Project description DEENESFRITPL Computer-controlled anaesthesia Administration of drugs during surgical anaesthesia occurs manually by the anesthesiologist, who takes into account very specific physiological parameters and expected patient response to surgical stimuli. In complex situations, though, involving patient comorbidities or drug antagonism, optimisation of drug infusion rate seems impossible. The key objective of the AMICAS project, funded by the European Research Council, is to pave the way towards computer-assisted drug optimisation using multivariable models. The idea is to combine these models with human expertise for reducing as much as possible the large uncertainties in patient response under anaesthesia and improving surgical outcomes. Show the project objective Hide the project objective Objective A major challenge in anesthesia is to adapt the drug infusion rates from observed patient response to surgical stimuli. The 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. 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, a mature methodology in systems and control engineering with potential to faster recovery times and lower risk of complications. The goal of this proposal 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. I plan 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. I am convinced that integration of human expertise with computer optimization is a successful solution for breakthrough into clinical practice. Fields of science engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systemsmedical and health sciencesclinical medicinesurgeryengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol engineering Keywords multivariable control model uncertainty convolutional neural networks predictive control interaction anomalous diffusion drug effect general anesthesia cardiac surgery human expertise Programme(s) HORIZON.1.1 - European Research Council (ERC) Main Programme Topic(s) ERC-2021-COG - ERC CONSOLIDATOR GRANTS Call for proposal ERC-2021-COG See other projects for this call Funding Scheme HORIZON-ERC - HORIZON ERC Grants Host institution UNIVERSITEIT GENT Net EU contribution € 1 927 325,00 Address SINT PIETERSNIEUWSTRAAT 25 9000 Gent Belgium See on map Region Vlaams Gewest Prov. Oost-Vlaanderen Arr. Gent Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 927 325,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all UNIVERSITEIT GENT Belgium Net EU contribution € 1 927 325,00 Address SINT PIETERSNIEUWSTRAAT 25 9000 Gent See on map Region Vlaams Gewest Prov. Oost-Vlaanderen Arr. Gent Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 927 325,00
