Modeling of drug delivery in general anesthesia

Manual or open-loop administration does not take into account patient´s individual dose or dose-response relationship; hence they represent sub-optimal solutions for optimizing individual drug titration. This may lead to under-or over- sedation, increasing the time on mechanical ventilation, the length of intensive care unit (ICU) stay and mortality. Model based predictive control can mitigate with this problem, improving the efficiency of drug delivery and patient safety. A multiple-input single-output (MISO) patient model is identified and validated in this paper. The inputs are two drugs commonly used for general anesthesia, propofol and remifentanil, and the output is the Bispectral Index (BIS). Wavelet time-frequency analysis was used to filter the measured signals. The parameters of the interaction model which relates the effect-site concentrations of these drugs to BIS are identified based on least-squares algorithm, using data from real-life clinical tests.