Closed-Loop Drug Administration Control System
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Solution Overview
Problem
Closed-loop control systems for anesthesia face challenges in addressing significant intra- and inter-patient variability in response to standard drug doses, leading to safety concerns and inefficiencies in drug delivery.
Innovation Solution
The implementation of a Model Predictive Controller (MPC) with auxiliary models, such as population-based PKPD models, to constrain drug infusion rates and concentrations, ensuring safe and effective anesthesia delivery by integrating physiological characteristics like blood pressure and depth of hypnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of drug dosing is used to account for patient variability, then individualized anesthesia can be achieved, but it requires considerable clinical experience and increases the complexity of operation
Solution Approach 1:
The closed-loop control system automatically adjusts drug infusion rates based on real-time physiological feedback without requiring continuous manual intervention. The system self-regulates by comparing actual physiological parameters against target values and automatically modifying the infusion rate to maintain optimal anesthesia depth, thereby eliminating the need for constant clinical assessment and adjustment while achieving individualized anesthesia.
Solution Approach 2:
The system continuously monitors physiological parameters (such as BIS, heart rate, blood pressure) and uses this feedback to automatically adjust drug infusion rates. The feedback loop enables the system to detect deviations from the desired anesthesia depth and correct them in real-time, providing adaptability without requiring manual intervention and reducing operational complexity.
2Ease of operation
If fixed drug infusion rates are used based on patient body weight, then the system is simple to operate, but it does not account for individual patient response variability
Solution Approach 1:
The system transitions from a static fixed infusion rate approach to a dynamic adaptive control system. The infusion rate is continuously adjusted based on real-time physiological feedback, allowing the system to adapt to individual patient responses while maintaining ease of operation through automated control. The dynamic adjustment occurs without requiring complex manual programming by the clinician.
Solution Approach 2:
The system automatically modifies the drug infusion rate parameter based on physiological feedback and patient response. Instead of using a fixed parameter value, the system dynamically changes the infusion rate to optimize anesthesia depth for each individual patient, achieving adaptability while the automated nature maintains operational simplicity.
3Manufacturing precision
If closed-loop control is implemented to reduce patient variability, then drug delivery precision is improved, but system complexity increases
Solution Approach 1:
The closed-loop control system integrates multiple functions into a single automated platform: physiological parameter monitoring, target anesthesia depth calculation, real-time feedback processing, and automatic infusion rate adjustment. This multi-functionality achieves precise drug delivery while consolidating complexity into an integrated system that requires minimal external intervention, balancing precision with manageable system complexity.
4Reliability
If higher drug infusion rates are used to ensure adequate anesthesia, then anesthesia depth is improved, but the risk of overdose and harmful effects increases
Solution Approach 1:
The system continuously monitors physiological parameters that indicate anesthesia depth and uses this feedback to adjust the infusion rate. By detecting when the desired anesthesia depth is achieved, the system automatically reduces the infusion rate to prevent overdose, thereby ensuring reliable anesthesia depth while minimizing harmful effects through real-time feedback-based dose optimization.
Solution Approach 2:
The system proactively prevents overdose by continuously monitoring physiological parameters and adjusting the infusion rate before harmful effects can occur. The feedback mechanism detects early signs of excessive anesthesia depth and automatically reduces the dose in advance, counteracting potential harm before it manifests, thus ensuring safety while maintaining adequate anesthesia.
Data Source
AI summary
A control system for administration of a drug comprises a drug administration actuator for administering the drug to a patient at a controllable dosage; a monitor for measuring an effect of the drug on the patient; and a controller configured to determine a control signal to the drug administration actuator; wherein the controller is configured to implement a closed loop model-predictive control scheme comprising, for each of a series of time steps, minimizing a cost function subject to one or more constraints to determine the control signal, the cost function based at least in part on a reference level and the monitor measurement; wherein the control signal is used as an input to an auxiliary model to estimate at least one concentration level of the drug in the patient; and wherein the constraints comprise at least one constraint on the estimate of the concentration level of the drug.