Modelling and multi-parametric control for delivery of anaesthetic agents

Abstract

This article presents model predictive controllers (MPCs) and multi-parametric model-based controllers for delivery of anaesthetic agents. The MPC can take into account constraints on drug delivery rates and state of the patient but requires solving an optimization problem at regular time intervals. The multi-parametric controller has all the advantages of the MPC and does not require repetitive solution of optimization problem for its implementation. This is achieved by obtaining the optimal drug delivery rates as a set of explicit functions of the state of the patient. The derivation of the controllers relies on using detailed models of the system. A compartmental model for the delivery of three drugs for anaesthesia is developed. The key feature of this model is that mean arterial pressure, cardiac output and unconsciousness of the patient can be simultaneously regulated. This is achieved by using three drugs: dopamine (DP), sodium nitroprusside (SNP) and isoflurane. A number of dynamic simulation experiments are carried out for the validation of the model. The model is then used for the design of model predictive and multi-parametric controllers, and the performance of the controllers is analyzed.

Optimal model‐based control of non‐viral siRNA delivery

“…A literature survey revealed that while a number of research works have been done on model‐based control of drug delivery (Dua, Dua, & Pistikopoulos, ), very little thought had been given to the development of control strategies for gene delivery systems (Dua, ; Jamili & Dua, ; Ma & Zhang, ). This paper presents the mathematical modeling, simulation and control of the dynamic process of non‐viral siRNA delivery.…”

“…However, no effort has been made to develop a holistic framework that is applicable for in vivo gene therapy, and provides a model-based decision-making platform taking into account the main multi-objective optimization issues, which consequently forms the main objective of this paper. A literature survey revealed that while a number of research works have been done on model-based control of drug delivery (Dua, Dua, & Pistikopoulos, 2010), very little thought had been given to the development of control strategies for gene delivery systems (Dua, 2012;Jamili & Dua, 2016;Ma & Zhang, 2009). This paper presents the mathematical modeling, simulation and control of the dynamic process of non-viral siRNA delivery.…”

Optimal drug infusion profiles using a Particle Swarm Optimization algorithm

“…For example, Yelneedi et al (2009a,b) evaluated the robustness of advanced control strategies for the regulation of hypnosis with propofol in a broad range of patients. In general, the most popular control strategies considered are (Dua and Pistikopoulos, 2010;Gentilini et al, 2001;Gopinath et al, 1995;Isaka and Sebald, 1993;Kwok et al, 1997;Rao et al, 2000;Uemura et al, 2006;Yu et al, 1992): multirate model predictive control, model predictive control, cascade internal model control and multi-parametric model based control, among others. Model based controllers use non-linear physiological models to simulate human processes such as blood circulation, respiration and distribution of substances among the organs (Yelneedi et al, 2009a,b;Yu et al, 1992).…”

“…The performance criteria commonly adopted is the minimization of the settling times of the variables of interest. Some of the controllers have been tested with relative success on animals and on patients undergoing a specific disease (Dua and Pistikopoulos, 2010;Gentilini et al, 2001;Gopinath et al, 1995).…”

Probing nanoantenna-directed photothermal destruction of tumors using noninvasive laser irradiation

“…17 We solve the governing differential equation by adopting the Finite Volume Method for spatial discretization and fully implicit approach for temporal discretization. We take the temperature and location dependence of the blood perfusion into account by considering w b = f͑a , b͒, where the forms of the function f over different temperature ranges, as well as values of the parameter a and b are given in Table I.…”