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Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease that remains a leading cause of non-traumatic disability in young adults. The urgency to advance MS research has never been greater, as global incidence and prevalence are rising, and patients continue to face delays in diagnosis, incomplete response to therapies, and limited options for progressive disease. Recent progress in defining disease stages, understanding sex- and gender-related influences, and identifying modifiable risk factors emphasizes the critical need for timely translation of scientific insights into precision medicine approaches. While FDA-approved therapies have substantially altered the course of relapsing forms of MS, therapeutic gaps in progressive disease highlight a pressing unmet clinical challenge. Advances in neuroimaging, digital biomarkers, and patient-centered monitoring now converge with the rapid growth of artificial intelligence (AI)-based tools, creating an unprecedented opportunity to refine diagnostic precision, predict progression, and personalize interventions. The integration of these technologies offers transformative potential to move beyond conventional monitoring toward predictive and adaptive care. This review synthesizes current knowledge of MS pathophysiology, immunity, and therapy, while underscoring the immediate relevance of harnessing AI and digital innovations to address current challenges and shape the future of precision medicine.
Pithakumar et al. (Thu,) studied this question.