Model predictive control using MISO approach for drug co-administration in anesthesia. (September 2022)

• Record Type: Journal Article
• Authors: Pawłowski, Andrzej; Schiavo, Michele; Latronico, Nicola; Paltenghi, Massimiliano; Visioli, Antonio
• Is Part Of: Journal of process control. Volume 117(2022)
• Page Start: 98
• Page End: 111
• Publication Date: 2022-09
• Subjects: Anesthesia control -- Drug co-administration -- Model predictive control -- PK/PD model -- Tuning -- Robustness; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.07.007
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: In this paper, a model predictive control system for the depth of hypnosis is proposed and analyzed. This approach considers simultaneous co-administration of the hypnotic and analgesic drugs and their effect on the Bispectral Index Scale (BIS). The control scheme uses the nonlinear multiple-input–single-output (MISO) model to predict the remifentanil influence over the propofol hypnotic effect. Then, it exploits a generalized model predictive control algorithm and a ratio between the two drugs in order to provide the optimal dosage for the desired BIS level, taking into account the typical constraints of the process. The proposed approach has been extensively tested in simulation, using a set of patients described by realistic nonlinear pharmacokinetic/pharmacodynamic models, which are representative of a wide population. Additionally, an exhaustive robustness evaluation considering inter- and intra-patient variability has been included, which demonstrates the effectiveness of the analyzed control structure. Highlights: We present MISO MPC-based scheme for drug co-administration in general anesthesia. The control scheme is based on external predictor to compensate process nonlinearity. The performance and the robustness are evaluated for inter/intra-patient variability.