Portable GC detector for breath-based COVID diagnostics

Project Summary/Abstract: This proposal has two major goals: 1) Define signature exhaled breath volatileorganic compounds (VOCs) to diagnose SARS-CoV-2 infections, and 2) Develop a portable chemical sensingdevice that can capture and detect exhaled VOCs and includes machine learning algorithms for automateddata processing and results interpretation. This project will bring a portable sensor forward into clinical use withthe aim of supplementing COVID-19 diagnostics with a reagentless alternative. Breath testing of exhaled VOCbiomarkers 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 exhaledbreath 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 samplesfrom 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 DavisMedical Center (Sacramento, CA) and VA Northern California Health Care System (Mather, CA), where MPIDr. Kenyon and Co-Is Drs. Harper and Schivo have joint clinical appointments. Our group has a proven trackrecord to conduct these types of clinical breath studies. In Aim #2, we will develop a portable breath analysisdevice using our novel miniature differential mobility spectrometry (DMS) detector, coupled with chip-basedgas chromatography. DMS is a subset of ion mobility spectrometry and detects VOCs at ambient temperaturesand 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 willcompare functionality of a compact commercially available GC column to a micro-GC column chip fromDeviant, a subcontractor in this work. Individual components of this device have already been developed, andunder direction of MPI Prof. Davis, Chair of Mechanical and Aerospace Engineering, a team of researchengineers would integrate these pieces together into a single unit. Collaborator Prof. Chuah would guidedevelopment of a custom software package for the device with machine learning and artificial intelligencecapabilities for automated data processing and interpretation. The device would be placed in the hands ofclinicians, who would provide feedback that engineers would immediately incorporate into the device andreturn to the clinicians for more testing. Under Aim #3, our team would process the GC-MS and GC-DMS datagenerated in this work, identifying a novel VOC profile for COVID-19 diagnostics. Aim #4 would initiate towardsthe end of this study to develop both a regulatory pathway & contract manufacturing plan for large scaleproduction 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.