Open Architecture Therapy Delivery System for Custom Control Algorithms
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Solution Overview
Problem
Existing therapy delivery systems for chronic diseases, such as diabetes, often rely on algorithms developed from population studies, which may not adequately meet the individual needs of patients, as changes to these algorithms require extensive testing and are considered non-trivial.
Innovation Solution
A therapy delivery system with an open architecture that allows for the replacement and customization of control algorithms, enabling the implementation of individually tailored therapy through a simulation module that tests and validates new algorithms before deployment, ensuring safe and effective therapy delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control algorithms are developed from population-based studies, then the system maintains reliability and safety through formal testing, but the system loses adaptability to individual patient needs
Solution Approach 1:
The control algorithm is segmented into a standardized core framework that ensures reliability and customizable parameters/modules that enable individualization. This segmentation allows the system to maintain formal testing for the core while allowing flexible customization for patient-specific needs.
Solution Approach 2:
The system transitions from static, pre-tested algorithms to dynamic, adaptable algorithms that can be customized for individual patients while maintaining safety through simulation testing. The algorithm structure allows for dynamic adjustment of parameters based on patient response and changing conditions.
2Adaptability or versatility
If control algorithm logic or parameter ranges are changed to meet individual needs, then the system improves adaptability, but the system increases complexity and requires extensive re-testing
Solution Approach 1:
The system performs preliminary simulation testing in a virtual environment before deploying customized algorithms to patients. This preliminary action allows for validation of individualized algorithms without requiring extensive clinical re-testing, reducing the complexity burden of customization.
Solution Approach 2:
A simulation module acts as an intermediary between algorithm development and clinical deployment. This intermediary layer enables testing and validation of customized algorithms in a controlled virtual environment, simplifying the path from customization to patient use.
3Ease of operation
If a standardized control algorithm is used across all patients, then the system maintains ease of operation and deployment, but the system reduces manufacturing precision in meeting individual therapy requirements
Solution Approach 1:
The system applies local quality by maintaining a standardized core algorithm for ease of deployment while allowing specific parameters and modules to be customized for each patient's unique needs. This enables precise tailoring of therapy to individual patients without complicating the overall system deployment.
Data Source
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AI summary
A therapy delivery system having an open architecture and method of providing thereof are disclosed. The present invention provides a therapy dosage module having a control algorithm that can be replaced with a predefined or independently defined control algorithm. The tools necessary to create and test such control algorithms in the therapy dosage module in a simulated environment before implementing it in a live therapy system are also disclosed.