Basal Profile Translation for Insulin Pump Transition
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Solution Overview
Problem
Conventional automatic drug delivery systems face challenges in transitioning users from multiple daily injection therapy to insulin pump therapy, requiring determination of unfamiliar parameters and lacking the ability to refine basal profiles based on glucose control outcomes, especially when glucose readings are not available.
Innovation Solution
The system proposes an initial basal profile for new users by translating their typical multiple daily injection therapy parameters into an automated basal profile, and adjusts this profile over time based on observed glucose control outcomes, incorporating overnight and daytime segments to address varying insulin needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the automatic drug delivery system uses conventional basal profile parameters for insulin delivery, then the system can provide automated insulin delivery, but the transition from multiple daily injection therapy becomes difficult due to unfamiliar parameters
Solution Approach 1:
The system transforms conventional MDI parameters (total daily insulin dose, long-acting insulin dose, short-acting insulin doses) into automated pump therapy parameters (basal profile segments with start times, end times, and delivery rates). This parameter transformation allows users to transition smoothly from familiar MDI settings to automated delivery without needing to learn entirely new parameter sets.
Solution Approach 2:
The system introduces an intermediary translation process that converts between MDI therapy parameters and pump therapy basal profile parameters. This intermediary layer acts as a bridge, allowing the automated system to accept familiar MDI inputs and automatically generate appropriate pump delivery schedules, easing the transition for users.
2Reliability
If the automatic drug delivery system provides fixed basal profiles, then the system can operate safely, but the system cannot refine the basal profile over time based on glucose control outcomes
Solution Approach 1:
The system implements a feedback mechanism where glucose control outcomes are continuously monitored and used to automatically adjust and refine basal profile parameters over time. This closed-loop feedback allows the system to adapt to individual user needs while maintaining safe delivery through algorithmic constraints and validation.
Solution Approach 2:
The basal profile transitions from a static, fixed configuration to a dynamic, adaptive parameter set that evolves over time based on observed glucose control outcomes. The system maintains reliability through controlled adaptation, allowing the basal profile to become increasingly personalized and optimized for each user's specific metabolic patterns.
3Measurement precision
If the automatic drug delivery system requires glucose readings for profile adjustment, then the system can optimize insulin delivery, but the system cannot provide recommendations when glucose readings are not available
Solution Approach 1:
The system performs preliminary actions by establishing an initial basal profile based on MDI parameters before glucose data becomes available. This preliminary configuration allows the system to begin automated insulin delivery immediately using safe, algorithm-derived parameters, and then refine the profile as glucose readings become available for optimization.
Data Source
AI summary
Disclosed herein are various embodiments comprising methods to propose or modify a basal profile of a user, wherein the basal profile is delivered by an automatic drug delivery system operating in manual mode or is administered manually by the user. Suggestions of initial basal profiles or modifications to existing basal profiles may be based on previous glucose control outcomes or previous insulin delivery as recorded by the automatic drug delivery system.