SOURCE-LINKED INTELLIGENCE

Real time Liver disease early diagnosis through exhaled Volatile Organic Compounds sensing

CORDIS · observation · Publication date unknown

es. 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 close

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recordType

award

status

SIGNED

region

EU

value

2499875

unit

EUR