Virtual Basal Rate Profiles for Insulin Dosing Optimization
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Solution Overview
Problem
Current insulin management systems for diabetes, particularly multiple daily injections (MDI) and continuous subcutaneous insulin infusion (CSII), lack efficient methods for real-time adjustment of insulin dosing based on individual patient metabolic states, leading to suboptimal glycemic control and increased risk of hypoglycemia.
Innovation Solution
A method and system that constructs virtual basal rate profiles using pharmacokinetic properties of insulin to optimize insulin delivery, allowing for retrospective and real-time adjustments based on historical and planned insulin injections, providing a unified framework for analysis and optimization of MDI and CSII treatment parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time adjustment of insulin dosing based on individual patient metabolic states is implemented, then glycemic control is improved, but system complexity increases
Solution Approach 1:
The patent creates a virtual replica of the patient's insulin delivery system that mirrors actual insulin injections, CGM readings, and metabolic responses. This virtual model allows complex real-time optimization calculations to be performed in silico, simplifying the computational burden on the actual delivery system while maintaining personalized glycemic control.
Solution Approach 2:
The system performs retrospective analysis of historical data to build and refine the virtual basal rate profile before making real-time dosing decisions. By pre-characterizing the patient's insulin pharmacokinetics and metabolic responses through historical data mining, the system prepares optimization algorithms in advance, reducing real-time computational complexity.
2Measurement precision
If retrospective analysis of historical insulin data is performed, then dosing accuracy is improved, but processing time increases
Solution Approach 1:
The system continuously updates the virtual basal rate profile using historical data in a retrospective manner, building a comprehensive model of the patient's insulin response characteristics. This pre-computed profile is then queried in real-time for specific dosing scenarios, separating the time-consuming model building from the quick real-time queries.
Solution Approach 2:
The patent extracts key pharmacokinetic parameters and metabolic response patterns from historical insulin data, isolating the essential information needed for dosing decisions. By distilling complex historical data into simplified virtual basal rate profiles and lookup tables, the system retrieves dosing recommendations quickly without reprocessing the entire historical dataset in real-time.
3Productivity
If virtual basal rate profiles are constructed from planned injections, then treatment optimization is improved, but computational requirements increase
Solution Approach 1:
The system creates a simplified virtual representation of the patient's insulin delivery system that replicates the essential pharmacokinetic behavior without requiring complex real-time simulations. This virtual copy allows treatment optimization to be performed using lighter computational methods, reducing overall energy requirements while maintaining optimization effectiveness.
Solution Approach 2:
The patent transforms complex continuous insulin delivery parameters into discrete virtual basal rate profiles with characteristic pharmacokinetic parameters. By representing insulin action through simplified parameter sets (absorption rates, duration, magnitude) rather than continuous differential equations, the system reduces computational complexity while preserving treatment optimization capability.
Data Source
AI summary
Equivalent insulin pump retrospective virtual basal rates for daily injections are constructed from planned insulin injections according to a virtual basal rate profile developed for a patient, and a database of historical insulin injections, i.e. basal injections actually administered by the patient, providing a unified framework for analysis, design, optimization, and adaptation of MDI (multiple daily injections) and CSII (continuous subcutaneous insulin infusion (i.e. insulin pump) treatment parameters for patients with diabetes.