SBIR Phase I: A Powerful Clinical Aid in the Diagnosis of Vaginitis to Prevent PTB and Stop STI Transmission

SBIR 第一阶段：诊断阴道炎以预防 PTB 和阻止 STI 传播的强大临床辅助工具

• 批准号: 2026102
• 负责人: Peggy Robinson
• 金额: $ 24.97万
• 依托单位: CAZA HEALTH LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026102&HistoricalAwards=false
• 关键词: SBIR; Phase; Powerful; Clinical; Aid; SBIR; Phase; Powerful; Clinical; Aid

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide fast, accurate diagnosis of vaginal infections. Vaginitis results in 10 million office visits a year representing 10% of all US women’s health visits, is known to dramatically increase susceptibility to sexually transmitted infections. External testing is expensive and can take from a day to weeks for results. For current in-office tests, 40% of all yeast infections and 30% of bacterial infections are misdiagnosed and require further visits. More importantly, vaginitis can lead to a large fraction of spontaneous preterm births - a major cause of neonatal mortality, emotional distress and lifelong disability worldwide. In the US, PTB results in healthcare costs of $26 B/year, motivating a fast and accurate test. This project will develop an advanced test that uses artificial intelligence (AI) to study samples quickly and accurately in the doctor's office.This Small Business Innovation Research Phase I project advances a novel test for vaginitis upon clinical presentation. This project leverages Artificial Intelligence (AI) image analysis with a high-quality fluorescence microscope to rapidly scan specimens in the doctor's office for fast diagnosis. This project will validate preliminary studies suggesting higher image accuracy compared to viewing similar samples under a microscope. Phase 1 of this project will examine prepared samples from diverse patient populations of up to 500 women to optimize analysis and characterization of VHA automated digital pathology system. All samples will be compared to manual assessment currently used clinically. Additionally, user testing in multiple types of clinical research environments, such as medical schools and health networks, will be undertaken to diversify patient sample populations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I期项目的更广泛的影响/商业潜力是提供对阴道感染的快速，准确的诊断。阴道炎每年可进行1000万个办公室就诊，占美国妇女健康访问的10％，众所周知，可显着增加对性传播感染的敏感性。外部测试很昂贵，可能需要一天到几周才能取得结果。对于当前的办公室测试，所有酵母菌感染中有40％和30％的细菌感染被诊断出来，需要进一步就诊。更重要的是，阴道可以导致大量的赞助早产 - 这是新生儿死亡率，情绪困扰和终身残疾的主要原因。在美国，PTB的医疗保健费用为每年26美元，激发了快速准确的测试。该项目将开发一项高级测试，该测试使用人工智能（AI）在医生办公室快速准确研究样品。本小企业创新研究阶段I项目在临床表现时为阴道进行了新的测试。该项目利用具有高质量荧光显微镜的人工智能（AI）图像分析来快速扫描医生办公室的快速诊断标本。该项目将验证初步研究表明，与在显微镜下查看相似样品相比，图像精度更高。该项目的第1阶段将检查来自多达500名妇女的患者人群的样本，以优化VHA自动化数字病理系统的分析和表征。将将所有样品与当前在临床上使用的手动评估进行比较。此外，将采取多种类型的临床研究环境中的用户测试，例如医学院和健康网络，以使患者样本人群多样化。该奖项反映了NSF的法定任务，并通过使用基金会的智力优点和更广泛的影响来评估NSF的法定任务。