Pregnancy-Adaptive Insulin Dosing Using Gestational TDI Scaling
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Solution Overview
Problem
Conventional automatic drug delivery systems struggle to maintain optimal glycemic control during pregnancy due to changing insulin requirements, which can lead to complications such as congenital malformations, miscarriage, and neonatal hypoglycemia, as they do not account for the fluctuating insulin needs throughout different phases of pregnancy.
Innovation Solution
The system adjusts the dosing algorithm by scaling the pre-pregnancy TDI requirements based on the current pregnancy phase, using continuous glucose monitoring to detect meal intake and adjust basal and bolus insulin doses dynamically, with feedback on meal composition and exercise, to ensure safe glycemic control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional automatic drug delivery systems use fixed dosing algorithms based on pre-pregnancy TDI requirements, then the system structure remains simple and easy to operate, but glycemic control deteriorates due to changing insulin requirements during pregnancy
Solution Approach 1:
The dosing algorithm transitions from static pre-pregnancy parameters to dynamic pregnancy-phase-specific parameters. The system automatically adjusts TDI requirements, basal insulin percentages, and insulin-to-carbohydrate ratios based on the detected pregnancy phase (first, second, or third trimester), ensuring glycemic control adapts to changing physiological conditions without requiring manual reconfiguration by the user.
Solution Approach 2:
The system modifies key dosing parameters including total daily insulin (TDI) requirements, basal insulin percentage, and insulin-to-carbohydrate ratios according to pregnancy phase. These parameter changes are automatically applied when the system detects phase transitions, resolving the contradiction by allowing complex parameter adjustments while maintaining ease of operation through automated detection and application.
2Reliability
If the system dynamically adjusts insulin doses based on pregnancy phase detection, then glycemic control improves, but the device complexity increases due to additional sensing and control mechanisms
Solution Approach 1:
The system performs self-diagnosis and self-adjustment by automatically detecting pregnancy phase transitions through glucose pattern recognition and autonomously modifying dosing parameters. This eliminates the need for manual user input or complex external monitoring equipment, achieving improved insulin delivery accuracy without proportionally increasing system complexity.
Solution Approach 2:
The system continuously monitors glucose levels and uses this feedback to detect pregnancy phase transitions and adjust dosing parameters accordingly. The feedback loop enables automatic adaptation to changing insulin requirements during pregnancy, improving delivery accuracy while keeping the system structure manageable through integrated sensing and control.
3Reliability
If the system uses phase-specific dosing parameters, then the risk of hypoglycemia and other complications reduces, but the difficulty of detecting and measuring pregnancy phase increases
Solution Approach 1:
The system replaces manual pregnancy phase determination with automated glucose pattern recognition algorithms. Instead of requiring mechanical or manual assessment methods, the system analyzes glucose level patterns, trends, and variability to infer pregnancy phase, reducing the difficulty of detection while improving safety through consistent, objective measurements.
Solution Approach 2:
The system uses glucose level patterns as an intermediary indicator to infer pregnancy phase. Rather than directly measuring physiological changes associated with pregnancy phase, the system detects indirect evidence through glucose dynamics, which serve as a mediator that translates physiological state into detectable signals for automated dosing adjustment.
4Adaptability or versatility
If conventional systems deliver fixed basal and bolus dosages, then the device operation remains simple, but the adaptability to changing pregnancy conditions deteriorates
Solution Approach 1:
The system automatically detects pregnancy phase transitions and adjusts dosing parameters without requiring user intervention. The pump performs self-service by monitoring glucose patterns, determining phase changes, and modifying TDI, basal percentage, and insulin-to-carbohydrate ratios autonomously, thereby achieving high adaptability while maintaining ease of operation.
Solution Approach 2:
The system transitions from fixed dosing parameters to dynamic, phase-adaptive parameters. By automatically adjusting insulin delivery based on detected pregnancy phase, the system achieves versatility in adapting to changing physiological conditions while keeping the user experience simple through automated operation.
Data Source
AI summary
The disclosed embodiments are directed to methods for dynamically adjusting the total daily insulin requirements of a user during pregnancy, based on the gestational week. An initial estimate of the adjusted total daily insulin requirement may be calculated as a multiple of the pre-pregnancy total daily insulin requirement, based on an average scale factor from a population of pregnant women suffering from Type I diabetes mellitus. An automatic drug delivery device may adjust the initial estimate of the total daily insulin requirement based on blood glucose level readings from a continuous glucose monitor during the course of the pregnancy.