PersonAlisation of RelApse risk in autoimmune DISEase "PARADISE"

Autoimmune disease affects 10% of adults, most of whom are women, and two of the top five medications with the highest cost globally are used to maintain these recurring conditions in remission. These medications act by suppressing the immune system, leaving the patient exposed to severe infection and at risk of cancer. Affected individuals receive standard treatment regimens for long periods of time, even though, in some cases, the autoimmune response may no longer be detectable. 

The general requirement for these medications, and their side effects, has been raised as a key target for research by the PARADISE consortium patient groups. Therefore, we aim to develop and validate a deployable personalised predictive tool that will accurately define the individual’s degree of immune system activation so that the medication dose can be tailored and, in some cases, stopped safely. 

We use systemic vasculitis as an archetypal autoimmune disease, integrating clinical, innovative biomarker and smartphone app-derived patient wellbeing data through a novel semantic web platform to inform predictive algorithms that will underpin a physician-facing tool. Such artificial intelligence (AI) applications are coming under intense scrutiny in the EU, so we will co-develop an “AI transparency notice” with the patient arm of the European Reference Network for immune disorders through a series of multi-stakeholder workshops, which will make explicit and explainable the full provenance of the PARADISE tool clinical outputs.

Award Date
17 October 2022
Award Value
Principal Investigator
Professor Mark Little
Host Institution
Trinity College Dublin
ERA-NET Cofund for Personalised Medicine