# A Handheld Microchip for GC analysis of breath to screen for COVID-19

> **NIH NIH U18** · UNIVERSITY OF LOUISVILLE · 2022 · $957,641

## Abstract

Project Summary
 The COVID-19 pandemic has caused unprecedented societal suffering and economic disruption. In the
United States, more than six million people have contracted COVID-19 and more than one hundred ninety
thousand patients have died of this disease to date. Although current COVID-19 diagnostic testing technologies
are critical for slowing the spread of the virus and preventing future outbreaks, they are not practical for field use.
Current diagnostic tests are cumbersome to perform because they use aqueous solutions, require multiple steps,
and hours-to-days to obtain results. Since the US began to reopen the economy in May, there has been a
significant increase in the number of COVID-19 cases. Therefore, there is an urgent need to develop a diagnostic
approach that is non-invasive, portable, and can rapidly provide test results.
 The overall goal of the project is to develop a mobile breath analysis technology for rapid screening for
COVID-19 using a handheld breath collection tool and a portable GC with a photoionization detector (PID). The
handheld tool will be a closed system for trapping select volatile organic compounds (VOCs) on a microfabricated
chip. The captured VOCs will be eluted with ethanol and then analyzed using a commercially available, portable
GC-PID instrument. Artificial intelligence (AI) and machine learning algorithms will be applied to recognize the
VOC pattern that correlates with COVID-19 infection. The central innovation is the microfabricated chip that
captures carbonyl compounds in exhaled breath and thus serves as a preconcentrator, which enables analysis
of carbonyl VOCs by the portable GC-PID. The hypothesis is that the carbonyl metabolome in exhaled breath is
directly related to the body’s reaction to the novel coronavirus infection, and changes in the carbonyl VOC
composition in exhaled breath relative to healthy controls can be used to detect both symptomatic and
asymptomatic COVID-19 patients.
 Three specific aims are proposed to fulfill the overall goal. Aim 1 is to build a disposable handheld breath
analyzer tool for concentrating carbonyl VOCs. Aim 2 is to identify VOC patterns in the breath of COVID-19
patients by machine learning algorithms. Aim 3 is to integrate portable GC technology with the breath sampling
tool for COVID-19 screening guided by an AI system. The University of Louisville is uniquely suited to rapidly
transition the microchip technology to field use because of the PI and Co-PI’s experience in breath analysis and
translational research, and the project team’s experience in virology, infectious diseases, biostatistics, and
artificial intelligence as well as the state-of-the-art facilities that include a MicroNano Technology Center,
Biosafety Level 3 Regional Biocontainment Lab, and an NIH-funded REACH program.

## Key facts

- **NIH application ID:** 10320985
- **Project number:** 4U18TR003787-02
- **Recipient organization:** UNIVERSITY OF LOUISVILLE
- **Principal Investigator:** Xiao-An Fu
- **Activity code:** U18 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $957,641
- **Award type:** 4N
- **Project period:** 2020-12-21 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10320985

## Citation

> US National Institutes of Health, RePORTER application 10320985, A Handheld Microchip for GC analysis of breath to screen for COVID-19 (4U18TR003787-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10320985. Licensed CC0.

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