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iPROLEPSIS: PSORIATIC ARTHRITIS INFLAMMATION EXPLAINED THROUGH MULTI-SOURCE DATA ANALYSIS GUIDING A NOVEL PERSONALISED DIGITAL CARE ECOSYSTEM

Project description

DEENESFRITPL

Digitally combatting psoriatic arthritis

Approximately 0.5 % of the global population suffers from psoriatic arthritis (PsA), a chronic and progressive inflammatory condition. About one third of psoriasis patients will develop PsA. The mechanisms behind the transformation to PsA are unknown, making an early diagnosis and initiation of appropriate treatment challenging. PsA is still a chronic condition with treatment aimed at achieving disease remission. Most patients will however experience disease exacerbations. The EU-funded iPROLEPSIS project aims to improve early detection of PsA symptoms and reduce diagnostic delay. It will use advanced AI technology applied to multi-sourced big data to dynamically capture and analyse patients’ own data, ensuring more patient-centred care and directly contributing to quality of life improvement in PsA.

Objective

Psoriatic Arthritis (PsA) is a chronic, progressive, inflammatory disease affecting 1-2% of the general population, while manifesting in up to 30% of people with psoriasis (PsO). The transition from health to PsA is currently untraceable; diagnosis of early PsA is challenging even in PsO patients. Untimely diagnosis is common and contributes to early deterioration of quality of life, also increasing the burden of the multiple comorbidities associated with PsA. In this vein, iPROLEPSIS aspires to shed light upon the health-to-PsA transition with a comprehensive multiscale/multifactorial PsA model employing novel trustworthy AI-based analysis of multisource and heterogenous (i.a. in-depth health, environmental, genetic, behavioural) data, digital phenotyping of inflammatory symptoms with emphasis on tracking of motor manifestations using smart devices and wearables, novel optoacoustic imaging-based markers of PsA in the skin and joints, and investigation of the role of mast cells in the PsA transition, to identify key drivers of the disease and support personalized models for PsA risk/progression prediction and monitoring as well as associated inflammation detection and severity assessment. To ultimately advance PsA diagnosis and care, the models will be translated into a digital health ecosystem comprising dependable tools for supporting healthcare professionals in disease screening, monitoring and treatment via quantitative, explainable evidence, and empowering people with/at risk of PsA with tailored insights and preventive interventions based on actionable factors for educated health management. The project will steer its research and development efforts following a trustworthy framework for ethical, lawful, and robust AI, and a user-centered co-creation approach based on constant involvement of key stakeholders during the design, development, and testing of the digital health ecosystem, securing successful integration of the latter in the continuum of care.

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Call for proposal

HORIZON-HLTH-2022-STAYHLTH-02

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

ARISTOTELIO PANEPISTIMIO THESSALONIKIS
Net EU contribution
€ 1 050 000,00
Address
KEDEA BUILDING, TRITIS SEPTEMVRIOU, ARISTOTLE UNIVERSITY CAMPUS
546 36 THESSALONIKI
Greece

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Region
Βόρεια Ελλάδα Κεντρική Μακεδονία Θεσσαλονίκη
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 1 050 000,00

Participants (13)

Partners (1)

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Last update: 20 January 2023

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Permalink: https://cordis.europa.eu/project/id/101095697

European Union, 2024