Immune-evasive beta cells in Type 1 diabetes: innovations in genetic engineering, biomaterials, and computational modeling

Abstract

Type 1 diabetes (T1D) is characterized by the autoimmune destruction of pancreatic beta cells, resulting in lifelong insulin therapy that falls short of a true cure. Beta cell replacement therapies hold immense potential to restore natural insulin production, but they face significant hurdles such as immune rejection, limited donor availability, and long-term graft survival. In this review, we explore cutting-edge advances in genetic engineering, biomaterials, and machine learning approaches designed to overcome these barriers and enhance the clinical applicability of beta cell therapies. We highlight recent innovations in genetic editing techniques, particularly CRISPR/Cas9-based strategies, aimed at generating hypoimmune beta cells capable of evading immune detection. Additionally, we discuss novel biomaterial encapsulation systems, engineered at nano-, micro-, and macro-scales, which provide physical and biochemical protection, promote graft integration, and survival. We mention that recent advances in machine learning and computational modeling also play a crucial role in optimizing therapeutic outcomes, predicting clinical responses, and facilitating personalized treatment approaches. We also critically evaluate ongoing clinical trials, providing insights into the current translational landscape and highlighting both successes and remaining challenges. Finally, we propose future directions, emphasizing integrated approaches that combine genetic, biomaterial, and computational innovations to achieve durable, scalable, and immunologically tolerant beta cell replacement therapies for T1D.