Big Data and Artificial Intelligence-Based Research Improves Understanding of Systemic Vasculitis

Researchers from the School of Medicine and the ADAPT Centre in the School of Informatics and Statistics at Trinity College Dublin have made a significant breakthrough in vasculitis research, in collaboration with researchers from Lund University. Their findings, recently published in The Lancet Rheumatologyprovide new insights into the diagnosis and treatment of systemic vasculitis, a group of rare and complex autoimmune diseases.

The study, part of the FAIRVASC project, leverages advanced artificial intelligence (AI) and big data techniques to address critical challenges in the diagnosis and treatment of systemic vasculitis. FAIRVASC connects vasculitis patient registries across Europe, enabling seamless data sharing and advanced analytics to advance research and improve patient care.

By focusing on anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis, the research introduces a novel approach to classifying this disease using a federated dataset ten times larger than previous studies.

Access to this much larger dataset allowed for more detailed analysis, revealing previously unidentified disease groups. This new classification method offers more accurate predictions of outcomes such as overall survival and kidney health, paving the way for more personalized treatment strategies that can significantly improve patient care.

Professor Mark Little, Professor of Nephrology and Consultant Nephrologist at Trinity College Dublin and Tallaght and Beaumont Hospitals, said: “Our research shows that by harnessing advanced AI systems and large datasets, we can uncover new patterns in this rare autoimmune disease that impact the likelihood of adverse events. This allows us to target potentially toxic therapies to those most likely to benefit from them.

“Such progress has only been possible through a multidisciplinary approach and the direct involvement of patients with lived experience of the disease, and this collaborative project has successfully brought together experts in medicine, computer science and statistics.”

Professor Declan O’Sullivan, ADAPT Principal Investigator and Professor of Computer Science at Trinity, said: “I am delighted to see that the research we are focusing on in our group, knowledge graphs for data integration, is having an impact on the advancement of medical research. In particular here, the federation of patient registries for rare diseases.”

The study highlights the transformative potential of AI in medical research, particularly in addressing the complexities of rare diseases, where it was previously impossible to generate cohorts large enough to enable meaningful research.

By enabling more accurate identification of disease patterns, AI may revolutionize the way clinicians approach diagnosis and treatment, offering hope for better outcomes not only for patients with vasculitis, but also for those suffering from other rare and challenging diseases.

This research provides a model for using advanced technologies to address similar challenges in the broader field of rare diseases, potentially leading to breakthroughs that could benefit countless patients around the world.