Clara-Mihaela Ionescu - AMICAS

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Clara Mihaela Ionescu is professor at Faculty of Engineering and Architecture, at Ghent University, Belgium since October 2016. She is a research-member of the laboratory of Dynamical Systems and Control. She holds a master degree is Automation and Applied Informatics in 2003 from Dunarea de Jos University of Galati, Romania, and a PhD degree in Biomedical Engineering from Ghent University in 2009. She was recipient of prestigious excellence scholarship for top-students going abroad from the Romanian Ministry of Research and Innovation during her master Studies at Ghent University in 2002. She was also recipient of prestigious excellent post-doctoral scholarship of Flemish Research Foundation, of Belgium for 6 years, from 2011 - 2017.

She is an ERC Consolidator Grant fellow: AMICAS, Adaptive Multi-Drug Infusion Control System for General Anesthesia during Major Surgery.

She is member of several valorization and innovation platforms in Belgium: Flanders Make, Centre for Sustainable Pharmaceutical Engineering, etc. She has more than 100 scientific publications in Web of Science with h-index of 31, and equal number of indexed conference proceedings. She is a IFAC TC member of TC 2.1, 6.4, 8.2, all involving modelling, identification, tuning and optimal control of chemical, biological, medical processes.

She organized two IFAC conferences: Advances in PID control in 2018 and Biology and Medical Systems in 2021. Her research interests include fractional order systems modelling and control, predictive control and related multi-objective optimization algorithms. Application areas are prevalent in biomedical systems, chemical and manufacturing processes.

Project description

During past decennia, the PI has identified major challenges in anesthesia, with foremost troublesome to adapt the drug infusion rates from observed patient response to surgical stimuli. This is due to the fact that current patient models are based on nominal population characteristic response and lack specific surgical effects. In major surgery (e.g. cardiac, transplant, obese patients) modelling uncertainty stems from significant blood losses, anomalous drug diffusion, drug effect synergy/antagonism, anesthetic-hemodynamic interactions, etc. This complex optimisation problem requires superhuman abilities of the anesthesiologist.

Computer controlled anesthesia holds the answer to be the game changer for best surgery outcomes and AMICAS is here to enable this paradigm shift. Although few, clinical studies report that computer based anesthesia for one or two drugs outperforms manual management. In reality, clinical practice mitigates a multi-drug optimization problem while accommodating large patient model uncertainty. The anesthesiologist makes decisions based on future surgeon actions and expected patient response. This is a predictive control strategy, where the PI has vast experience and Ghent University pioneered a mature predictive methodology in systems and control engineering.

The goal of AMICAS is to advance the scope and clinical use of computer based constrained optimization of multi-drug infusion rates for anesthesia with strong effects on hemodynamics. We aim to identify multivariable models and minimize the large uncertainties in patient response. With adaptation mechanisms from nominal to individual patient models, we design multivariable optimal predictive control methodologies to manage strongly coupled dynamics. To maximize performance of the closed loop, we model the surgical stimulus as a known disturbance signal and additional bolus infusions from anesthesiologist as known inputs.

Integration of human expertise with computer optimization is the key to a successful solution for breakthrough into clinical practice in computer guided anesthesia.

Objectives

  • to provide a safe, trustful and personalised decision making system with computer based optimization of multi-drug infusion systems in general anesthesia
  • to digitalise surgery protocols and clinical expertise in a usable format by the computer optimization
  • to provide to the interdisciplinary community of medical and engineering worlds a patient simulator for stimulating design, creativity and endorsement of control strategies relevant to clinical practice
  • to validate the developed solutions into clinical environment (clinical trials)

Role of Ghent University

UGent is the host institution for this project, endorsing groundbreaking research and providing full administrative and infrastructure support, with special care for psychosocial well-being environment of its employees.

Website

AMICAS

Contact

Prof. Dr. Clara-Mihaela Ionescu
Department of Electromechanical, Systems and Metal Engineering
e-mail