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

> **NIH NIH F31** · UNIV OF MARYLAND, COLLEGE PARK · 2022 · $34,248

## Abstract

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 extract...

## Key facts

- **NIH application ID:** 10389894
- **Project number:** 1F31DK131905-01
- **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK
- **Principal Investigator:** Alisa White
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $34,248
- **Award type:** 1
- **Project period:** 2022-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10389894

## Citation

> US National Institutes of Health, RePORTER application 10389894, Deep Learning-reinforced Engineering of Pancreatic Organoids with Micro-nano Biomaterials for Type 1 Diabetes Treatment (1F31DK131905-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10389894. Licensed CC0.

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