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Multivariate optoacoustic sensor for longitudinal diabetes monitoring

Project description

Non-invasive optoacoustic technology for diabetes monitoring

Diabetes mellitus, a growing health concern, requires solutions for early detection and continuous management. The EIC-funded MOSAIC project aims to miniaturise non-invasive optoacoustic technology for diabetes monitoring. By integrating optoacoustic sensing with novel explainable artificial intelligence (xAI), the project will use advancements in optoelectronic miniaturisation to access the skin’s dermal microvasculature and detect diabetes-related biomarkers. This approach offers a fast and reliable sensor that is non-invasive and suitable for long-term monitoring. The technology enables early detection, facilitates treatment monitoring, and improves life expectancy and quality of life. By overcoming barriers such as non-invasiveness, multi-biomarker detection, ease of integration into daily routines, and fully automated data analytics, MOSAIC holds the potential to reduce healthcare costs while improving patient outcomes.

Objective

MOSAIC will radically miniaturize non-invasive optoacoustic technology and make it portable by coupling optoacoustic sensing to novel explainable artificial Intelligence (xAI) to monitor a major health threat in the 21st century: Diabetes Mellitus. MOSAIC is based on recent advances on optoelectronic miniaturization and uses the skin as a window to dermal microvasculature and resolves a large number of biomarkers associated with diabetes. The technology is offered as a fast sensor that is inexpensive and reliable, entirely non-invasive and portable and supported by elaborate quality control monitoring so that it can be employed for long-term patient monitoring. Based on proof-of-concept human measurements, xAI will further independently characterize the predictive power of each biomarker and other clinical measurements to improve accuracy for continuous grading of disease status.
Impact: With 537 million diabetics and a large at-risk population, MOSAIC potentially relates to 2B people and aims to reach more individuals than is practical to screen in medical facilities. It offers early diabetes detection for early interventions, as well as treatment monitoring, improving life expectancy, quality of life and reducing healthcare costs.
Innovation: The sensor addresses 5 barriers to successful adoption: it is non-invasive, senses highly multiplexed biomarkers, it can be easily integrated into daily routine, and uses fully automated data-analytics.
MOSAIC synergistically integrates 3 teams on sensor developments, data analytics and xAI, one preclinical and one clinical team for sensor validation in mice and humans, respectively, and an SME for exploitation.

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Programme(s)

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Topic(s)

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HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-EIC-2024-PATHFINDEROPEN-01

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Coordinator

HELMHOLTZ ZENTRUM MUENCHEN DEUTSCHES FORSCHUNGSZENTRUM FUER GESUNDHEIT UND UMWELT GMBH
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.

€ 1 078 546,25
Address
INGOLSTADTER LANDSTRASSE 1
85764 Neuherberg
Germany

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Region
Bayern Oberbayern München, Landkreis
Activity type
Research Organisations
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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.

€ 1 078 546,25

Participants (5)

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