Effective, Reagent-free Detection of the Odor Signature of Covid-19 Infection Using a Nano-Enabled Sensor Array

使用纳米传感器阵列无需试剂即可有效检测 Covid-19 感染的气味特征

• 批准号: 10266403
• 负责人: Alan T Johnson
• 金额: $ 99.98万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-21 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10266403
• 关键词: Address; Age; Astronomy; Benchmarking; COVID-19; COVID-19 diagnosis; COVID-19 screening; COVID-19 testing; Carbon Nanotubes; Centers for Disease Control and Prevention (U.S.); Characteristics; Chemicals; Classification; Clinical; Code; Collaborations; Collection; Communities; Computer software; Computers; Counseling; DNA; Data; Data Analyses; Detection; Development; Device or Instrument Development; Devices; Diagnosis; Diagnostic; Discriminant Analysis; Disease; Engineering; Ensure; Florida; Future; Gender; Goals; Gold; Hand; Health; Housekeeping; Human; Human Resources; Human body; In Vitro; Individual; Information Sciences; International; Intuition; Laboratories; Lawyers; Mass Fragmentography; Measurement; Mechanics; Medical Device; Methods; Modeling; Modernization; Monitor; Nose; Occupations; Odors; Participant; Pathologic; Pathway interactions; Patients; Pattern; Pennsylvania; Performance; Phase; Physics; Production; RADx; Reagent; Reporting; Research; Risk; SARS-CoV-2 infection; SARS-CoV-2 negative; SARS-CoV-2 positive; Sampling; Skin; Software Engineering; Solid; Source; Specificity; Spottings; System; Systems Development; Technology; Testing; Time; Training; Universities; Validation; Viral; Virus Diseases; Visual; Workplace; animal care; artificial neural network; base; community setting; coronavirus disease; cost; design; design and construction; ethnic diversity; experience; high standard; machine learning algorithm; medical schools; member; multidisciplinary; nano; nanosensors; next generation; novel virus; operation; prevent; programs; prototype; public health emergency; racial diversity; sample collection; screening; screening program; sensor; sex; software development; software systems; vapor; volatile organic compound

PROJECT SUMMARY COVID-19 presents a public health emergency: There is a critical need for rapid, not reagent intensive, non- invasive testing technologies. This program will lead to the production of a prototype system to diagnose COVID-19 infection using the body odor signature of the disease. Our goal is to maximize societal impact by creating a validated prototype that can be used in a community or workplace setting by minimally trained personnel for low-cost, on-the-spot diagnosis within minutes. The system will be developed in a manner that puts it on a pathway for rapid FDA approval. The Research Aims are: Aim 1. Optimization, assembly, and integration of a prototype system with the ability to odor signature of COVID-19 in samples of body odor. The system will be simple to use, pose essentially zero risk to the operator and the test subject, and report a result within minutes. The production cost at scale will be approximately $9,000 for the complete measurement system, with a per test cost of approximately $0.50. The design and construction of the prototype will be conducted by Novo Engineering, a leading firm with extensive experience in medical device development. Aim 2. Software development. Software for the system from VOC sampling to final diagnostic result will be developed to ensure error-free operation of the device. Our preliminary results suggest that simple linear discriminant analysis (LDA) does an excellent job of classifying VOCs from human body odor as COVID-19 positive or negative (92% sensitivity and 87% specificity). Optimization of the sensor array (Aim 1) and use of richer feature sets in our classifier models will lead to further performance improvements in the prototype system. Aim 3. System Benchmarking and Validation. We will benchmark the full prototype system against a number of VOC mixtures, with and without in vitro skin models. The system will undergo extensive testing against body odor samples from individuals with pathological conditions other than COVID-19 and other sources of potentially confounding VOCs. The prototype will be validated against 1000 samples drawn from the COVID-SAFE program at Penn. The screening will include all members of the Penn community, and represents incredible racial and ethnic diversity as well as a wide variance in age, sex, and gender. Aim 4. Regulatory Approval Plan The plan will be developed under the direction of Sr/Key personnel John Fuson, JD, an attorney at Crowell & Moring LLP and a former Associate Chief Counsel at FDA. Novo Engineering has extensive experience in guiding prototype design in alignment with the requirements for FDA approval. The proposed COVID-19 VOC-based testing device will be regulated by the FDA, likely as a Class I or II medical device. Because there is no clear predicate device to reference in this case, we intend to submit a direct de novo petition to FDA asking the agency to categorize and clear the proposed COVID-19 testing device as Class I or Class II without reference to any predicate.

项目总结 新冠肺炎引发公共卫生紧急情况：迫切需要快速、非试剂密集型、非 侵入性检测技术。本程序将产生一个原型系统进行诊断 新冠肺炎感染采用体臭为特征的疾病。我们的目标是最大限度地提高社会影响力 通过创建可在社区或工作场所环境中使用的经过验证的原型，以最低限度地 经过培训的人员可在几分钟内进行低成本的现场诊断。该系统将在一个 这使其走上了快速获得FDA批准的道路。研究的目的是： 目标1.具有气味特征能力的原型系统的优化、组装和集成 体味样本中含有新冠肺炎。该系统将简单易用，对 操作员和测试对象，并在几分钟内报告结果。规模化生产成本将为 整个测量系统的成本约为9000美元，每次测试的成本约为0.50美元。这个 原型的设计和建造将由Novo Engineering进行，该公司是一家领先的公司，拥有广泛的 有医疗器械研发经验。 目标2.软件开发。从VOC采样到最终诊断结果的系统软件将是 为确保设备运行无错误而开发。我们的初步结果表明，简单的线性 判别分析(LDA)很好地将人体气味中的VOCs分类为新冠肺炎 阳性或阴性(敏感性为92%，特异性为87%)。传感器阵列的优化(目标1)和使用 我们的分类器模型中的更丰富的特征集将导致原型系统的性能进一步提高。 目标3.系统基准和验证。我们将对完整的原型系统进行基准测试 具有和不具有体外皮肤模型的VOC混合物。该系统将接受针对Body的广泛测试 来自新冠肺炎和其他潜在疾病来源以外的病理情况的个人的气味样本 令人困惑的VOCs。原型将根据从COVID-SAFE计划中提取的1000个样本进行验证 在宾夕法尼亚大学。放映将包括宾夕法尼亚大学社区的所有成员，并代表了令人难以置信的种族和 种族多样性以及年龄、性别和性别上的巨大差异。 目标4.监管审批计划该计划将在高级/关键人员约翰的指导下制定 Fuson，JD，Crowell&Mory LLP的律师，FDA的前副首席法律顾问。Novo Engineering 在指导原型设计方面具有丰富的经验，符合FDA批准的要求。这个 拟议的基于新冠肺炎VOC的检测设备将受到美国食品和药物管理局的监管，可能是I类或II类医疗设备 设备。因为在这种情况下没有明确的谓词设备可供参考，所以我们打算提交一个直接从头开始 向美国食品和药物管理局请愿，要求该机构将拟议的新冠肺炎检测设备归类并清除为I类或 II类，不引用任何谓词。