Descrizione del progetto
Anestesia computerizzata
La somministrazione di farmaci nel corso dell’anestesia chirurgica è effettuata manualmente dall’anestesista, che prende in considerazione parametri fisiologici molto specifici e le previsioni di risposta del paziente agli stimoli chirurgici. In situazioni complesse, tuttavia, in cui nel paziente sono presenti patologie concomitanti o antagonismo farmacologico, ottimizzare la velocità di infusione dei farmaci sembra impossibile. L’obiettivo principale del progetto AMICAS, finanziato dal Consiglio europeo della ricerca, è quello di spianare la strada a un’ottimizzazione dei farmaci assistita dal computer mediante l’impiego di modelli multivariabili. L’idea è quella di combinare questi modelli con le competenze umane allo scopo di ridurre il più possibile le grandi incertezze che caratterizzano la risposta del paziente sotto anestesia, migliorando così gli esiti chirurgici.
Obiettivo
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.
Campo scientifico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- medical and health sciencesclinical medicinesurgery
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol engineering
Parole chiave
Programma(i)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-ERC - HORIZON ERC GrantsIstituzione ospitante
9000 Gent
Belgio