Sensor-Learned Pump Modes for Personalized Insulin Delivery

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Solution Overview

Problem

Automated drug delivery systems often require manual adjustments for life pattern changes, which can be intimidating, and default modes with pre-set settings may not be optimal for individual users due to significant interpersonal variations in insulin delivery needs.

Innovation Solution

A customizable medicament delivery algorithm that learns from user sensor data during an initial phase to establish personalized settings for a custom mode, allowing users to select activities and minimize manual input, adjusting medicament delivery parameters based on recorded sensor data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If default modes with pre-set settings are used, then ease of operation is improved, but manufacturing precision (optimality of insulin delivery settings) deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidoptimality of insulin delivery settings

Core Design Contradiction:

Ease of operationVSManufacturing precision

Solution Approach 1:

The system performs preliminary learning during an initial phase where it collects and evaluates sensor data to automatically establish customized mode parameters before the user needs to use the system. This preliminary action eliminates the need for users to manually configure settings while ensuring optimal insulin delivery parameters are pre-established based on actual user data.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system serves itself by automatically learning from sensor data and establishing customized mode parameters without requiring user intervention. The processor evaluates sensor data and sets medicament delivery algorithm parameters autonomously, freeing users from the intimidating task of manual adjustments while maintaining optimal delivery settings.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If manual adjustments are required for life pattern changes, then adaptability is improved, but ease of operation deteriorates

Engineering Contradiction:

ImproveadaptabilityVSAvoidease of operation

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors sensor data and uses this feedback to evaluate and adjust medicament delivery algorithm parameters. The processor receives sensor data, evaluates it against established criteria, and automatically modifies delivery settings to adapt to changing life patterns, maintaining both adaptability and ease of operation.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If singular fixed settings are used for life pattern adjustments, then ease of operation is improved, but adaptability deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidadaptability

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system transitions from static fixed settings to dynamic parameters that automatically adjust based on evaluated sensor data. The medicament delivery algorithm parameters are continuously refined through the learning process, allowing the system to adapt to individual users' unique responses and changing patterns while maintaining ease of operation through automation.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes parameters automatically based on sensor data evaluation. The processor modifies medicament delivery algorithm parameters such as target glucose concentrations, basal delivery rates, and response factors to create customized modes that adapt to each user's specific needs, eliminating the limitations of singular fixed settings.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250288740A1System and methods to customize modes into actionable pump settings

Publication Date: 2025.09.18 INSULET CORP

AI summary

A system and device for establishing a customized mode of a medicament delivery algorithm. The device may include a processor configured to receive an indication to establish a custom mode. The device implements an initial learning phase. A processor executing the initial learning phase receives and evaluates sensor data for a duration of time. A sensor operable to make analyte measurements may provide analyte measurement values. Based on a result of the initial learning phase, the device sets medicament delivery algorithm parameters for the custom mode, thereby establishing the custom mode for operation of a wearable automated medicament delivery system.