a laborious process involving several experimental trials. Scaling up a basic design to a parallelized device is another challenge. As a result, computational tools that can hasten the discovery process are essential. The proposed work is on the development of a rational design approach that will comprehensively access the vast design space for developing massively parallelized microfluidic architectures. The intellectual merits of the work are related to: (i) the development of a combined linear algebra and graph theory approach to simulate the behavior of large-scale droplet-based microfluidic platforms in a computationally tractable manner, and (ii) research on a specialized genetic algorithm (GA) approach, which will integrate with the simulation module for the design of customized droplet-based microfluidic platforms based on any desired objective. The first phase of the proposal will focus on the development and demonstration of a microfluidic platform for a specific combinatorial sequencing problem. A deliverable for this phase is a software system that would receive inputs from the user and deliver a CAD device design. The broader impact/commercial potential of this project, if successful, will be the development of several novel design concepts for microfluidic lab-on-a-chip devices that provide the ability to control chemicals at a molecular level. This will profoundly enhance our understanding of the fundamental workings of these devices. Precise control of chemical composition and concentration will lead to discovery of materials that help in protein crystallization and stem cell growth. This will be a valuable resource for pharmaceutical (multibillion dollar industry) companies for drug screening and combinatorial protein designs. Additionally, these platforms also can be designed for biological applications such as preferential separation of cancer cells from healthy cells. Initial customers for this software will be universities and research labs. As the technology successfully negotiates the validation cycle, the software either may be licensed directly to customers or used in a design consultancy mode with industries for specific design projects. The grand vision of the project is the development of an automated system that will synthesize droplet-based microfluidic platforms using either 3D printing or Xurography starting from just a design concept of a user.
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