课题基金 / 基金详情

OxDX: Machine learning enhanced point of care diagnosis platform for infectious diseases: faster, more accessible, user intuitive, leveraging novel fluorescent labelling of enveloped viruses.

OxDX: Machine learning enhanced point of care diagnosis platform for infectious diseases: faster, more accessible, user intuitive, leveraging novel fluorescent labelling of enveloped viruses.
OxDX:机器学习增强型传染病护理诊断平台:更快、更容易使用、用户直观,利用包膜病毒的新型荧光标记。
批准号:
10032103
负责人:
金额:
$36.59万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
英国初创公司OxDX Ltd将通过开发传染病诊断平台,利用OxDX独特的病原体识别技术,改变现有的人类病毒检测方法。由流感、副流感和呼吸道合胞病毒等病原体引起的传染病每年导致数千人死亡。目前的检测工作流程严重依赖于集中实验室,检测能力和物流网络在需求高峰期难以发挥作用。目前的病毒检测诊断方法,如病毒培养、RT-PCR或基于抗原的快速诊断检测,往往受到等待时间长或灵敏度和特异性有限的阻碍。因此,迫切需要分散的检测解决方案,将检测从实验室转移到护理点,提供直接,快速和灵敏的病毒检测方法。该项目专注于开发OxDX的诊断平台,提供降低成本的步骤变化,并在护理点提供实验室质量结果。适合临床环境之外的非临床专家使用,该平台可以迅速部署,改善全球获得超快速、准确的传染病诊断的机会。
英文摘要
UK-based start-up OxDX Ltd will transform existing approaches to human virus detection, through the development of an infectious disease diagnosis platform, leveraging OxDX's unique pathogen identification technology.Infectious diseases caused by pathogens like influenza, parainfluenza and respiratory syncytial virus cause many thousands of deaths annually. Current testing workflows rely heavily on centralised laboratories, with testing capacity and logistics networks struggling during peak demand spikes.Current diagnostic approaches for virus detection, such as virus culture, RT-PCR or antigen-based rapid diagnostic tests, are often hampered by long waiting times or limited sensitivity and specificity. As a result, there is an urgent need for decentralising testing solutions, moving testing away from laboratories to the point of care that provides straightforward, fast and sensitive viral detection methods.This project focuses on the development of OxDX's diagnostic platform, providing a step-change in cost reduction and delivering laboratory quality results at the point of care.Suitable for utilisation by non-clinical experts beyond clinical settings, the platform can be rapidly deployed, improving global accessibility to ultra-fast, accurate infectious disease diagnostics.
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海外基金
Understanding structural evolution of galaxies with machine learning
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位: