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Advanced personalised, multi-scale computer models preventing OsteoArthritis

Project description

Holistic insight into osteoarthritis

Osteoarthritis (OA) is a common degenerative joint disease that primarily affects the elderly but can also impact younger individuals and athletes. OA causes joint pain, limits mobility, and reduces independence and overall quality of life. While various risk factors have been implicated in OA development, there is a need to integrate patient-specific information at the cellular, tissue, organ, and body levels. The EU-funded OACTIVE project aims to address this gap by adopting a holistic approach that combines patient-specific data with information from biomarkers, behaviour modelling, and environmental factors. Researchers aim to develop personalised interventions for delaying the onset and slowing down the progression of OA also with the use of augmented reality for increased patient motivation and engagement.

Objective

Osteoarthritis (OA) is a degenerative disease of the articular cartilage and the most common form of arthritis that causes joint pain, mobility limitation and, thus, reduces independence and overall quality of life. Although the usual population associated with the condition is the elderly (65 years old ranges from 12- 30%), who are mostly inactive, athletes and younger individuals are also susceptible. Whilst the available data have implicated the role of the various modifiable or non-modifiable risk factors in the development and progression of OA, no study has conclusively explored the interaction and integration of other information sets in a patient-specific manner. The current OACTIVE project intents to make a significant leap forward adopting a multi-scale holistic approach where patient-specific information from various levels, including cell, tissue, organ and whole body will be integrated and combined with information from other sources such as biochemical/inflammatory biomarkers, behaviour modeling and social/environmental risk factors to generate robust predictors for new personalised interventions for delaying onset and slowing down progression of OA. OACTIVE targets to patient-specific OA prediction and interventions by using a combination of mechanistic, phenomenological computational models, simulations and big data analytics. Once constructed, these models will be used to simulate and predict optimal treatments, better diagnostics, and improved patient outcomes. Overcoming the limitation of the current treatment interventions, Augmented Reality empowered interventions will be developed in a personalised framework allowing patients experience the treatment as more enjoyable, resulting in greater motivation, engagement, and training adherence. OACTIVE’s mission is to improve healthcare by transforming and accelerating the OA diagnosis and prediction based on a more comprehensive understanding of disease pathophysiology, dynamics, and patient outcomes.

Call for proposal

H2020-SC1-2016-2017

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Sub call

H2020-SC1-2017-CNECT-2

Coordinator

EDEX - EDUCATIONAL EXCELLENCE CORPORATION LIMITED
Net EU contribution
€ 521 000,00
Address
Makedonitisas avenue 46
1700 Nicosia
Cyprus

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Region
Κύπρος Κύπρος Κύπρος
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 521 000,00

Participants (12)