Enhanced Insulin Delivery Rate Adjustment System

Publication ID: 24-11857763_0006_PTD
Published: October 28, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Insulin Delivery Rate Adjustment System,” Published Technical Disclosure No. 24-11857763_0006_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857763_0006_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,763.

Summary of the Inventive Concept

An advanced system for adjusting insulin delivery rates, incorporating machine learning and real-time glucose data analysis to optimize insulin delivery for individuals with diabetes.

Background and Problem Solved

The original patent, 'Adjusting insulin delivery rates', addressed the need for personalized insulin delivery. However, it had limitations in terms of predicting future glucose levels, handling fear of hypoglycemia, and adapting to changing glucose trends. The new inventive concept builds upon the original patent, providing enhanced features to overcome these limitations.

Detailed Description of the Inventive Concept

The system comprises a glucose measurement device, a processor, and a controller. The processor predicts multiple future blood glucose levels for multiple different basal insulin delivery profiles, and the controller selects the optimal profile that minimizes differences between predicted future blood glucose values and target blood glucose values. The system can also receive glucose data, calculate a probability of achieving a target blood glucose level, and select an optimal basal insulin delivery profile based on the calculated probability. Additionally, the system can obtain a fear of hypoglycemia index from a user, calculate a personalized basal insulin delivery rate, and deliver insulin accordingly. The system can adapt to changing glucose trends by identifying trends in glucose data and adjusting the basal insulin delivery rate in real-time.

Novelty and Inventive Step

The new inventive concept introduces the use of machine learning algorithms to predict multiple future blood glucose levels, enabling the selection of an optimal basal insulin delivery profile. The system's ability to adapt to changing glucose trends and incorporate fear of hypoglycemia indices into insulin delivery decisions are also novel and non-obvious improvements over the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the system could include using different machine learning algorithms, incorporating additional health metrics (e.g., exercise, diet), or integrating with wearable devices. Variations could include implementing the system in different form factors, such as a mobile app or a dedicated device.

Potential Commercial Applications and Market

The enhanced insulin delivery rate adjustment system has significant commercial potential in the diabetes management industry, with potential applications in personalized medicine, real-time glucose monitoring, and artificial pancreas systems. The target market includes individuals with diabetes, healthcare providers, and medical device manufacturers.

CPC Classifications

SectionClassGroup
A A61 A61M5/1723
A A61 A61B5/14532
A A61 A61B5/4839
A A61 A61M5/142
A A61 A61M5/145
A A61 A61M5/14244
A A61 A61M5/14248
G G16 G16H20/17
G G16 G16H40/60
G G16 G16H40/67
A A61 A61B2562/0295
A A61 A61M2005/14208
A A61 A61M2205/3303
A A61 A61M2205/3553
A A61 A61M2205/3561
A A61 A61M2205/3569
A A61 A61M2205/3584
A A61 A61M2205/502
A A61 A61M2205/52
A A61 A61M2230/005
A A61 A61M2230/201
G G16 G16H10/60
G G16 G16H40/40
G G16 G16H50/30

Field of Art

Medical device technology focused on diabetes management, insulin delivery systems, and personalized medical monitoring, requiring expertise in biomedical engineering, medical device design, data analysis, and metabolic health monitoring

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device specialist with advanced knowledge of diabetes management technologies, proficient in machine learning, data processing algorithms, and physiological monitoring systems, holding at least a master's degree with 3-5 years of specialized experience

Obviousness Rationale

A person having ordinary skill in the art would recognize that the PTD's machine learning-based insulin delivery optimization represents a predictable technological progression from the source patent's foundational glucose management approach. The disclosed variations leverage known machine learning techniques to enhance insulin delivery prediction and personalization, which would be a natural evolutionary step for a skilled practitioner seeking to improve diabetes management technologies.

Obvious Combinations & Variations

Source Patent Element
Calculating probability of achieving glucose level based on input parameters
PTD Variation
Incorporating machine learning algorithms to predict multiple future blood glucose levels across different insulin delivery profiles
Obviousness Reasoning
Applying machine learning to predictive medical modeling is a known technique, and a PHOSITA would recognize the potential for more sophisticated glucose level predictions using advanced computational methods
Source Patent Element
Fear of hypoglycemia index as an input parameter
PTD Variation
Dynamically adjusting insulin delivery rates based on personalized hypoglycemia risk and real-time glucose trends
Obviousness Reasoning
Expanding patient-specific risk parameters into adaptive delivery mechanisms represents a logical extension of existing personalization techniques in medical device design
Source Patent Element
Insulin delivery profiles with variable baseline rates
PTD Variation
Using machine learning to select optimal insulin delivery profiles that minimize glucose value deviations
Obviousness Reasoning
Implementing computational selection methods for optimizing existing profile-based delivery approaches is a predictable solution for improving medical device performance
Source Patent Element
Glucose data collection and analysis
PTD Variation
Real-time trend identification and dynamic insulin rate adjustment using continuous sensor data
Obviousness Reasoning
Enhancing data-driven medical device responsiveness through continuous monitoring and adaptive algorithms is a natural technological progression in medical device design
Source Patent Element
Basic insulin delivery rate calculation methods
PTD Variation
Integrating additional health metrics and wearable device data to refine insulin delivery personalization
Obviousness Reasoning
Expanding input parameters for medical device decision-making represents a standard approach to improving technological precision and patient outcomes
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857763 and the disclosed technical variations, a person having ordinary skill in the art would find the claimed insulin delivery optimization techniques obvious and anticipated, as the published technical disclosure demonstrates predictable technological extensions utilizing standard machine learning and medical device design principles, thereby rendering subsequent claims of novelty invalid under 35 U.S.C. ยง 103.

Original Patent Information

Patent NumberUS 11,857,763
TitleAdjusting insulin delivery rates
Assignee(s)INSULET CORPORATION