Risk-Based Insulin Delivery Set Points from Glucose Variability
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Solution Overview
Problem
Current insulin delivery systems for diabetes management impose a significant cognitive burden on users, requiring frequent manual adjustments and recalibration, and there is a lack of reliable, safe, and simple systems for glycemic control.
Innovation Solution
A method and system that adjusts basal insulin delivery rates based on estimated variability in blood glucose levels over a diurnal period, using a continuous glucose monitor and insulin pump to automatically modify target blood glucose levels and deliver insulin accordingly, incorporating predictive models and user-specific dosage parameters to minimize glycemic fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual insulin dosing adjustments are made multiple times per day, then glycemic control can be maintained, but cognitive burden on the patient increases significantly
Solution Approach 1:
The system enables self-service by automatically monitoring blood glucose levels and adjusting insulin delivery without requiring patient intervention. The closed-loop system autonomously makes dosing determinations that would otherwise require multiple patient decisions per day, thereby maintaining glycemic control while eliminating cognitive burden.
Solution Approach 2:
The system implements continuous feedback through real-time blood glucose monitoring that automatically feeds into the insulin delivery algorithm. This closed-loop feedback mechanism allows the system to dynamically adjust insulin rates based on actual glucose levels, ensuring reliable glycemic control without requiring patient cognitive processing.
2Ease of operation
If insulin delivery is automated with closed-loop control, then cognitive burden is reduced, but system complexity increases
Solution Approach 1:
The system merges the continuous glucose monitor and insulin pump into an integrated closed-loop system. By combining these two devices and their control algorithms into a unified system, the patent reduces overall complexity compared to having separate manual coordination of multiple devices, while achieving automated insulin delivery.
Solution Approach 2:
The control system performs multiple functions including continuous glucose monitoring, predictive glucose level calculation, insulin dosage determination, and pump control adjustment. This multi-functionality consolidates what would otherwise require multiple separate systems into a single universal platform, managing complexity through integration.
3Device complexity
If fixed target blood glucose levels are used, then insulin delivery protocol is simple, but glycemic control precision decreases due to individual variability
Solution Approach 1:
The system transitions from static fixed target glucose levels to dynamic personalized targets. By calculating individual variability metrics from historical glucose data and adjusting target levels accordingly, the system adapts to each patient's unique physiological patterns, thereby improving glycemic control precision without excessive complexity.
Solution Approach 2:
The system changes the parameter of target blood glucose level from a fixed constant to a variable that adjusts based on individual patient variability. This parameter modification allows the system to optimize glycemic control for each patient's specific needs while maintaining protocol simplicity through automated calculation.
4Measurement precision
If frequent blood glucose monitoring is performed, then glycemic control accuracy improves, but loss of time and energy increases
Solution Approach 1:
The system implements continuous blood glucose monitoring that operates without interruption, eliminating the need for discrete manual testing sessions. This continuous action provides accurate glycemic data in real-time without requiring the patient to allocate specific time blocks for monitoring, thereby improving accuracy without increasing perceived time loss.
Solution Approach 2:
The system replaces manual blood glucose testing mechanics with automated continuous monitoring. The automated sensor and data collection system eliminates the need for patient involvement in the physical act of testing, transferring the monitoring function from mechanical patient action to automated electronic operation, thus improving accuracy without consuming patient time.
Data Source
AI summary
A method may include obtaining blood glucose level readings over a diurnal period for each of a plurality of days and determining an estimated variability of the blood glucose levels over the diurnal period for the plurality of days. The method may also include modifying, based on the estimated variability of the blood glucose level, a target blood glucose level to a modified target blood glucose level, and delivering insulin, using an insulin pump, during the diurnal period based on the modified target blood glucose level.