Portable GC detector for breath-based COVID diagnostics

用于基于呼吸的新冠肺炎诊断的便携式 GC 检测器

基本信息

批准号：
10266337
负责人：
CRISTINA ELIZABETH DAVIS
金额：
$ 97.55万
依托单位：
UNIVERSITY OF CALIFORNIA AT DAVIS
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-12-21 至 2022-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10266337
关键词：
2019-nCoV Aerospace Engineering Appointment Artificial Intelligence Automatic Data Processing Benchmarking Biological Markers Breath Tests COVID diagnostic COVID-19 COVID-19 diagnosis COVID-19 diagnostic COVID-19 test California Catalogs Chemicals Clinical Clinical Chemistry Clinical Pathology Clinical Trials Communities Computer software Consultations Contact Tracing Contracts Coupled Custom Data Data Analyses Detection Development Devices Diagnosis Diagnostic Diagnostic tests Disease Engineering Environment Exhalation Feedback Fingerprint Flushing Funding Gas Chromatography Gases Goals Gold Healthcare Healthcare Systems Heating Human Resources Individual Industry Infection Intuition Joints Lead Liquid substance Machine Learning Manufacturer Name Maps Mass Spectrum Analysis Materials Testing Mathematics Measurement Measures Mechanics Medical center National Institute of Biomedical Imaging and Bioengineering Observational Study Output Pattern Polymerase Chain Reaction Process Production Public Health Publishing Rapid diagnostics Reagent Regulatory Pathway Research SARS-CoV-2 infection SARS-CoV-2 negative SARS-CoV-2 positive Sampling Sensitivity and Specificity Site Skin Spectrometry Standardization System Technology Temperature Testing Time Training Translational Research United States United States National Institutes of Health Upper Respiratory Infections Viral Work base biomarker signature clinical care detector deviant differential expression disease transmission graphical user interface instrument intelligent algorithm ion mobility large scale production machine learning algorithm metabolomics novel novel diagnostics pandemic disease portability pressure programs prospective prototype recruit risk mitigation scale up sensor standard of care volatile organic compound

项目摘要

Project Summary/Abstract: This proposal has two major goals: 1) Define signature exhaled breath volatile organic compounds (VOCs) to diagnose SARS-CoV-2 infections, and 2) Develop a portable chemical sensing device that can capture and detect exhaled VOCs and includes machine learning algorithms for automated data processing and results interpretation. This project will bring a portable sensor forward into clinical use with the aim of supplementing COVID-19 diagnostics with a reagentless alternative. Breath testing of exhaled VOC biomarkers is a relatively new concept that has the potential to transform healthcare in the US and globally. Our overarching hypothesis is that a miniature breath analysis device can measure signatures of exhaled breath VOCs in real-time and correlate their profile to viral upper respiratory infections such as SARS-CoV-2, even asymptomatically. In Aim #1, we propose a prospective, observational study to analyze breath samples from COVID-19 positive and negative subjects, solely for the purpose of analysis through gold standard GC- MS to define breath VOC biomarkers of infection. We will recruit subjects at two local sites, the UC Davis Medical Center (Sacramento, CA) and VA Northern California Health Care System (Mather, CA), where MPI Dr. Kenyon and Co-Is Drs. Harper and Schivo have joint clinical appointments. Our group has a proven track record to conduct these types of clinical breath studies. In Aim #2, we will develop a portable breath analysis device using our novel miniature differential mobility spectrometry (DMS) detector, coupled with chip-based gas chromatography. DMS is a subset of ion mobility spectrometry and detects VOCs at ambient temperatures and pressures, making it highly appropriate for portable devices. This device would include our custom chip- based preconcentrator, which is packed with a chemical sorbent for extraction of VOCs from breath, and will compare functionality of a compact commercially available GC column to a micro-GC column chip from Deviant, a subcontractor in this work. Individual components of this device have already been developed, and under direction of MPI Prof. Davis, Chair of Mechanical and Aerospace Engineering, a team of research engineers would integrate these pieces together into a single unit. Collaborator Prof. Chuah would guide development of a custom software package for the device with machine learning and artificial intelligence capabilities for automated data processing and interpretation. The device would be placed in the hands of clinicians, who would provide feedback that engineers would immediately incorporate into the device and return to the clinicians for more testing. Under Aim #3, our team would process the GC-MS and GC-DMS data generated in this work, identifying a novel VOC profile for COVID-19 diagnostics. Aim #4 would initiate towards the end of this study to develop both a regulatory pathway & contract manufacturing plan for large scale production and deployment of the device for clinical approval. These efforts are supported by collaborator Dr. Nam Tran, Director of Clinical Pathology & Clinical Chemistry at the UC Davis Medical Center.

项目摘要/摘要：该提案有两个主要目标：1）定义签名呼气挥发物有机化合物 (VOC) 来诊断 SARS-CoV-2 感染，以及 2) 开发便携式化学传感该设备可以捕获和检测呼出的 VOC，并包含用于自动化的机器学习算法数据处理和结果解释。该项目将把便携式传感器推向临床使用目的是通过无试剂替代方案来补充 COVID-19 诊断。呼出VOC的呼气测试生物标志物是一个相对较新的概念，有潜力改变美国和全球的医疗保健。我们的首要假设是微型呼吸分析设备可以测量呼出气体的特征实时呼吸 VOC，并将其特征与病毒性上呼吸道感染（例如 SARS-CoV-2）相关联，甚至无症状。在目标#1中，我们提出了一项前瞻性观察性研究来分析呼吸样本来自 COVID-19 阳性和阴性受试者，仅用于通过黄金标准 GC 进行分析- MS 定义呼吸 VOC 感染生物标志物。我们将在两个当地地点招募受试者，即加州大学戴维斯分校医疗中心（加利福尼亚州萨克拉门托）和 VA 北加州医疗保健系统（加利福尼亚州马瑟），其中 MPI 凯尼恩博士和同事。哈珀和斯基沃有联合临床预约。我们的团队拥有成熟的轨道记录进行这些类型的临床呼吸研究。在目标 2 中，我们将开发便携式呼吸分析仪设备使用我们新颖的微型差分迁移谱 (DMS) 检测器，并结合基于芯片的气相色谱法。 DMS 是离子淌度光谱法的一个子集，可在环境温度下检测 VOC 和压力，使其非常适合便携式设备。该设备将包括我们的定制芯片- 基于预浓缩器，其中装有化学吸附剂，用于从呼吸中提取 VOC，并且将将紧凑型市售 GC 色谱柱与微型 GC 色谱柱芯片的功能进行比较 Deviant，这项工作的分包商。该设备的各个组件已经开发出来，并且在 MPI 机械与航空航天工程系主任 Davis 教授的指导下，一个研究团队工程师会将这些部件集成到一个单元中。合作者蔡教授将指导为具有机器学习和人工智能的设备开发定制软件包自动数据处理和解释的能力。该设备将被放置在临床医生将提供反馈，工程师将立即将其纳入设备中，返回临床医生进行更多测试。根据目标 3，我们的团队将处理 GC-MS 和 GC-DMS 数据这项工作中生成的，确定了用于 COVID-19 诊断的新型 VOC 配置文件。目标#4将朝着这项研究的结尾是制定大规模的监管途径和合同制造计划生产和部署该设备以获得临床批准。这些努力得到了合作者 Dr. 的支持。 Nam Tran，加州大学戴维斯分校医学中心临床病理学和临床化学主任。