Development and characterization of electronic noses for the rapid detection of COVID-19 in exhaled breath – COVINose

Early, easy and rapid diagnosis of coronavirus disease 2019 (COVID-19) is of the utmost importance but remains challenging. Breath analysis is an innovative, non-invasive, real-time, point-of-care technique for detecting volatile organic compounds (VOCs) in expired breath with potential for use in diagnosis and large-scale screening. Our consortium has previously shown in a study with mass spectrometry breath analysis that patients with severe COVID-19 have a discriminating “breathprint”, which includes at least a set of four putatively identified VOCs. Electronic noses (eNoses) are portable devices for breath analysis consisting of sensor array and pattern recognition algorithm to generate signal patterns that are already used in clinical research. Our project is aimed at (i) providing a formal identification of the COVID-19 specific VOCs, (ii) performing an extensive investigation of the performance of the different eNoses and sensors for the detection of these VOCs to select the best sensors for COVID-19 diagnosis, using laboratory investigations and data from ongoing clinical trials, (iii) optimizing the eNaiR software for the VOC signature detection and the COVID-19 status prediction, and (iv) designing and setting-up validation clinical trials in independent patient cohorts (observational clinical trials) with the optimized sensors and analytical strategy. This project brings together a consortium of experts in analytical sciences (mass spectrometry and eNoses), data processing, clinical research in patients with severe infections and clinical research in exhaled breath analysis.