Predict is participating, alongside the University of Bari and the University of Salento, in the Endoscope project, funded under the “D3-4Health” cascade calls promoted by Sapienza University of Rome.
D3-4Health (Digital Driven Diagnostics, Prognostics and Therapeutics for Sustainable Healthcare) is an initiative involving 28 public and private entities, with the aim of developing advanced digital technologies for healthcare and contributing to the creation of a digital and biological twin.
Within this framework, the Endoscope project will carry out a multicenter comparative study to validate breath analysis as an innovative tool for the early diagnosis of colorectal cancer. Thanks to Mistral technologies, it will be possible to explore a highly selective, non-invasive, and easy-to-apply screening method.
Funded by the Italian Ministry of University and Research through the National Plan for Complementary Investments (PNC) to the NRRP (PNRR), the Endoscope project will run for 12 months and involve the collection of 1,000 exhaled breath samples from individuals who tested positive in FIT/FOBT screenings across the Puglia region.
Of these, 300 samples will be analyzed using the Mistral Sampler, correlating the results with colonoscopy data to identify a specific metabolic pattern using machine learning algorithms.
The Importance of Early Diagnosis
Colorectal cancer is the third most common cancer among men and the second among women, with over 50,000 new cases in 2023 (+5% compared to 2022 – Source: Cancer Statistics in Italy 2023). In this context, innovative diagnostic tools like breath analysis can offer a viable alternative:
The Endoscope project aims to optimize screening pathways, offering advanced solutions for the benefit of both patients and the National Health System. Additionally, breath analysis will contribute to the development of the digital and biological twin, enhancing personalized and precision medicine.
Thanks to its expertise and Mistral technologies, Predict continues to work toward making early diagnosis more accessible, effective, and innovative.
