Multiple sclerosis (MS) treatments have advanced substantially, yet selecting the most effective therapy and preventing long-term progression remain challenging because of the disease's heterogeneity and variable treatment responses. Current drugs mainly target relapses and inflammation, while only partially protecting against neurodegeneration. Identifying predictive and prognostic biomarkers and improving monitoring are key to more personalized, evidence-based MS care.
Clinnova-MS, part of the Clinnova program, is a prospective, observational cohort designed to explore objective markers of disease activity (progression or relapses) and treatment outcomes using clinical, imaging, molecular, digital, and patient-reported data. Artificial intelligence and data science will be applied to integrate information from sources such as MRI, deep molecular phenotyping, exposome data, Patient Reported Outcome Measures (PROMs)/Patient-Reported Experience Measures (PREMs), and connected devices.
Up to 800 participants with early MS, transitioning to progressive disease, or undergoing treatment change will be enrolled in France, Switzerland, Germany, and Luxembourg (about 100 at Centre Hospitalier du Luxembourg (CHL)). Participants will provide clinical data, biological samples (blood mandatory; other specimens optional), imaging (as per standard care), and digital health information. They will be followed for up to five years, with visits at baseline, 6 months (optional), 12 months, annual follow-up, and unscheduled visits if new symptoms or relapses occur.
