Award Abstract #2029847

EAGER: Breath-Based Early and Fast Detection of COVID-19 Infection

NSF Directorate:
ENG - Directorate for Engineering
NSF Division:

Division of Chemical, Bioengineering, Environmental, and Transport Systems

Initial Amendment Date:

Latest Amendment Date:

Award Number:

2029847

Award Instrument:

Grant

Program Manager:

Stephanie George

Start Date:

End Date:

Awarded Amount to Date:

$199,359.00

Investigator(s):

Pelagia Gouma [email protected] (Principal Investigator)
Milutin Stanacevic (Co-Principal Investigator)
Andrew Bowman (Co-Principal Investigator)

Sponsor:

Ohio State University
Office of Sponsored Programs
Columbus OH 432101016

NSF Program:
Engineering of Biomed Systems
CER - Ceramics
EBMS - Engineering of Biomedical Systems
Program Reference Code(s):
096Z
7916
Program Element Code(s):
1253
1774
5345
Abstract:

Abstract
The aim of this research project is to enable early and rapid detection of infection COVID-19 by sampling human breath. COVID-19 disease is a pandemic currently, according to the World Health Organization (WHO) caused by the 2019-nCoV virus. Without innate immunity to the novel virus and with the lack of therapeutic means to treat it, the only way to contain the spread of this disease further is through early diagnosis. However, for many infected individuals the disease remains asymptomatic, yet they can potentially transmit COVID-19 and unknowingly infect more of the population. This project will lead to new approach to diagnose COVID-19 infection from sampling human breath.

The investigator proposes to use a disruptive approach to infectious disease diagnosis and to the detection of COVID-19 specifically. This approach involves sampling the breath of human-- or animal in the proposed work-- subjects for three gaseous signaling metabolites (i.e. COVID-19 biomarkers). The hypothesis of the project is that the magnitude of the relative change in these biomarkers upon the subject’s infection with the 2019-nCoV virus provides an early and distinct signal of this infection. The PI will test this hypotheses by producing a three-sensor array, utilizing selective resistive gas sensors based on binary metal oxides, and by testing the breath of swine infected by a beta-coronavirus as well as the breath of humans infected by COVID-19. Measurements will be made repeatedly on definitively or potentially infected subjects to map the rise and fall of the biomarkers over time. Correlating the measurements made with the relative concentration of pro-inflammatory cytokines released in them is expected to produce a diagnostic tool for the pandemic infection. The diagnostic prototype tool will be equipped with wireless capability for rapid deployment as point-of-care, early detection means. The proposed research and technology aim to set the stage for the diagnostics of the future. Establishing the pathway for the effective diagnosis of coronavirus diseases through biomarker monitoring and establishing the specifications required for the early detection of COVID-19 before any symptoms appear are expected to be the major outcomes of the proposed research. Promoting breath analysis as a first response, on-site, point-of-care, personalized diagnostics method is envisioned. Training students working on this project on interdisciplinary research is an added benefit of this research project.

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.