Instead of Identifying Drunk Drivers, Experimental Israeli Breathalyzer Technology Picks up COVID-19

Having nasopharyngeal swabs stuck into your nose and throat for testing for the SARS-CoV-2 virus that causes the new coronavirus is not a pleasant experience. The sample is analyzed for SARS-CoV-2 RNA by the reverse-transcription polymerase chain reaction (RT-PCR). But now, Israeli researchers reporting in the journal ACS Nano have developed a prototype device that non-invasively detected COVID-19 in the exhaled breath of infected patients – like a “breathalyzer” test for drives who have drunk excessive amounts of alcohol.

In addition to being uncomfortable, the current gold standard for COVID-19 testing requires RT-PCR, a time-consuming lab procedure. Because of backlogs, obtaining a result can take several days. To reduce transmission and mortality rates, healthcare systems need quick, inexpensive and easy-to-use tests.

Epidemiological data show that the COVID-19 pandemic propagates through “local community transmission.” This means that the spread of infection cannot be accurately traced back to a source. There is a need for a non-invasive, rapid, inexpensive testing method to screen COVID-19 positive individuals – especially pre-symptomatic or asymptomatic carriers. Such a test could significantly reduce the rate of transmission – saving lives.

Prof. Hossam Haick and Dr. Yoav Broza of the Faculty of Chemical Engineering and Russell Berrie Nanotechnology Institute of the Technion-Israel Institute of Technology in Haifa, in collaboration with researchers from Wuhan, China, wanted to develop a nanomaterial-based sensor that could detect COVID-19 in exhaled breath. Previous studies have shown that viruses and the cells they infect emit volatile organic compounds (VOCs) that can be exhaled in the breath.

The researchers made an array of gold nanoparticles linked to molecules that are sensitive to various VOCs. When VOCs interact with the molecules on a nanoparticle, the electrical resistance changes. The researchers trained the sensor to detect COVID-19 by using machine learning to compare the pattern of electrical resistance signals obtained from the breath of 49 confirmed COVID-19 patients with those from 58 healthy controls and 33 non-COVID lung infection patients in Wuhan, where COVICD-19 began.

Each study participant blew into the device for two to three seconds from a very short distance. Once machine learning identified a potential COVID-19 signature, the team tested the accuracy of the device on a subset of participants. In the test set, the device showed 76% accuracy in distinguishing COVID-19 cases from controls and 95% accuracy in discriminating COVID-19 cases from lung infections. The sensor could also distinguish, with 88% accuracy, between sick and recovered COVID-19 patients. Although the test needs to be validated in more patients, the researchers say it could be very useful for screening large populations to determine which individuals need further testing.

Haick’s pre-screening diagnostic system could offer a screening solution that can be performed at home or point-of-care facilities, greatly reducing unneeded confirmatory tests and reducing the burden on hospitals. Importantly, the artificial intelligence of the device can be modified and applied to any other infectious diseases.


The technology, which will be developed for the market by the company Nanose Medical, thus has the potential to serve as a monitoring and epidemic control tool.



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