Myasthenia Gravis (MG) is a prototypic autoimmune disease causing muscle weakness and fatigability, frequently treated with lifelong immunosuppressive therapy (IST). Clinical heterogeneity, unpredictable disease course, treatment refractoriness in a proportion (10-15%) of patients, IST-related adverse events, and inter-individual variation in response to both conventional IS and emerging biological drugs highlight the need to adopt more effective, preventive and safe personalised medicine (PM) strategies, still lacking in MG. The MG-PerMed project will Combine pre-clinical, clinical, artificial intelligence (AI), telemedicine and bioethics research to promote adoption of PM in MG clinical practice. Integration of biomarker with real-world clinical data from three MG populations (Italian, French and Israeli) via AI will allow the development of a clinical decision support tool (MG-CDST), whose effectiveness in guiding the choice of the best patient-centred treatment programme will be proven in an exploratory clinical study. Our findings will set the basis for a shift from the current “one-fits-all” treatment flow-chart to personalised care in MG, thus promising to significantly improve therapeutic success and MG patients’ quality of life.