Development of Digital Biomarkers in Multiple Sclerosis: Validation Study 2

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. Focal demyelination and diffuse neurodegeneration in the gray and white matter of the brain and spinal cord lead to decreased physical and cognitive functioning and disability. Diagnosis is established by clinical assessment of persons with MS (PwMS), including taking their history and neurologic examination, in combination with imaging and body fluid assessments. Treatment decisions in MS are based on continuous monitoring of MS disease activity and progression through clinical and imaging assessments, while the role of body fluid assessments is not yet universally established. The predictive and prognostic value of these currently used assessments to individualize treatment decisions is still very limited. New and more reliable measures are needed, especially indicators of disease progression, which allow to personalize therapies and care. With the digitization of healthcare, new opportunities are emerging to provide quasi-continuous and granular health status measurements as digital measures. Such digital measures may allow to monitor MS disease activity and progression more informatively than the only episodical traditional assessments. Digital health technologies allow to remotely capture dynamic fluctuating functions and symptoms in real world settings with minimal disruption of patients' life and usual care. The investigators developed the dreaMS software program that includes app-based interactions with the patients, patient-reported information via surveys, and continuous monitoring through sensors. In a previous study (NCT04413032), which evaluated the feasibility and acceptance of using our dreaMS software program, we identified digital biomarkers (DB) that are relevant for PwMS. These DB are evaluated and validated in an ongoing study including a larger population of PwMS in Switzerland (NCT05009160). This international, observational study aims to evaluate and validate the generalizability of these DB across different languages and cultural settings to provide DB that are helpful for patient care, research, and regulatory decisions. Beyond this, the processes and data structures created for this study are intended to establish a collaborative research platform for subsequent studies, including pragmatic trials, promoting new long-term international academic collaborations.