AI Hemodynamic Control via Phenotypic Response Surface
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Solution Overview
Problem
Precise management of hemodynamics in surgery patients is challenging due to unique and dynamic physiologic responses to medications, leading to conditions like post-operative acute kidney injury and myocardial infarction, necessitating effective personalized and targeted hemodynamic management.
Innovation Solution
An artificial intelligence-enabled system that administers blood pressure regulators such as vasopressors and vasodilators based on individualized sensitivity, using a phenotypic response surface platform to dynamically adjust dosages and maintain target blood pressure ranges, incorporating a first dose based on population-averaged sensitivity and subsequent doses adjusted according to real-time individual responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If population averaged sensitivity is used for medication dosing, then dosing simplicity is improved, but dosing precision deteriorates due to unique and dynamic patient responses
Solution Approach 1:
The system performs preliminary dosing using population-averaged sensitivity parameters to establish an initial treatment protocol. This preliminary action provides a standardized starting point that is simple to implement while acknowledging that individual patient responses will require subsequent adjustments to achieve precise dosing.
Solution Approach 2:
The system transitions from static population-averaged dosing to dynamic individualized dosing by continuously monitoring patient responses and adjusting medication dosages in real-time. This dynamic adaptation allows the system to maintain dosing precision while retaining operational simplicity through automated adjustments.
2Adaptability or versatility
If intermittent dosing modification is used to obtain therapeutic effect, then dosing flexibility is improved, but hemodynamic control stability deteriorates
Solution Approach 1:
The system implements continuous feedback mechanisms where patient hemodynamic responses to medication are monitored and used to automatically adjust subsequent dosing. This feedback loop maintains hemodynamic stability by making real-time corrections while preserving dosing flexibility to accommodate individual patient needs.
Solution Approach 2:
The system dynamically changes dosing parameters based on monitored patient responses rather than using fixed intermittent dosing schedules. This parameter adaptation allows the system to maintain both flexibility in responding to individual patients and stability in achieving target hemodynamic values.
3Reliability
If personalized hemodynamic management is implemented, then patient outcome reliability is improved, but system complexity increases
Solution Approach 1:
The system enables self-service through automated algorithms that independently analyze patient data, determine appropriate dosing, and adjust medication administration without requiring complex manual intervention. This automation reduces the operational complexity burden while maintaining high reliability through consistent, data-driven decision-making.
Solution Approach 2:
The system replaces complex manual dosing decisions with computational algorithms and automated control mechanisms. This substitution of mechanical (manual) systems with electronic/computational systems maintains reliability through objective data analysis while managing complexity through standardized computational processes rather than complex human expertise.
Data Source
AI summary
Systems and methods for artificial intelligence enable control of hemodynamics in an individual are provided. A number of embodiments use a phenotypic response surface (PRS) that describes a physiological response to a vasopressor and/or a vasodilator to guide administration of the vasopressor and/or vasodilator. Additional embodiments determine an individualized response to but not limited to a vasopressor and/or vasodilator based on the change in pressure to a dose based on a population-based average. Some embodiments continually update the PRS and/or individualized sensitivity based on changes in physiological response to the vasopressor and/or vasodilator.