• Douglas J Eleveld, Johannes H Proost, Luis I Cortínez, Anthony R Absalom, and Michel M R F Struys.
• From the *Department of Anesthesiology, University Medical Center Groningen, University of Groningen, The Netherlands; †Departmento de Anestesiología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; and ‡Department of Anesthesia, Ghent University, Gent, Belgium.
• Anesth. Analg.. 2014 Jun 1;118(6):1221-37.

BackgroundPharmacokinetic (PK) models are used to predict drug concentrations for infusion regimens for intraoperative displays and to calculate infusion rates in target-controlled infusion systems. For propofol, the PK models available in the literature were mostly developed from particular patient groups or anesthetic techniques, and there is uncertainty of the accuracy of the models under differing patient and clinical conditions. Our goal was to determine a PK model with robust predictive performance for a wide range of patient groups and clinical conditions.MethodsWe aggregated and analyzed 21 previously published propofol datasets containing data from young children, children, adults, elderly, and obese individuals. A 3-compartmental allometric model was estimated with NONMEM software using weight, age, sex, and patient status as covariates. A predictive performance metric focused on intraoperative conditions was devised and used along with the Akaike information criteria to guide model development.ResultsThe dataset contains 10,927 drug concentration observations from 660 individuals (age range 0.25-88 years; weight range 5.2-160 kg). The final model uses weight, age, sex, and patient versus healthy volunteer as covariates. Parameter estimates for a 35-year, 70-kg male patient were: 9.77, 29.0, 134 L, 1.53, 1.42, and 0.608 L/min for V1, V2, V3, CL, Q2, and Q3, respectively. Predictive performance is better than or similar to that of specialized models, even for the subpopulations on which those models were derived.ConclusionsWe have developed a single propofol PK model that performed well for a wide range of patient groups and clinical conditions. Further prospective evaluation of the model is needed.

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