Chemical nanosensor arrays for human breath-based diagnostics: Perspective and a promising result for COVID-19 detection

Diagnosis of disease from breath signatures comprised of volatile, mostly organic compounds is a promising field of research and medical application that, after more than 4 decades of active research, has yielded far fewer breatkthroughs than its potential initially appeared to promise. The recent pandemic spurred many teams, including ours at NASA, to investigate this approach for a particular application: determining COVID-19 infection status. In this Perspective , we examine the science and technology underlying one means of implementing such diagnostics, the so-called electronic nose, in an implementation named EnCOVID: Electronic nose for Coronavirus Organic Volatiles Infection Detection. We demonstrate an approach to developing application-specific arrays of sensors that balance chemical selectivity with reversibility in a manner well suited to chemically complex mixtures like human breath; the method differs markedly from how single, highly selective sensors are typically chosen. Using a 64-nanosensor array of carbon-nanotube-based chemiresistors, we used SIMCA (soft independent modeling by class analogy) on results from 63 volunteers to show that COVID-19 status, positive or negative, can be correctly classified, relative to gold-standard RT-PCR, 92% of the time. While the data set is too small to generate the critical independent training and testing sets, this classification success is a promising basis upon which to design a larger, more definitive study. We conclude that the portability and possibility of low-cost, high-volume manufacture of an electronic nose-based system may be most valuable for applications outside hospitals and clinics, including situations—like an epidemic—and venues, from airports to sports venues to schools, where large numbers of people have to be screened rapidly, in parallel.