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Adaptive Multi-Drug Infusion Control System for General Anesthesia in Major Surgery

Project description

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.

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.

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Topic(s)

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2021-COG

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Host institution

UNIVERSITEIT GENT
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 927 325,00
Address
SINT PIETERSNIEUWSTRAAT 25
9000 GENT
Belgium

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Region
Vlaams Gewest Prov. Oost-Vlaanderen Arr. Gent
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 927 325,00

Beneficiaries (1)

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