Revolutionizing diabetes management by combining in silico models and AI control for vagus neuroprostheses

Introduction

Diabetes is a major world health problem, approaching epidemic proportions and causing long-term health damages due to inappropriate blood glucose regulation. Pharmacological therapies are limited by numerous side effects (such as renal insufficiency or heart failure) and dose management issues. Their efficacy is also hindered by often problematic patient compliance.

Unmet Need

This results in an unmet need for automatized, closed-loop glucose metabolism regulation, adaptable to variable patient conditions. The vagus nerve (VN) is a major component of the autonomous nervous system innervating internal organs, and its electrical stimulation has shown preliminary results in modulating glucose metabolism. However, the underlying mechanisms remain unknown, posing a high risk to its feasibility, and could lead to indiscriminate stimulation causing multiple side effects (compromising breathing or heart rate).

Research Goals

Fine glucose regulation cannot be achieved without a better understanding of nerve-implant interaction and circuits stimulated by VNS. I aim to fill present scientific gaps by developing the first VNS neuroprosthesis for personalized closed-loop regulation of glucose levels in diabetics.

Challenges

This results in a significant challenge: defining stimulation policies able to selectively block or activate specific neural pathways while counteracting metabolic shifts and implant-nerve alterations.

Methodology

To that aim, I will exploit models-driven interface design and AI-based stimulation policies.

1. Animal Experiments:

   • Investigate the physiological responses to optimal policies.
   • Maximize glucose regulation while minimizing adverse events.
   • Inspect both cervical and abdominal VNS.

2. Human Trials:

   • Validate optimal VNS.
   • Achieve device assessment in patients.

Expected Outcomes

DiabetManager will shed light on the underlying mechanisms of VNS-mediated glucose metabolism control while providing a versatile VN in-silico model, an unprecedented AI architecture for its adaptive stimulation, and disruptive health treatment.