课题基金 / 基金详情

SNM: Scalable Nanomanufacturing of Fab Compatible High-Density Nanowire Arrays for High-Throughput Drug Screening

SNM: Scalable Nanomanufacturing of Fab Compatible High-Density Nanowire Arrays for High-Throughput Drug Screening
SNM:用于高通量药物筛选的可扩展纳米制造兼容工厂的高密度纳米线阵列
批准号:
1728497
负责人:
Shadi Dayeh
金额:
$150.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31

项目摘要

项目成果

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中文摘要
翻译
活体动物的细胞非常小,但测量和操纵它们对于生产新的医学疗法至关重要。有一些令人鼓舞的新方法可以一次了解和控制一个细胞,但现在真的没有技术来单独测量和控制治疗所需的数千或数百万个细胞。迫切需要使用多个纳米设备来单独测量和控制细胞的新方法。该奖项将研究一种同时控制和测量多个电池的方法。基础技术是一个高密度的纳米线平台,它与培养系统中的细胞相互作用。纳米线设备的可伸缩纳米制造将使建造“芯片上的纳米实验室”机器成为可能。这种微小的“实验室”,与患者自身不断生长的细胞相结合,可以创建低成本、可预测的药物筛选平台,以加快药物发现和个性化治疗。该项目为本科生、高中生和代表性不足的少数民族学生提供了材料科学、工程和医学跨学科研究的培训机会。它补充和改进了课程课程,并促进了与行业合作伙伴的强有力的翻译交流。该项目旨在克服开发基于纳米线阵列的系统的障碍,使3D网络中的多用途、非破坏性、高灵敏度测量成为可能,而膜片钳、自动贴片或微电极阵列技术无法实现这些测量。研究了与药物筛选高度相关的人类模型--人源性神经元和心肌细胞。该项目探索了纳米压痕光刻作为一种可扩展的纳米制造方法,以开发晶片规模的纳米线神经生理学平台,该平台可扩展到250个井的8000个同步数据点,每个井有32个纳米线电极。这种可扩展的制造方法能够将高密度和大量的纳米线集成在集成系统中,该集成系统包括芯片上采集和数字化电子以及微流控药物干预通道和井。此外,还设计了多高度纳米线的新结构,用于筛选来自3D神经元和心肌细胞网络的药物效应,并将读出电子学与纳米线传感器完全集成。最后,可扩展到1820个井和115,840个同时测量点的单个低成本平台上的所有组件都是单片集成的,并且该平台通过Sanford Burnham Prebys医学发现研究所和加州大学圣地亚哥分校的药物小组进行了验证。这些技术创新应该能够实现跨组织深度的非破坏性细胞内电位测量。
英文摘要
Cells from living animals are very small, and yet measuring them and manipulating them are critical for producing new medical therapies. There are encouraging new methods to understand and control cells one at a time, but there really isn't now the technology to measure and control individually the thousands or millions of cells needed for a therapy. New approaches to individually measure and control cells using multiple nanoscopic devices are sorely needed. This award will study a method to control and measure many cells simultaneously. The base technology is a high-density platform of nanoscopic wires that interact with the cells in a culture system. The scalable nanomanufacturing of nanowire devices will make it possible to build "nanolab-on-a-chip" machines. Such tiny "laboratories", combined with a patient's own growing cells could create low-cost, predictive drug-screening platforms to accelerate drug discovery and personalized treatments. The project provides training opportunities for undergraduate, high school, and under-represented minority students in interdisciplinary research in materials science, engineering, and medicine. It augments and improves the course curriculum, and fosters a robust translational exchange with industry partners. The project aims to overcome the barriers in developing a nanowire array-based system that enables multi-use, non-destructive, high-sensitivity measurements in 3D networks that are not possible with patch-clamp, automated patch, or microelectrode array techniques. Human-derived neurons and cardiomyocytes, which are highly relevant human models for drug screening, are studied. The project explores nanoimprint lithography as a scalable nanomanufacturing method to develop a wafer-scale nanowire neurophysiology platform scalable to 8000 simultaneous data points for 250 wells with 32 nanowire electrodes each. This scalable fabrication method enables the integration of nanowires in high densities and large numbers in integrated systems that comprise on-chip acquisition and digitization electronics and microfluidic drug intervention channels and wells. Furthermore, new architectures of multiple height nanowires are devised for screening the effects of drugs from 3D neuronal and cardiomyocyte networks and fully integrate readout electronics with the nanowire sensors. Finally, all components on a single, low cost platform scalable to 1820 wells and 115,840 simultaneous measurement points are monolithically integrated and the platform validated with a panel of drugs at the Sanford Burnham Prebys Medical Discovery Institute and UC San Diego. These technical innovations should enable non-destructive intracellular potential measurements across the depth of a tissue.
期刊论文(23)
专著(0)
科研奖励(0)
会议论文
DOI: 10.21769/bioprotoc.3755
发表时间: 2020-09-20
期刊: BIO-PROTOCOL
影响因子: 0.8
作者: [D'Antonio-Chronowska, Agnieszka, D'Antonio, Matteo, Frazer, Kelly A.]
通讯作者: Frazer, Kelly A.
DOI: 10.1002/admt.202100224
发表时间: 2021
期刊: Advanced Materials Technologies
影响因子: 6.8
作者: [Oh, Hongseok, Dayeh, Shadi A.]
通讯作者: Dayeh, Shadi A.
DOI: 10.3389/fnins.2020.00055
发表时间: 2020-02-28
期刊: FRONTIERS IN NEUROSCIENCE
影响因子: 4.3
作者: [Hermiz, John, Hossain, Lorraine, Gilja, Vikash]
通讯作者: Gilja, Vikash
DOI: 10.1002/adfm.202112045
发表时间: 2022-02-25
期刊: ADVANCED FUNCTIONAL MATERIALS
影响因子: 19
作者: [Lee,Sang Heon, Thunemann,Martin, Dayeh,Shadi A.]
通讯作者: Dayeh,Shadi A.
共 10 条
    Force Sensing Surgical Forceps Using Novel Piezoelectric TFT Array for Robotic Surgery
    • 批准号:
      2114482
    • 项目类别:
      Standard Grant
    • 资助金额:
      $36.0万
    • 财政年份:
      2021
    • 负责人:
      Shadi Dayeh
    • 依托单位:
    MsRI-EW: Workshop for Clinical Translation of Implantable Devices. To be Held Virtually, August 10-12, 2020.
    • 批准号:
      2034627
    • 项目类别:
      Standard Grant
    • 资助金额:
      $5.0万
    • 财政年份:
      2020
    • 负责人:
      Shadi Dayeh
    • 依托单位:
    EAGER: Exploiting Superior Electrochemical Characteristics of Scaled PEDOT:PSS Microelectrode Arrays for High Fidelity Electrocorticography
    • 批准号:
      1743694
    • 项目类别:
      Standard Grant
    • 资助金额:
      $10.0万
    • 财政年份:
      2017
    • 负责人:
      Shadi Dayeh
    • 依托单位:
    Monolithically Integrated High-Power GaN Devices and Si CMOS Circuits for High Frequency and High Power Converter
    • 批准号:
      1711030
    • 项目类别:
      Standard Grant
    • 资助金额:
      $36.0万
    • 财政年份:
      2017
    • 负责人:
      Shadi Dayeh
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis