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Automating a platform for rapid clinical microbiology

Automating a platform for rapid clinical microbiology
快速临床微生物学自动化平台
批准号:
710319
负责人:
金额:
$10.86万
依托单位:
依托单位国家:
英国
项目类别:
GRD Proof of Concept
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --

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中文摘要
翻译
该公司开发了一种测试方法,使医院微生物实验室能够快速检测血液中的细菌和真菌感染。目前的方法通常需要1-3天才能判断血液标本是否呈阳性,如果呈阴性则需要5天报告。新的检测在24小时内提供阳性和阴性结果,这有助于节省医院费用和不必要的抗生素使用,并有助于困难的诊断。然而,这项测试需要训练有素的科学家进行3个小时。这种手工需求使得繁忙的实验室很难将新测试融入其日常工作流程中。SMART项目旨在展示测试自动化版本的概念证明。在仪器上进行测试需要开发从血液污染物中分离微生物的新方法,这是项目中的一个关键风险因素。最终的自动化方法旨在将实验室工作人员所需的手工时间减少到几分钟,并允许每天运行更多数量的测试,同时提高准确性。医院微生物学家表示,让实验室更容易进行测试将更有可能被采用,预计这将大大促进英国和全球的销售。如果SMART概念验证成功,公司打算完成开发并推出自动化检测产品,并将这种自动化应用于未来的产品。
英文摘要
The Company has developed a test allowing the hospital microbiology laboratory to rapidlydetect bacterial and fungal infections in blood. Current methods usually take 1-3 days to tell ifa blood specimen is positive and 5 days to report if it is negative. The new test provides bothpositive and negative results in 24 hours which helps to save hospital costs and unnecessaryantibiotic use and will assist in difficult diagnoses. However the test takes 3 hours for atrained scientist to perform. This manual requirement makes it harder for a busy lab to fit thenew test into its daily workflowThe SMART project is intended to show proof of concept for an automated version of the test.Running the test on an instrument requires development of new methods for separating microorganismsfrom blood contaminants and this is a key risk factor in the project. It is intendedthat the final automated method will reduce the amount of hands on time required by lab staffto a matter of minutes and allow higher numbers of tests to be run per day with improvedaccuracy. Hospital microbiologists have said that making the test easier for the lab to run willmake adoption much more likely and this is expected to boost sales significantly in the UKand worldwide. If the SMART proof of concept is successful the Company intends tocomplete development and launch the automated detection product as well as apply thisautomation to future products.
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Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information