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Morphomolecular diagnostics of head and neck cancer

Project description

Multimodal endoscopy for early cancer detection

Head and neck cancers contribute significantly to global mortality rates, with poor survival when diagnosis occurs at advanced stages. Early detection offers the most effective strategy to improve outcomes. However, endoscopic detection mostly relies on optical contrast between neoplastic and normal mucosa and uses enhanced light or fluorescence, which offer limited sensitivity. The ERC-funded LEAN project builds on previous work to address this issue and develop a new endoscopic tool. Researchers aim to advance a novel endoscopic probe that integrates Raman spectroscopy and optical coherence tomography. This combination delivers molecular specificity and high-resolution imaging for real-time, non-invasive diagnosis and staging. The project will prepare this innovative tool for clinical translation and cancer diagnosis.

Objective

Head and neck cancers (HNC) represent a significant global health burden and have poor survival rates when diagnosed at advanced stages. Early detection at precancerous or early cancer stages is the most effective strategy to reduce mortality, improve patient outcomes and save healthcare expenses. However, current endoscopic approaches are limited in their ability to provide accurate diagnosis, monitoring and timely intervention.
Building upon patented ERC research, the LEAN project addresses this critical clinical gap by exploring the commercial application of a ground-breaking multi-modal endoscopic platform that integrates Raman spectroscopy with optical coherence tomography (OCT) within a single miniaturised (<2.2 mm) fibre-based probe. This innovative combination harnesses the unparalleled molecular specificity of Raman spectroscopy alongside the high-resolution morphological imaging capabilities of OCT, offering clinicians a powerful new tool for real-time, non-invasive detection, grading and staging of HNC. Here we will optimise and refine the fabrication process and develop a rigorous quality and manufacturing system (QMS) design file. These advancements will ensure safety and scalable assembly for prospective clinical trials. The project will also leverage artificial intelligence (AI) to synergistically fuse Raman and OCT datasets, enabling the creation of robust algorithms capable of delivering real-time probabilistic diagnosis of precancer and cancer.
LEAN lays the groundwork for exploitation of our innovation by outlining a project that will enable translation of our device into humans to ultimately change the current clinical pathway for H&N patients. These activities pave for the for clinical trials and will provide an entry point in the broader market for label-free minimally invasive diagnostics.

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Topic(s)

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

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(opens in new window) ERC-2025-POC

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Host institution

KING'S COLLEGE LONDON
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
STRAND
WC2R 2LS London
United Kingdom

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Region
London Inner London — West Westminster
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Beneficiaries (1)

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