Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics

开发用于定量筛选吞咽困难治疗药物的纳米膜电子学和机器学习算法

基本信息

  • 批准号:
    10675556
  • 负责人:
  • 金额:
    $ 23.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-23 至 2024-07-31
  • 项目状态:
    已结题

项目摘要

Project Summary Dysphagia is an impairment of the swallow reflex's neurological and muscular functions that causes a debilitating and potentially deadly condition such as choking, malnutrition, dehydration or pneumonia during swallowing. Dysphagia afflicts almost 15 million Americans, particularly individuals 50-60 years or older with up to a 20% chance of dysphagia. However, regardless of the cause of dysphagia, currently there are no available therapeutic treatments. Limitation of preclinical tools and methods to study dysphagia is one of the biggest reasons for the lack of therapeutic treatment for dysphagia. Video-fluoroscopic swallowing study (VFSS) has been used to diagnose dysphagia in a clinical study as well as research with animal models for drug development. However, the VFSS method in clinical study relies on the active cooperation of a human subject, such as ingestion of food with barium (oral contrast agent) and movement immobilization during X-ray imaging. The VFSS tool shows the severe issue in an animal study due to uncontrollable target, which results in poor image quality and unreliable drug development. Overall, none of the existing commercial systems can offer a portable, real-time, continuous monitoring of swallowing with either humans or animals. Here, this project will develop a novel, nanomembrane electronic system that offers a continuous, quantitative assessment of swallowing activities in a non-invasive way on the skin of rat models, which will help to develop potential dysphagia drugs. Specifically, we will develop soft, ultrathin, lightweight, miniaturized wearable electronics to monitor time-dependent changes of swallowing muscle functions via wireless, real-time recording of electromyograms on swallowing muscles of a dysphagia rat model. In this project, our initial study in the evaluation of dysphagia therapeutics will focus on ALS-related dysphagia since there are well-established animal models (transgenic superoxide dismutase; SODG93A) with severe dysphagia at a young age. SODG93A animal models have been widely used to screen potential therapeutic compounds, including two FDA-approved ALS drugs: edaravone and riluzole. Collectively, if successful, the newly developed nanomembrane electronics will be a game-changer in the therapeutic evaluation of candidate drugs for ALS-related dysphagia as well as other diseases- related dysphagia. The research outcome is expected to provide a new drug for an effective treatment of dysphagia, which will eventually reduce mortality and improve the quality of life of dysphagia patients.
项目总结

项目成果

期刊论文数量(0)
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Woon-Hong Yeo其他文献

Woon-Hong Yeo的其他文献

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{{ truncateString('Woon-Hong Yeo', 18)}}的其他基金

Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics
开发用于定量筛选吞咽困难治疗药物的纳米膜电子学和机器学习算法
  • 批准号:
    10493361
  • 财政年份:
    2021
  • 资助金额:
    $ 23.65万
  • 项目类别:
Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics
开发用于定量筛选吞咽困难治疗药物的纳米膜电子学和机器学习算法
  • 批准号:
    10373326
  • 财政年份:
    2021
  • 资助金额:
    $ 23.65万
  • 项目类别:

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