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Project Topic
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Myasthenia Gravis (MG) is a prototypic autoimmune disease causing muscle weakness and fatigability, mostly treated by chronic immunosuppressive (IS) therapy. MG clinical heterogeneity, fluctuating symptoms with unpredictable disease course, and inter-individual variation in response to treatments, including conventional IS and the emerging biological drugs, highlight the need to adopt safe, predictive and preventive personalised medicine (PM) strategies, still lacking in MG. The MG-PerMed project will employ an interdisciplinary approach, combining pre-clinical, clinical, artificial intelligence (AI) and bioethic research, to achieve PM for MG. Pharmacogenetic, pharmaco-miR and serological biomarkers associated with clinical features and response to therapies will be validated in three different MG populations (Italian, French and Israeli). Integration of biological and real-world clinical data by AI will lead to the development of a clinical decision support tool (MG-CDST), to guide clinicians in the choice of the best therapeutic program for individual patients/patient subgroups, enabling both early prediction of the optimal therapy and on-treatment disease monitoring to prevent MG symptom worsening and crisis. For the first time, a MG-CDST-based PM approach will be prospectively validated. The project outcomes promise to significantly change the MG treatment flow-chart, shifting from the “one-fits-all” approach to personalised care. MG-CDST adoption into the clinical practice should prospectively lead to: treatment failure prevention, prevention of IS drug-related adverse events, prevention of disease exacerbations, and in turn an improved MG patient compliance to treatment and a better quality of life. MG-dedicated Apps will allow patient/caregiver involvement in therapeutic decisions. Data dissemination will promote PM adoption in consensus guidelines for MG, and potentially other autoimmune diseases in which current treatment is chronic immunosuppression.
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