29 October is World Psoriasis Day, a yearly reminder of the 125 million people worldwide who face the challenges and frustrations of psoriasis and psoriatic arthritis (PsA). This day is dedicated to raising awareness about these chronic conditions, promoting understanding and the need for ongoing research and support.
On this occasion, HaDEA has spoken with Prof. Leontios Hadjileontiadis, the coordinator of the iPROLEPSIS project.
How is your project contributing to the early detection, diagnosis and treatment of psoriatic arthritis (PsA)?
The iPROLEPSIS project is a Horizon Europe research initiative that aims to transform how psoriatic arthritis (PsA) is managed in medical settings by using artificial intelligence (AI) and different types of biological data.
PsA is a chronic inflammatory disease that often goes undiagnosed in its early stages, leading to irreversible joint damage and reduced quality of life. iPROLEPSIS addresses this challenge by developing a robust, predictive framework that enables:
- Early identification of individuals at risk for PsA, especially among psoriasis patients who may not yet show joint symptoms;
- Personalised diagnostic pathways using AI-enhanced analysis of clinical, genetic, and imaging data;
- Tailored treatment strategies based on predictive models that anticipate disease progression and therapeutic response.
The project brings together a multidisciplinary consortium of clinicians, data scientists, researchers, industry, and patient representatives across Europe. It integrates clinical registries and novel digital biomarkers to construct comprehensive patient profiles. This approach supports precision medicine by enabling early detection and personalised interventions for individuals at risk of psoriatic arthritis.
How has using AI-based technology in your project helped to improve the lives of those with PsA?
The iPROLEPSIS project uses advanced artificial intelligence applied to big data to transform the early detection and diagnosis of psoriatic arthritis (PsA). It integrates data from clinical registries, patient feedback, and novel digital biomarkers to build predictive models that identify individuals at risk of developing PsA. This is particularly helpful for psoriasis patients who haven’t developed musculoskeletal symptoms yet. The project develops personalised representations for each patient, supporting doctors’ timely and targeted interventions. Unlike traditional diagnostic pathways, which often involve late referrals and subjective assessments, iPROLEPSIS uses data to allow for more precise and faster clinical decision-making and treatment. The project’s approach improves individual outcomes and generates population-level insights that can inform broader healthcare strategies. By bridging dermatology and rheumatology and promoting personalised care, iPROLEPSIS sets a new standard for managing PsA across Europe.