Evaluates a new LC-MS/MS assay for quantifying propofol during major noncardiac surgery, suggesting improvement in dosing algorithms.
Background: Propofol is a widely used anesthetic agent, yet it exhibits substantial interindividual variability in dosage requirements—likely driven by pharmacokinetic and/or pharmacodynamic factors. Despite ongoing efforts, accurate population-based pharmacokinetic–pharmacodynamic dosing algorithms, targeting plasma propofol concentrations, remain suboptimal. Reliable, high throughput and cost-efficient bioanalytical methods are required to quantify plasma propofol concentrations in large-scale clinical pharmacokinetic–pharmacodynamic studies to improve these algorithms. A review of the existing literature indicated an absence of liquid chromatography - tandem mass spectrometry (LC-MS/MS) assays suitable for this purpose. Methods: The authors developed, optimized, validated, and clinically applied a new bioanalytical method using protein precipitation and LC-MS/MS quantification. Results: The assay demonstrated intra- and inter-run assay accuracy of 86%–114% and 94%–105%, respectively, across the quantification range of 25–5000 ng/mL. Intra- and inter-run coefficients of variation were 2.7%–15.7% and 1.1%–5.0%, respectively. Propofol extraction recovery was 92%, with a total run-time of 5.5 minutes. This method demonstrated acceptable performance for dilution integrity, matrix effects, and stability under bench-top, freeze–thaw, autosampler, and long-term storage conditions, as well as reinjection reproducibility. This method was subsequently applied to quantify plasma propofol concentrations in a patient undergoing major noncardiac surgery, assessing the corresponding concentration–time profile. All measured propofol concentrations (648–4356 ng/mL) were within the validated assay quantification range. Conclusions: The authors report a robust and efficient LC–MS/MS assay for propofol that was optimized, validated, and shown to be suitable for large-scale clinical pharmacokinetic studies. This fit-for-purpose method supports population pharmacokinetic modelling to inform more individualized dosing strategies.
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