Objective
The CHARM project aims to radically transform the cancer diagnosing process and bring the emerging field of digital histopathology to the next level, introducing a novel technology for tissue analysis, capable to measure the molecular composition of the patient tissue samples and to recognize and classify the tumor in a completely label/stain-free way. The instrument, integrated with artificial intelligence (AI), will offer to histopathologists a reliable, fast and low-cost Clinical Decision Support System (CDSS) for cancer diagnosis and personalized cancer therapy. We will develop a Class C, (IVDR, In-Vitro Diagnostic Regulation) medical device consisting of a turnkey low-cost broadband Coherent Raman Scattering (CRS) microscope (enabled by our patented graphene-based fiber laser technology), named the Chemometric Pathology System (CPS), integrating an AI module based on deep learning, statistics and machine learning. The CPS will be capable of automatically analyzing unstained tissues, providing fast and accurate tumour identification (differentiating normal vs neoplastic tissues) with accuracy >98% and final tumour diagnosis prediction (differentiating and grading histologic subtypes) with accuracy >90%, thus offering to the histopathologist a decision tree compatible with existing clinical protocols but with biomolecular-based objectivity and reduced time to result (TRL6). We will develop a robust business case for the application and ensure the project continuation to higher TRLs and the final market entrance. This proposal builds on the results of the ERC POC project GSYNCOR.
Fields of science
- natural sciencesphysical sciencesopticsmicroscopy
- medical and health sciencesclinical medicineoncology
- medical and health scienceshealth sciencespersonalized medicine
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesphysical sciencesopticslaser physics
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Topic(s)
Funding Scheme
HORIZON-AG - HORIZON Action Grant Budget-BasedCoordinator
37126 Verona
Italy
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Participants (5)
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
33100 Udine
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
20133 Milano
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
00185 Roma
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07747 Jena
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28034 Madrid
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partners (1)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
CB2 1TN Cambridge
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