Summary
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 (as renal insufficiency or heart failure) and dose management issues. Their efficacy is also hindered by often problematic, patients’ compliance. This results in an unmet need for automatized, closed-loop glucose metabolism regulation, adaptable to variable patients’ conditions. Vagus nerve (VN) is a major component of the autonomous nervous system innervating internal organs, and its electrical stimulation showed preliminary results in modulating glucose metabolism. However, 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). Fine glucose regulation cannot be achieved without 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. 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. To that aim I will exploit models-driven interface design and AI-based stimulation policies. Animal experiments will investigate the physiological responses to optimal policies, maximising glucose regulation while minimizing adverse events, inspecting both cervical and abdominal VNS. Optimal VNS will be validated in human trials achieving device assessment in patients. DiabetManager will shed light on the underlying mechanisms of VNS-mediated glucose metabolism control, while providing versatile VN in-silico model, unprecedent AI-architecture for its adaptive stimulation, and disruptive health treatment.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101126266 |
| Start date: | 01-09-2024 |
| End date: | 31-08-2029 |
| Total budget - Public funding: | 1 999 201,00 Euro - 1 999 201,00 Euro |
Cordis data
Original description
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 (as renal insufficiency or heart failure) and dose management issues. Their efficacy is also hindered by often problematic, patients’ compliance. This results in an unmet need for automatized, closed-loop glucose metabolism regulation, adaptable to variable patients’ conditions. Vagus nerve (VN) is a major component of the autonomous nervous system innervating internal organs, and its electrical stimulation showed preliminary results in modulating glucose metabolism. However, 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). Fine glucose regulation cannot be achieved without 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. 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. To that aim I will exploit models-driven interface design and AI-based stimulation policies. Animal experiments will investigate the physiological responses to optimal policies, maximising glucose regulation while minimizing adverse events, inspecting both cervical and abdominal VNS. Optimal VNS will be validated in human trials achieving device assessment in patients. DiabetManager will shed light on the underlying mechanisms of VNS-mediated glucose metabolism control, while providing versatile VN in-silico model, unprecedent AI-architecture for its adaptive stimulation, and disruptive health treatment.Status
SIGNEDCall topic
ERC-2023-COGUpdate Date
24-11-2024
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