Shows the newest developments in the field of multi-parametric model predictive control and optimization and their application for drug delivery systems This book is based on the Modelling, Control and Optimization of Biomedical Systems (MOBILE) project, which was created to derive intelligent computer model-based systems for optimization of biomedical drug delivery systems in the cases of diabetes, anaesthesia, and blood cancer. These systems can ensure reliable and fast calculation of the optimal drug dosage without the need for an online computer--while taking into account the specifics and constraints of the patient model, flexibility to adapt to changing patient characteristics and incorporation of the physician's performance criteria, and maintaining the safety of the patients. Modelling Optimization and Control of Biomedical Systems covers: mathematical modelling of drug delivery systems; model analysis, parameter estimation, and approximation; optimization and control; sensitivity analysis & model reduction; multi-parametric programming and model predictive control; estimation techniques; physiologically-based patient model; control design for volatile anaesthesia; multiparametric model based approach to intravenous anaesthesia; hybrid model predictive control strategies; Type I Diabetes Mellitus; in vitro and in silico block of the integrated platform for the study of leukaemia; chemotherapy treatment as a process systems application; and more. * Introduces readers to the Modelling, Control and Optimization of Biomedical Systems (MOBILE) project * Presents in detail the theoretical background, computational tools, and methods that are used in all the different biomedical systems * Teaches the theory for multi-parametric mixed-integer programming and explicit optimal control of volatile anaesthesia * Provides an overview of the framework for modelling, optimization, and control of biomedical systems This book will appeal to students, researchers, and scientists working on the modelling, control, and optimization of biomedical systems and to those involved in cancer treatment, anaesthsia, and drug delivery systems.

Efstratios N. Pistikopoulos, PhD, Professor Pistikopoulos is the Interim Co-Director and Deputy Director of the Texas A&M Energy Institute, as well as a TEES Distinguished Research Professor in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. A Fellow of the Institution of Chemical Engineers and of the American Institute of Chemical Engineers, and the Editor-in-Chief of Computers & Chemical Engineering, Professor Pistikopoulos received the Computing in Chemical Engineering Award of the Computing and Systems Technology (CAST) Division of the American Institute of Chemical Engineers (AIChE) in 2012, the title of Doctor Honoris Causa from the University Politehnica of Bucharest in 2014, and from the University of Pannonia in 2015; and was elected Fellow of the Royal Academy of Engineering in the UK in 2013. Ioana Nascu, PhD, MEng, is a Postdoctoral Research Associate at Artie McFerrin Department of Chemical Engineering, Texas A&M University and part of the "Multi-parametric Optimization and Control Group" of Prof. E. N. Pistikopoulos. Her research interest are on the area advanced control strategies including model predictive control and multiparametric model predictive control as well as advanced estimation techniques. More specifically, her research focuses on developing advanced multiparametric optimization and control strategies for biomedical processes. Eirini G. Velliou, PhD, MEng, FHEA, is an Associate Professor of Bioprocess Engineering, Principal Investigator and founder of the Bioprocess and Biochemical Engineering Group (BioProChem) at the Department of Chemical and Process Engineering of the University of Surrey, UK. Her research focus falls within the engineering and validation of platforms for studying biological systems as influenced by environmental stress, including cancer tissue engineering and environmental (cancer cell) stress response.

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