Abstract

Type 2 diabetes is a chronic metabolic disorder characterized by high blood sugar levels over a prolonged period. It is a significant global health issue, affecting millions of people worldwide. The traditional treatment for diabetes involves medication, lifestyle changes, and regular monitoring of blood sugar levels to decide on treatment modifications accordingly. However, recent advancements in modern technologies/techniques involving artificial intelligence (AI) and stem cell therapy have shown promising results in achieving excellent diabetes care outcomes and even remission, which was never conceivable a few decades ago. AI-driven interventions enable the development of tailored treatment plans, leveraging patient data to optimize glycaemic control and predict complications. Whole Body Digital Twin (WBDT) models provide holistic insights, facilitating significant rates of diabetes remission. Stem cell therapy when coupled with newer technologies has shown to be revolutionary towards this. Especially therapies targeting the mammalian Target of Rapamycin (mTOR) pathway show a great potential for regenerating damaged pancreatic beta cells and improving insulin production. However, challenges such as data privacy concerns with AI models utilising big data and ethical considerations in stem cell research persist; there is a need for regulatory norms towards this especially with the availability of these advanced treatment modalities, which would be the face of medical science in the coming years. For sure, combining AI and stem cell-based therapies present an innovative approach to enhance diabetes management, enabling the identification of suitable candidates for treatment and predicting treatment success. Diabetes was considered a lifelong disease that carried a huge burden of secondary organ complications over a period. This manuscript explores the potential of these innovative approaches in treating diabetes and discusses the scientific evidence supporting their utility.

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