Nanopore Array for Multiparameter Analysis of Single Extracellular Vesicles

用于单个细胞外囊泡多参数分析的纳米孔阵列

基本信息

  • 批准号:
    10760154
  • 负责人:
  • 金额:
    $ 35万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-20 至 2024-09-19
  • 项目状态:
    已结题

项目摘要

Project Summary Today, researchers and clinicians, in academia and industry, lack the tools and technologies needed to accurately characterize, differentiate, and sort extracellular vesicles (EVs); currently available technologies were simply not developed to characterize entities smaller than 200 nanometers in size. While the importance of EVs in directing cargo delivery for intercellular communication is well known, the inability to profile the true distribution of their biophysical properties is the main hindrance to understanding the mechanisms of action, identifying disease-specific biomarkers, and harnessing the therapeutic potential of EV-based nanomedicine. During this Phase I STTR program, Electronic BioSciences (EBS), a company with a successful track record of commercializing nanopore-based analytical technology and the associated high-performance, low-noise electronics, will collaborate with Distinguished Professor Henry S. White at the University of Utah, who is a foremost expert in nanopores, mass transport and electroanalytical characterization, to develop and demonstrate an entirely new technology capable of state-of-the-art, comprehensive EV characterization and sample profiling at the single-vesicle level. Furthermore, the ability to quickly assess individual EVs will enable the ability to sort and isolate specific EV subpopulations for further downstream characterization and/or utilization. During this project, a prototype system will be built and the feasibility of comprehensively characterizing and sorting/isolating specific EV populations will be demonstrated and validated. The resulting system will have the ease-of-use, throughput, and price point of a high-throughput, “low-resolution” flow-cytometer, but the resolution of state-of- the-art microscopy techniques, such as scanning or transmission electron microscopy (SEM or TEM, respectively) or atomic force microscopy (AFM). The advantage of the proposed technology will be the development of a system enabling the ability to identify and sort/isolate precisely defined populations of biological- and medical-significance nanoscale (<200 nm) entities using high-dimensional (multiparameter) data, which will have applications far beyond EVs, including but not limited to characterizing other nanostructures important in drug delivery and gene therapy nanomedicines such as lipid nanoparticles for vaccines, exosome- based therapeutics, lentivirus, virus-like particles, and polymer-based nanocapsules. Thus, the successful completion of this program will result in a broadly applicable tool able to bring precision to bear on these smallest of couriers and enable the characterization/classification urgently needed to advance the fields of EVs and nanomedicine.
项目摘要 今天,学术界和工业界的研究人员和临床医生缺乏所需的工具和技术, 准确表征,区分和分类细胞外囊泡(EV);目前可用的技术是 只是没有被开发来表征尺寸小于200纳米的实体。虽然电动汽车的重要性 在引导细胞间通信的货物递送方面是众所周知的, 其生物物理特性的主要障碍是了解作用机制, 疾病特异性生物标志物,并利用基于EV的纳米医学的治疗潜力。在此 第一阶段STTR计划,电子生物科学公司(EBS),一家成功的跟踪记录, 将基于纳米孔的分析技术和相关的高性能、低噪音 电子,将与杰出教授亨利S。犹他州大学的白色, 纳米孔、质量传输和电分析表征方面的最重要专家,开发和展示 一种全新的技术,能够进行最先进、全面的EV表征和样品分析 在单个囊泡水平上。此外,快速评估单个电动汽车的能力将使分类的能力成为可能。 并分离特定EV亚群用于进一步下游表征和/或利用。在此 项目,将建立一个原型系统和全面表征和分类/隔离的可行性, 具体的EV人群将得到证实和验证。由此产生的系统将具有易用性, 高通量、“低分辨率”流式细胞仪的通量和价格点,但国家的分辨率, 现有技术的显微镜技术,例如扫描或透射电子显微镜(SEM或TEM, 原子力显微镜(AFM)。所提出的技术的优点将是 开发一个系统,能够识别和分类/隔离精确定义的种群, 使用高维(多参数)数据的生物学和医学意义的纳米级(<200 nm)实体, 其应用将远远超出电动汽车,包括但不限于表征其他纳米结构 在药物递送和基因治疗中重要的是纳米医学,例如用于疫苗的脂质纳米颗粒、外泌体- 基于治疗剂、慢病毒、病毒样颗粒和基于聚合物的纳米胶囊。成功者, 完成这一计划将导致一个广泛适用的工具,能够带来精度,以承担这些最小的 并实现推进电动汽车领域所急需的表征/分类, 纳米医学

项目成果

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Sean German其他文献

Sean German的其他文献

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{{ truncateString('Sean German', 18)}}的其他基金

The Nanopore-based Ion Selective Electrode Vial
基于纳米孔的离子选择电极瓶
  • 批准号:
    10325420
  • 财政年份:
    2021
  • 资助金额:
    $ 35万
  • 项目类别:
Fingerprinting Cancer via Multiparameter Extracellular Vesicle Analysis
通过多参数细胞外囊泡分析对癌症进行指纹识别
  • 批准号:
    10325414
  • 财政年份:
    2021
  • 资助金额:
    $ 35万
  • 项目类别:

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