Drug co-administration in anesthesia using event-based MPC

In this article, a predictive event-based control architecture for multivariable drug infusion in the anesthesia process is presented. The control scheme considers a multiple-input single-output process, where the depth of hypnosis is the controlled variable and the infusion rates of propofol and remifentanil, which are co-administered by imposing a fixed ratio between them, are the control variables. The control system is built on the top of a nonlinear pharmacokinetic/pharmacodynamic model for drug co-administration that reflects the super-additive effect of both drugs on the bispectral index scale (BIS), which is a measure of the hypnotic state of the patient. Further, in order to compensate the nonlinear behavior of the system, it exploits an external predictor that is designed to increase the robustness to inter-/intra-patient variability. The overall controller parameters are tuned by applying an optimization method on a representative set of virtual patients. The main feature of the proposed control algorithm consists in its asynchronous execution, which can be beneficial in reducing control signal changes due to the noisy measurements of the BIS. The evaluation of the analyzed control architecture through a simulation study reveals that control action variations can be reduced by about 48% on average with respect to its time-based counterpart. This reduction is obtained at the expense of a lower control accuracy, resulting in a degradation of 18% in terms of integrated absolute error. Results are acceptable from a clinical practice perspective proving that the proposed approach is a feasible alternative to classical time-based predictive controllers.