Deep Learning-reinforced Engineering of Pancreatic Organoids with Micro-nano Biomaterials for Type 1 Diabetes Treatment

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PROJECT SUMMARY An estimated 1.6 million Americans are currently living with type 1 diabetes. The most common method of treating type 1 diabetes is through daily blood monitoring and insulin injections, which can affect quality of life and may result in severe health issues. Full pancreatic transplantations are a more permanent treatment option but involve invasive surgery that can lead to complications, has a high morbidity rate, and patients are required to take immunosuppressants for the rest of their lives which can be very detrimental to health. One method for diabetes treatment that has become a promising option and focus of a lot of research is islet transplantation, which is a much less invasive method but still requires patients to take immunosuppressants or risk transplantation rejection. A way to prevent the need for immunosuppressants post-transplantation is through encapsulating the islets in biomaterials which can allow nutrient exchange while mitigating immune rejection by preventing immune cell infiltration. Encapsulated islet transplantation still faces many problems including immune responses and poor islet viability post-transplantation, which may be addressed using engineering and biomaterials as proposed in this project. Aim 1 will focus on developing novel microencapsulation methods, which we hypothesize will result in lower islet cell death and lower post-transplantation immune responses in vivo. Microfluidic encapsulation of islets gives greater control over microcapsule composition and configuration than other encapsulation methods. Using this method, a biomimetic encapsulation that mimics the structure of the pancreas and uses materials in a core-and-shell design can be achieved. Implementing a label-free deep learning detection method to selectively pick islet-laden microcapsules from empty capsules on-chip to obtain a highly pure sample of islet-laden microcapsules for transplantation, may greatly improve the efficiency and minimize contamination (and associated immune response), compared to tedious manual sorting methods used in the past. Furthermore, the islets will be co-encapsulated with pancreatic stromal cells to create a biomimetic microenvironment (i.e., pancreatic organoid). The microencapsulated islets will be rigorously characterized in vitro and tested in vivo in a diabetic mouse model by monitoring blood glucose levels of the mice. Aim 2 will focus on developing a nanoparticle-based strategy for further improving the survival of the microencapsulated islets. Physiological amounts of antioxidants show enhanced islet survival post-transplantation. Encapsulating antioxidants in nanoparticles can improve the uptake and allow for sustained release during islet transplantation. Effect of the antioxidant-laden nanoparticles on islet survival and insulin production will be tested in vitro and then their effects on blood glucose levels tested in vivo. Through a combination of deep learning-enabled selective extraction, core-shell hydrogel microencapsulation, and nanoparticle-mediatexd antioxidants delivery, major challenges facing islet transplantation may be addressed. This novel multiscale engineering strategy has great potential for clinical translation to be widely used for treating type 1 diabetes.