Descripción del proyecto
Lucha digital contra la artritis psoriásica
Aproximadamente el 0,5 % de la población mundial padece artritis psoriásica, una enfermedad inflamatoria crónica y progresiva. Casi un tercio de los enfermos de psoriasis desarrollarán artritis psoriásica. Se desconocen los mecanismos que subyacen a la evolución en artritis psoriásica, lo cual dificulta el diagnóstico precoz y el inicio del tratamiento adecuado. La artritis psoriásica sigue siendo una enfermedad crónica con un tratamiento dirigido a lograr la remisión de la enfermedad. No obstante, la mayoría de los pacientes conocerán exacerbaciones de la enfermedad. El equipo del proyecto iPROLEPSIS, financiado con fondos europeos, pretende mejorar la detección precoz de los síntomas de la artritis psoriásica y reducir el retraso diagnóstico. Empleará tecnología avanzada de inteligencia artificial aplicada a macrodatos de múltiples fuentes para capturar y analizar de manera dinámica los propios datos de los pacientes, garantizando así una atención más centrada en el paciente y contribuyendo directamente a la mejora de la calidad de vida en la artritis psoriásica.
Objetivo
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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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
546 36 THESSALONIKI
Grecia