Recent Prospects for the Diagnosis and Management of Multiple Sclerosis: A Succinct Review
TL;DR
This review explores the pathophysiology and current diagnostic landscape of MS, and highlights the role of AI in nanomedicine and neurology, emphasising its potential to enhance personalised treatment strategies and real-time monitoring.
Abstract
Multiple sclerosis (MS) is a chronic autoimmune neurodegenerative disorder characterised by inflammation, demyelination, and progressive neurological dysfunction within the central nervous system. Current diagnostic approaches, including magnetic resonance imaging, cerebrospinal fluid analysis, and evoked potentials, provide valuable insights but remain limited by insufficient specificity in early detection. In parallel, therapeutic strategies are constrained by the blood–brain barrier (BBB), which restricts efficient drug delivery to affected neural tissues. Recent advances in nanotechnology have introduced theranostic nanocarriers as a promising platform that integrates targeted drug delivery with real-time disease monitoring. Additionally, the integration of artificial intelligence (AI) has accelerated the optimisation of nanoparticle design, improved diagnostic accuracy through advanced imaging analysis, and enabled predictive modelling of disease progression. This review explores the pathophysiology and current diagnostic landscape of MS, and highlights the role of AI in nanomedicine and neurology, emphasising its potential to enhance personalised treatment strategies and real-time monitoring.