Intelligent Infusion Management System

Publication ID: 24-11857762_0005_PTD

Published: November 07, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Infusion Management System,” Published Technical Disclosure No. 24-11857762_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857762_0005_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. 11,857,762.

Summary of the Inventive Concept

A wearable, real-time fluid flow monitoring and control system that leverages machine learning and predictive analytics to optimize infusion therapy, ensuring accurate and personalized fluid delivery.

Background and Problem Solved

The original patent's integrated liquid flow closed loop sensing and control technology has limitations in terms of real-time monitoring and adaptability. The new inventive concept addresses these limitations by introducing a wearable, machine learning-based system that predicts potential flow rate deviations and adjusts the infusion rate accordingly, providing a more accurate and personalized infusion experience.

Detailed Description of the Inventive Concept

The Intelligent Infusion Management System consists of a wearable infusion device with an integrated fluid flow sensor and a machine learning-based predictive analytics module. The module analyzes real-time sensor data and patient-specific information to predict potential flow rate deviations, adjusting the infusion rate to ensure optimal fluid delivery. The system also includes a cloud-based fluid flow monitoring platform, a network of wearable infusion devices, and a real-time data analytics module to detect anomalies in fluid flow data and alert healthcare professionals to potential infusion errors.

Novelty and Inventive Step

The new inventive concept introduces a wearable, machine learning-based system that integrates real-time fluid flow monitoring, predictive analytics, and adaptive control, providing a novel and non-obvious solution for optimizing infusion therapy. The use of machine learning algorithms and real-time sensor data to generate patient-specific fluid flow profiles and dynamically adjust the infusion rate is a significant departure from the original patent's technology.

Alternative Embodiments and Variations

Alternative embodiments of the Intelligent Infusion Management System could include a modular design with interchangeable sensors and analytics modules, or a standalone fluid flow monitoring device that integrates with existing infusion systems. Variations could also include the use of different machine learning algorithms or sensor technologies to optimize fluid flow monitoring and control.

Potential Commercial Applications and Market

The Intelligent Infusion Management System has significant commercial potential in the medical device industry, particularly in the areas of infusion therapy, patient monitoring, and personalized medicine. The system's ability to optimize fluid delivery and reduce the risk of infusion errors could lead to improved patient outcomes, reduced healthcare costs, and increased market share for companies that adopt this technology.

CPC Classifications

Section	Class	Group
A	A61	A61M5/172
A	A61	A61M2205/3334
A	A61	A61M2205/3584
A	A61	A61M2205/52
H	H01	H01R13/15
H	H01	H01R2201/12
H	H01	H01R2201/20
H	H02	H02J50/10

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Medical Device Technology, Specifically Infusion Systems and Fluid Flow Control, involving Biomedical Engineering, Electronic Sensing, and Control Systems with Expertise in Medical Device Design, Electronic Sensor Integration, and Fluid Delivery Mechanisms

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device designer with advanced knowledge of electronic sensing technologies, fluid dynamics, control systems, and machine learning applications in medical device design, typically holding a Master's or PhD in Biomedical Engineering or related field

Obviousness Rationale

A PHOSITA would recognize that integrating machine learning and predictive analytics into existing closed-loop fluid monitoring systems represents a natural technological progression. The source patent's foundational work on integrated flow sensing provides a clear technological framework that would motivate a skilled practitioner to explore advanced computational techniques for improving fluid delivery precision. The machine learning extensions represent an incremental, predictable enhancement to existing medical device control methodologies.

Obvious Combinations & Variations

Source Patent Element

Electronic flow sensor with conductive connections and control circuitry for modifying infusion device flow rates

PTD Variation

Adding machine learning predictive analytics module to dynamically adjust infusion rates based on real-time sensor data

Obviousness Reasoning

Applying computational intelligence to existing sensor-based control systems is a known technique in medical device design, representing a predictable technological evolution with foreseeable improvements in precision and personalization

Source Patent Element

Integrated IV administration set with flow stop and electronic sensing capabilities

PTD Variation

Implementing cloud-based monitoring platform and networked wearable devices for comprehensive fluid flow tracking

Obviousness Reasoning

Extending local sensing capabilities to networked, cloud-connected systems is a standard approach in modern medical technology, representing an obvious design choice for improving data collection and patient monitoring

Source Patent Element

Tubing fitment with electronic flow sensor and data communication components

PTD Variation

Incorporating artificial intelligence directly into electronic flow sensors to detect and automatically correct fluid flow anomalies

Obviousness Reasoning

Integrating intelligent decision-making capabilities into existing sensor architectures is a predictable technological progression, utilizing well-established machine learning techniques to enhance existing sensing technologies

Source Patent Element

Control circuitry configured to send signals modifying pumping mechanism flow rates

PTD Variation

Developing patient-specific fluid flow profiles using machine learning algorithms and real-time sensor data

Obviousness Reasoning

Personalizing control systems through advanced computational techniques represents a natural extension of existing control methodologies, leveraging known machine learning approaches to improve medical device performance

Source Patent Element

Infusion device with electronic flow sensing and communication capabilities

PTD Variation

Creating a closed-loop infusion control system with feedback mechanisms driven by predictive analytics

Obviousness Reasoning

Enhancing feedback control systems with predictive computational techniques is a standard engineering approach, representing an obvious technological improvement with foreseeable benefits in medical device precision

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857762 and the disclosed technological variations, a Person Having Ordinary Skill In The Art would find the proposed machine learning-enhanced fluid flow monitoring and control systems to be obvious extensions of existing medical device technologies. The incremental advancements in computational intelligence, sensor integration, and adaptive control represent predictable technological progressions that would be readily conceived by a skilled practitioner in the field of medical device design and biomedical engineering.

Original Patent Information

Patent Number	US 11,857,762
Title	Integrated liquid flow closed loop sensing and control
Assignee(s)	CareFusion 303, Inc.