Adaptive Neuromodulation System Using Biomarker Feedback
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Solution Overview
Problem
Current neuromodulation systems for treating neuroinflammation lack precision in delivering targeted therapy, as they do not effectively utilize real-time biomarker data to adjust stimulation parameters, leading to suboptimal treatment outcomes.
Innovation Solution
A neuromodulation system that includes a neuromodulation output circuit, memory, and control circuit configured to deliver neuromodulation energy based on stored parameter sets and sensed biomarker data, allowing for real-time adjustments to optimize treatment by comparing biomarker parameters to reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neuromodulation systems deliver therapy based on fixed parameters, then device complexity is reduced, but treatment precision and adaptability deteriorate
Solution Approach 1:
The system continuously monitors biomarker levels (such as glutamate, GABA, or other neural markers) and uses this feedback to automatically adjust neuromodulation parameters. The control circuit receives biomarker data from sensors, compares it to reference ranges, and modifies stimulation intensity, frequency, or duration accordingly, creating a closed-loop system that adapts to real-time neural state changes
Solution Approach 2:
The neuromodulation system transitions from static, pre-programmed parameters to dynamic, real-time parameter adjustment. The stimulation parameters are no longer fixed but continuously adapted based on measured biomarker levels, allowing the system to respond to changing neural conditions and optimize therapeutic effect throughout the day
2Adaptability or versatility
If neuromodulation systems use real-time biomarker data to adjust parameters, then treatment adaptability is improved, but device complexity increases
Solution Approach 1:
The implantable device integrates multiple functions into a single system: it includes both the neuromodulation stimulation circuitry and the biomarker sensing capability within the same implantable unit. This multi-functional design allows the device to both monitor neural biomarkers and deliver adaptive therapy without requiring separate implanted components, thereby managing complexity while maintaining adaptability
Solution Approach 2:
The system performs self-adjustment of therapy parameters based on its own measurements of neural biomarker levels. The control circuit automatically interprets biomarker data and modifies stimulation parameters without requiring external intervention or complex external programming systems, enabling the device to self-optimize therapy in real-time
3Ease of operation
If fixed stimulation parameters are used, then ease of operation is improved, but treatment efficacy deteriorates
Solution Approach 1:
The system incorporates automatic feedback control where biomarker measurements directly drive parameter adjustments. This eliminates the need for manual trial-and-error programming while ensuring therapy is optimized for the patient's current neural state, simultaneously improving ease of operation and treatment efficacy
Solution Approach 2:
The system is pre-programmed with reference ranges for biomarker levels and algorithms for parameter adjustment. This preliminary configuration allows the device to automatically adapt to real-time conditions without requiring complex user programming, maintaining ease of operation while achieving personalized adaptive therapy
Data Source
AI summary
An example of a system for modulating neuroinflammation at a tissue site in a patient includes a neuromodulation output circuit, a memory, and a control circuit. The neuromodulation output circuit may be configured to deliver the neuromodulation. The memory may be configured to store a neuromodulation parameter set selected to modulate neural activity at the tissue site and a sensed biomarker parameter. The biomarker parameter may include a measure of a biomarker or a measure of a derivative of the biomarker. The biomarker may be indicative of the neuroinflammation at the tissue site. The control circuit may be configured to control the delivery of the neuromodulation using the neuromodulation parameter set and adjust one or more parameters of the neuromodulation parameter set using the biomarker parameter.