Abstract
Mesenchymal Stromal Cells (MSCs) are increasingly recognized as promising candidates for treating Systemic Lupus Erythematosus (SLE) due to their immunomodulatory and regenerative properties. However, their therapeutic efficacy remains inconsistent, largely due to the heterogeneity of MSC origins, culture conditions, cell quality, host immune interactions, and the influence of immunosuppressive treatments. Artificial Intelligence (AI) offers powerful tools to address these challenges by optimising MSC modification and application. This review explores how AI can identify optimal genetic and epigenetic targets, predict MSC behaviour under different environmental and priming conditions, and design personalise therapies tailored to individual patients. Moreover, AI enables the analysis of extensive datasets to refine dosing strategies and improve the integration of MSC therapy with immunosuppressants. By enhancing the precision, consistency, and personalisation of MSC-based interventions, AI has the potential to significantly improve therapeutic outcomes in SLE, advancing the field toward more effective and patient-centred autoimmune disease management.