Current MS care relies on short, scheduled outpatient appointments that do not consider patients in their own environments and fluctuations in symptoms. Patients inadvertently become passive partners in their own care.
We now have the potential to revolutionise MS monitoring by gathering day-to-day patient data and detecting disease progression via smartphone applications. This allows patients to play an active role in their disease journey and provides an opportunity for early intervention to minimise disability. Currently, these mobile applications lack validation and real-world data. Once validated, these digital biomarkers would pave the way for more efficient drug trials in progressive MS.
This study aims to address these needs by 1) evaluating the feasibility, reliability and validity of app-based self-monitoring tools, 2) identifying mobile apps that can detect MS changes over time and predict the progression of disease, 3) integrating mobile app data with clinical and imaging data to develop predictive models of treatment failure.
This doctoral work will be based on prospective data from ACTIVE MS. This is a multi-centre cohort study that uses three purpose-designed apps to assess multiple neurological domains including cognition, cerebellar function, mood, mobility and fine motor skills. The study will leverage the current MSBase registry infrastructure, providing a ready-made data integration system.
Updated: 14 February, 2022
Laboratory research that investigates scientific theories behind the possible causes, disease progression, ways to diagnose and better treat MS.
Research that builds on fundamental scientific research to develop new therapies, medical procedures or diagnostics and advances it closer to the clinic.
Clinical research is the culmination of fundamental and translational research turning those research discoveries into treatments and interventions for people with MS.