The ARCADIA arthritis remission study has been awarded £3 million in funding from Arthritis UK, bringing together leading centres across the UK and Europe to address a key challenge in inflammatory arthritis: how to accurately define when remission has truly been achieved.
Running from November 2025 to October 2030, the ARCADIA consortium will focus on understanding remission at a biological level, with the aim of supporting safer treatment decisions and, ultimately, long-term drug-free remission for people living with arthritis.
Why this research matters
A central strength of the ARCADIA study is its ability to include children and young people alongside adults. This is made possible through the infrastructure developed within the TRICIA network, including the MAPJAG observational study, which has established safe and acceptable approaches to collecting synovial tissue in children, alongside standardised protocols and well-characterised patient cohorts.
Until recently, studies of remission have relied largely on adult data, with limited insight into joint biology in children. MAPJAG has begun to address this gap, enabling ARCADIA to incorporate paediatric tissue data and explore how remission differs across the life course.
At present, remission is assessed using clinical examination and blood tests, which cannot distinguish between true absence of disease and disease that is suppressed but still present. This uncertainty means that many patients experience relapse after stopping treatment.
The ARCADIA arthritis remission study aims to move beyond this by focusing on “tissue remission”, using detailed analysis of joint samples to determine whether the disease has truly resolved.
Building on MAPJAG and TRICIA
ARCADIA builds directly on the foundations laid by MAPJAG and the TRICIA network, extending tissue-based research into a larger, multi-centre programme. By combining data from children and adults, the consortium aims to develop a more accurate and biologically grounded definition of remission.
As more tissue data are generated and analysed, this work will support the development of tools to predict relapse and guide treatment decisions, helping to ensure that the right patients can safely reduce or stop medication at the right time.