Automated Insulin Dosing Feedback for User-Specific Bolus Adjustment
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Solution Overview
Problem
Existing automated medicament delivery systems often fail to optimize glucose control outcomes when a user's behavior deviates from the specific patterns assumed by their algorithms, leading to sub-optimal insulin delivery.
Innovation Solution
A system and method that assesses the actual manual insulin delivery patterns of a user and adjusts clinical parameters such as insulin-to-carb ratio and correction factor based on the proportion of actual versus target manual insulin delivery, aligning insulin delivery with the user's individual glucose disturbances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated medicament delivery algorithms use fixed patterns to determine bolus dosing, then the system operates with simple rules, but glucose control outcomes become sub-optimal when user behavior deviates from assumed patterns
Solution Approach 1:
The system continuously monitors actual manual insulin delivery patterns and uses this feedback to dynamically adjust algorithm parameters. The automated medicament delivery device receives data about user behavior patterns and modifies its bolus dosing calculations accordingly, creating a closed-loop system that adapts to individual user needs without requiring complex manual reconfiguration.
Solution Approach 2:
The algorithm transitions from static, fixed patterns to dynamic, adaptive parameters that automatically adjust based on observed user behavior. The system modifies parameters such as bolus fraction targets and dosing calculations in real-time based on actual delivery patterns, allowing the algorithm to evolve with the user's changing needs while maintaining computational efficiency.
2Reliability
If the system adjusts clinical parameters based on actual versus target manual insulin delivery proportion, then glucose control improves, but the system complexity increases
Solution Approach 1:
The system automatically modifies clinical parameters including insulin-to-carb ratios, correction factors, and bolus fractions based on the proportion of actual versus target manual insulin delivery. By dynamically adjusting these parameters according to observed delivery patterns, the system optimizes glucose control while keeping the adjustment logic encapsulated within the algorithm, preventing user confusion.
Solution Approach 2:
The system performs self-optimization by automatically adjusting its own parameters based on monitored delivery patterns without requiring user intervention. The automated medicament delivery device independently analyzes actual versus target delivery proportions and modifies its bolus dosing calculations accordingly, eliminating the need for complex user-side calculations or manual parameter reconfiguration.
3Productivity
If the automated medicament delivery device delivers medicament based on assumed user patterns, then the system operates efficiently, but it fails to optimize for individual user deviations
Solution Approach 1:
The system performs preliminary analysis of user behavior patterns and pre-adjusts algorithm parameters before they are needed for actual dosing calculations. By anticipating individual deviations based on observed patterns, the system prepares optimized parameters in advance, maintaining efficient automated operation while improving precision for individual user needs without requiring real-time complex computations during dosing events.
Data Source
AI summary
A system for administration of medicament to a user-body includes an analyte sensor and an automated medicament delivery device. The automated medicament delivery device is configured to determine an actual bolus fraction of a total daily medicament that was delivered as a total daily bolus dose, determine a ratio of the actual bolus fraction relative to a target bolus fraction, and based at least partially on the determined ratio of the actual bolus fraction relative to a target bolus fraction, determine at least one new value of a parameter value utilized by the automated medicament delivery device to determine bolus doses.