Automated Insulin Delivery System with Multi-Reservoir Formulation
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Solution Overview
Problem
Conventional Automated Insulin Delivery (AID) systems face challenges in accurately managing postprandial glucose responses due to mismatches between glycemic reactions and insulin onset and peak actions, particularly with varying meal types, leading to ineffective glucose control.
Innovation Solution
An insulin formulation process that combines different types of insulin (rapid-acting and long-acting) based on event data, such as meal detection, carbohydrate ingestion, and activity levels, to generate specific insulin formulations and delivery rates, using a device with multiple insulin reservoirs and advanced monitoring systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional AID systems use single-type insulin delivery, then the system is simple to operate, but the postprandial glucose control accuracy deteriorates due to mismatch between glycemic response and insulin action timing
Solution Approach 1:
The patent segments the insulin delivery function by using multiple insulin reservoirs containing different insulin types (rapid-acting and long-acting). This segmentation allows the system to deliver different insulin formulations at different times to match the glycemic response to various meal types, thereby improving postprandial glucose control accuracy without requiring complete system redesign
Solution Approach 2:
The system dynamically selects and adjusts insulin formulation based on real-time CGM data and meal type detection. The control algorithm adapts the insulin delivery profile dynamically - choosing rapid-acting insulin for fast-absorbing carbohydrates and long-acting insulin for slow-absorbing meals - which resolves the contradiction between control accuracy and system complexity through adaptive decision-making
2Adaptability or versatility
If the system uses multiple insulin types with different onset and peak actions, then the adaptability to different meal types improves, but the device complexity increases due to multiple reservoirs and formulation management
Solution Approach 1:
The AID system is designed with multi-functionality by incorporating multiple insulin reservoirs that can store different insulin types. This universal design allows a single device to handle various meal types (high-carb, high-fat, high-fiber) by selecting appropriate insulin formulations, making the system adaptable to diverse dietary patterns without requiring multiple separate devices
Solution Approach 2:
The system performs self-service through automated insulin formulation selection and delivery. The control algorithm automatically determines the appropriate insulin type and dosage based on CGM data and meal type detection, eliminating the need for manual intervention in formulation management. This automation reduces the operational complexity burden on the user despite the increased device capability
3Reliability
If conventional systems use fixed insulin dosing schedules, then the operation is straightforward, but the effectiveness of glucose control deteriorates due to individual variations in glycemic response to different foods
Solution Approach 1:
The system implements continuous feedback control by monitoring glucose levels via CGM and adjusting insulin delivery accordingly. The control algorithm uses real-time glucose data to evaluate the effectiveness of current insulin dosing and automatically modifies subsequent dosing schedules. This feedback mechanism ensures reliable glucose control effectiveness while the automation maintains ease of operation by eliminating manual dosing calculations
Solution Approach 2:
The system dynamically changes insulin dosing parameters (type, amount, timing) based on detected meal types and individual glycemic responses. Rather than using fixed dosing schedules, the control algorithm adjusts parameters in real-time to match the specific carbohydrate load and absorption rate of each meal, thereby improving glucose control effectiveness while the automated parameter adjustment keeps the system easy to operate
Data Source
AI summary
Techniques and devices for determining and generating insulin formulations are described. An automated insulin delivery device may include a wireless interface with a glucose sensor for providing blood glucose concentration readings of a user, a plurality of insulin reservoirs, each of the plurality of insulin reservoirs holding a different one of a plurality of insulin types, each of the plurality of insulin types having a different strength, a storage medium storing programming instructions and user glucose information, the user glucose information comprising the blood glucose concentration readings, predicted future blood glucose concentration readings, and user activity information, determining an insulin strength based on the user glucose information, determining an insulin formulation ratio to generate an insulin formulation having the insulin strength using the plurality of insulin types, an insulin formulation device to generate the insulin formulation; and an insulin delivery component to deliver the insulin formulation to the user.