Presenter Information

Jason C. Huang, University of Utah

Location

Virtual

Start Date

5-10-2021 9:25 AM

End Date

5-10-2021 9:35 AM

Description

Our group is investigating the antidepressant effects of high-dose propofol, but dosing propofol to induce standardized changes in EEG activity (“burst suppression”) is challenging due to limited knowledge of each subject’s pharmacokinetics (PK) and pharmacodynamics (PD). In this paper, we approximated PK-PD models for propofol-induced burst suppression (PIBS), based on multiple subjects over repeated treatments. We then applied these models to predict BSR in each subject’s repeated treatment, then evaluate their predictive performances. We hypothesized that predicting BSR from a greater number of previous treatments would improve performance, but our current results are not conclusive enough to validate the hypothesis. We discuss our contributions, limitations, and adjustments for future studies.

Available for download on Tuesday, May 10, 2022

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May 10th, 9:25 AM May 10th, 9:35 AM

Predicting Propofol-Induced Burst Suppression Using an Individualized Model-Based Approach Over Repeated Treatments

Virtual

Our group is investigating the antidepressant effects of high-dose propofol, but dosing propofol to induce standardized changes in EEG activity (“burst suppression”) is challenging due to limited knowledge of each subject’s pharmacokinetics (PK) and pharmacodynamics (PD). In this paper, we approximated PK-PD models for propofol-induced burst suppression (PIBS), based on multiple subjects over repeated treatments. We then applied these models to predict BSR in each subject’s repeated treatment, then evaluate their predictive performances. We hypothesized that predicting BSR from a greater number of previous treatments would improve performance, but our current results are not conclusive enough to validate the hypothesis. We discuss our contributions, limitations, and adjustments for future studies.