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The AMICAS (Adaptive Multi-drug Infusion Control system for general Anesthesia in major Surgery) project integrates human expertise with computer optimization to create a successful solution for breakthrough into clinical practice

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Centre of Excellence in Computer Assisted Systems for Drug Dosing Control and Optimisation

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Key challenges addressed.

The ERC AMICAS project proposes an Adaptive Multi-drug Infusion Control system for general Anesthesia in major Surgery. A major challenge in anesthesia is to adapt the drug infusion rates from observed patient response to surgical actions. The patient models are based on nominal population characteristic response and lack specific surgical effects. In major surgery (for instance, cardiac, transplant, bariatric surgery) modelling uncertainty arises from significant blood losses, anomalous drug diffusion, drug effect synergy/antagonism, anesthetic-hemodynamic interactions, etc. This complex interplay requires superhuman abilities of the anesthesiologist, acquired along many years of training and practice. How can we mimic this large amount of expertise? How to provide support for their critical decisions? .

Computer controlled anesthesia holds the answer to be the game changer for best surgery outcomes. Although few, clinical studies report that computer-based anesthesia for one or two drugs outperforms manual management. In reality, clinical practice performs a multi-drug optimization problem while mitigating large patient model uncertainty. The anesthesiologist makes decisions based on future surgeon actions and expected patient response. This is a predictive control strategy, a mature methodology in systems and control engineering with great potential to induce faster recovery times and lower the risk of post-surgery complications.

The interdisciplinary team of AMICAS aims to advance the scope and clinical use of computer based constrained optimization of multi-drug infusion rates for anesthesia with strong effects on hemodynamics. In doing so, we 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 occurring in patient’s vital signs during major surgery. Ultimately, to maximize the performance of the closed loop, we model the surgical stimulus as a known disturbance signal and additional bolus infusions from anesthesiologist as known inputs.


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Who we are


Principal Investigator

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.


Dana Copot

FWO Postdoctoral Researcher

Senior postdoctoral research with 10 years experience in control. In the last 3 years I have developed the open source patient simulator. This is a versatile and complete simulation environment for test and evaluation of different control strategies.

Update the patients simulator with new features.


Erhan Yumuk

Postdoctoral Researcher

A dedicated researcher and lecturer with nine years of experience in Control Engineering area. Willing to expand the scientific horizon by studying various control strategies as well as to contribute to the research project's goals

Develop and test control strategies on anesthesia and hemodynamic systems

Ghada Ben Othman

PhD Researcher

Motivated and dedicated PhD researcher working on artifical inteligence algorithms for scarce data. Eager to make great progess in the development of methodlogies for objective pain assesement.

I will focus on the development of artificial inteligence algorithms for pain prediction.

Hamed Farbakhsh

PhD Researcher

Motivated and dedicated PhD researcher in the field of control engineering. Eager to make great progess in terms of development of control algorithms for optimal drug dosing problems.

I will focus on the implementation on the bechmark patient simulator of the new models and control strategies.

Amani Rayene Ynineb

PhD Researcher

Motivated and dedicated PhD researcher working on modelisation and control of the hemodynamic system in TIVA. Eager to make great progess in terms of development of control algorithms for optimal drug dosing problems.

I will focus on the development of model predictive controller for the hemodynamic drug administration.


Objective 1

Design and validate a time-and-data efficient online estimation of a patient-based model to include cardiovascular system dynamical changes with predictable disturbance profiles.

Objective 2

Design and validate a stable control methodology and algorithm for optimal multi-drug infusion rates to mitigate strong dynamic interactions and model uncertainty

Objective 3

Provide a trusted, integrated technological solution for computerized anesthesia in clinical trials.


Martine Neckebroek

Doctor specialist

An anesthetist at Ghent University Hospital, specializing in intensive care anesthesia and pediatric anesthesia

Antonio Visioli


Holds a full professor position in Control Systems at the Department of Mechanical and Industrial Engineering of the University of Brescia. He is a senior member of IEEE, the chair of the IFAC Technical Committee on Education, a member of the Technical Committee on Education of the IEEE Control Systems Society, the secretary of the subcommittee on Industrial Automated Systems and Control of the IEEE Industrial Electronics Society Technical Committee on Factory Automation.

Nicola Latronico

Professor, MD

Professor of Anesthesia and Critical Care, University of Brescia, Head of Department of Medical and Surgical Specialties Radiological Sciences and Public Health

Mirko Fiacchini

PhD Researcher

Researcher in CNRS - HDR GIPSA-lab, Control Systems Department

Isabela Birs

Postdoctoral Researcher

Isabela Birs is currently a postdoc BOF researcher at Ghent University. She has a PhD in the field of modeling and control of non-Newtonian fluids with multi-industry applicability. Her main research focus is fractional order systems, event-based fractional order control, advanced control strategies and biomedical systems.

Cristina Muresan


Full professor at the Technical University of Cluj-Napoca, Romania, with approximately 15 years experience in controlling multivariable time delay systems. Passionate on developing and implementing new fractional order control algorithms. Current focus on the design and analysis of fractional order controllers for the combined anesthesia and hemodynamic system.

Cosmin Copot

Senior Researcher

Expert in development of dynamical models for control systems with interdisciplinary applications. He has vast experience in image based methodologies (using AI tools) with applicability in both technical and biomedical applications. His knowledge will be employed to achieve the exploratoryt research objectives within this project


The patient simulator platform is designed through an interdisciplinary combination of medical, clinical practice and systems engineering expertise gathered in the last decades by our team. The result is an open source patient simulator in Matlab/Simulink from Mathworks(R). Simulator features include complex synergic and antagonistic interaction aspects between general anesthesia and hemodynamic stabilization variables. The anesthetic system includes the hypnosis, analgesia and neuromuscular blockade states, while the hemodynamic system includes the cardiac output and mean arterial pressure. Nociceptor stimulation is also described and acts as a disturbance together with predefined surgery profiles from a translation into signal form of most commonly encountered events in clinical practice. A broad population set of pharmacokinetic and pharmacodynamic (PKPD) variables are available for the user to describe both intra- and inter-patient variability. This simulator has some unique features, such as: i) additional bolus administration from anesthesiologist, ii) variable time-delays introduced by data window averaging when poor signal quality is detected, iii) drug trapping from heterogeneous tissue diffusion in high body mass index patients. We successfully reproduced the clinical expected effects of various drugs interacting among the anesthetic and hemodynamic states. Our work is uniquely defined in current state of the art and first of its kind for this application of dose management problem in anesthesia. This simulator provides the research community with accessible tools to allow a systematic design, evaluation and comparison of various control algorithms for multi-drug dosing optimization objectives in anesthesia.

Detailed description of the open source patient simulator can be found here

Citation disclaimer: If you use this simulator please cite the paper bellow

C. M. Ionescu, M. Neckebroek, M. Ghita and D. Copot, An Open Source Patient Simulator for Design and Evaluation of Computer Based Multiple Drug Dosing Control for Anesthetic and Hemodynamic Variables,

IEEE Access, vol. 9, pp. 8680-8694, 2021, doi: 10.1109/ACCESS.2021.3049880.


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