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Updated: Mar 31, 2026

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs
Published on: November 8, 2024
Population Pharmacokinetics of Fentanyl in the Critically Ill
Leena Choi1, Benjamin A Ferrell, Eduard E Vasilevskis
11Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN.2Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN.3Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN.4Center for Health Services Research, Vanderbilt University School of Medicine, Nashville, TN.5Geriatric Research, Education and Clinical Center Service, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN.6Division of Critical Care, Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, TN.7Anesthesia Service, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN.8Aegis Sciences Corporation, Nashville, TN.9Center for Quality Aging, Vanderbilt University School of Medicine, Nashville, TN.10Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN.11Division of Rheumatology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN.
Objective:
To characterize fentanyl population pharmacokinetics in patients with critical illness and identify patient characteristics associated with altered fentanyl concentrations.
Design:
Prospective cohort study.
Setting:
Medical and surgical ICUs in a large tertiary care hospital in the United States.
Patients:
Patients with acute respiratory failure and/or shock who received fentanyl during the first 5 days of their ICU stay.
Measurements And Main Results:
We collected clinical and hourly drug administration data and measured fentanyl concentrations in plasma collected once daily for up to 5 days after enrollment. Among 337 patients, the mean duration of infusion was 58 hours at a median rate of 100 μg/hr. Using a nonlinear mixed-effects model implemented by NONMEM, we found that fentanyl pharmacokinetics were best described by a two-compartment model in which weight, severe liver disease, and congestive heart failure most affected fentanyl concentrations. For a patient population with a mean weight of 92 kg and no history of severe liver disease or congestive heart failure, the final model, which performed well in repeated 10-fold cross-validation, estimated total clearance, intercompartmental clearance (Q), and volumes of distribution for the central (V1) and peripheral compartments (V2) to be 35 L/hr (95% CI, 32-39 L/hr), 55 L/hr (95% CI, 42-68 L/hr), 203 L (95% CI, 140-266 L), and 523 L (95% CI, 428-618 L), respectively. Severity of illness was marginally associated with fentanyl pharmacokinetics but did not improve the model fit after liver and heart diseases were included.
Conclusions:
In this study, fentanyl pharmacokinetics during critical illness were strongly influenced by severe liver disease, congestive heart failure, and weight, factors that should be considered when dosing fentanyl in the ICU. Future studies are needed to determine if data-driven fentanyl dosing algorithms can improve outcomes for ICU patients.
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