Objective
The analysis of volatile organic compounds (VOCs) in exhaled breath with nano sensors has great potential to transform healthcare, with accurate, inexpensive, real-time diagnostics. However, attempts to implement this strategy have failed to reach clinical deployment. Firstly, many efforts try to identify the complex mixture of VOCs associated with disease, which is a long and expensive process. Secondly, commercially available sensors require high operating temperatures and have low sensitivity to breath VOCs. NaNose Medical has overcome these limitations through DiaNose, an easy to use, hand-held diagnostics device with potential applicability in >20 different diseases. Instead of identifying individual VOCs, DiaNose deploys an array of patented cross-reactive sensors delivering a chemical signature of breath that can be classified as healthy or diseased through artificial intelligence. Our initial alpha prototype focuses on a key clinical indication: Non-Alcoholic Fatty Liver Disease (NAFLD): with a global prevalence of 30%, it is the leading cause of liver related morbidity, generating an annual burden in Europe of > 35 billion and a further 200 billion of societal costs. Crucially, NAFLD diagnostics present key limitations: liver biopsies are expensive, invasive and subject to sampling error, and non-invasive alternatives lack precision, are operator-dependent, and require expert interpretation. DiaNose will fill this gap, aiming to achieve a diagnostic accuracy of >90% at <50/test. Lab testing of our alpha prototype has shown high accuracy (88%) with NAFLD models. With the ReLiV project, we will develop an advanced beta prototype that will be validated in clinical settings across different locations. This will bring DiaNose one step closer to commercialization, providing a truly cost-effective, point-of-care detection and monitoring device capable of improving patient outcomes and alleviating the economic burden generated by the growing NAFLD pandemic.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
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Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC - HORIZON EIC GrantsCoordinator
4250574 Netanya
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.