Duration: January 01, 2024 – June 30, 2027 | 42 months
Funding: EUR 5 Mio.
Coordinator: University of Limerick
Consortium of 11 partners from 6 countries | 5 SMEs
A molecular-level approach is required to accurately assess, diagnose, treat, and understand diseases such as cancers, which originate from the disruption of cells.
Current solutions come from the field of photonics, the area of physics dealing with the use of radiant energy such as light, the basic element of which is the photon. Yet today’s photonic real-time imaging solutions can only provide morphological analysis and significantly restrict early detection of cancer and therapy selection and testing.
Breakthrough photonic technologies are needed to perform rapid, standardised ex vivo, in vivo or in vitro diagnosis at high speed and sensitivity – diagnosis performed either on living tissue outside or within the human body or on any material in a test tube.
This can be achieved by employing extended spectral analysis for an accurate reflection of cellular life cycles and diseases processes, thereby enhancing specificity.
uCAIR will develop this breakthrough technology.
We will develop a multimodal and coherent Raman platform for modules optimisation and benchmarking – uCAIR1.
In the end, we will build an optimized platform: the uCAIR2 prototype, a compact microscopy platform designed for fast and accurate diagnostics.
We will develop a Raman microspectroscopy platform to enable increased quality and speed of diagnosis of human tissue, for instance during procedures of endomicroscopy. Endomicroscopy makes it possible to obtain microscopic images of the examined area as part of conventional endoscopy.
Our goal is to achieve an ultra-fast coherent Raman scattering through the development of an advanced laser technology covering a broad spectral and temporal range.
Named after the Indian physicist C.V. Raman, Raman spectroscopy is a technique used to analyze the vibrational modes of molecules by measuring the scattered light resulting from interactions with a laser beam. It is often used to investigate material properties, for example of pigments in art objects.
It has proven as an effective tool in biophotonics, the application of photonics in biology. Photonics being the field of physics that deals with the use of radiant energy, e.g. light, the basic element of which is the photon.
We will integrate an AI expert system to speed up signal recording without reducing overall accuracy for automatic classification of molecular Raman signatures.
Our AI expert system will undergo a rigorous training using robust datasets derived from a series of measurements conducted on specimens with progressively increasing complexity. A quality metric will be developed measuring the fit between uCAIR recordings and expected Raman signatures.
Coordinator - University of Limerick
Dr. Christophe Silien
