Fuzzy logic for model adaptation of a pharmacokinetic-based closed loop delivery system for pancuronium

In this paper, we investigate the ability of fuzzy logic to adapt the parameters of a pharmacokinetic and pharmacodynamic model-based controller for the delivery of the muscle relaxant pancuronium. The system uses the model to control the rate of drug delivery and uses feedback from a sensor which measures muscle relaxation level to adapt the model using fuzzy logic. The control strategy administers mini-bolus doses of pancuronium and modulates the magnitude and time interval between the bolus doses to maintain a patient's muscle relaxation within an allowable range specified by the user. Before each new dose is given, the fuzzy logic adaptation scheme uses the error between the predicted patient response and the measured response to adapt the model. The system was tested using computer simulation by varying the parameters of the model by 50% from their nominal values. It was also evaluated in a clinical trial of five patients undergoing surgical procedures lasting 5 h or longer.