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Pain control in infants is an important clinical concern, with potential long-term adverse neurodevelopmental effects. Intravenous morphine is routinely administered for postoperative pain management; however, its dose-concentration-response relationship in neonates and infants has not been well characterized. Although the current literature provides dosing guidelines for the average infant, it fails to control for the large unexplained variability in morphine clearance and response in individual patients. Bayesian estimation can be used to control for some of this variability. The authors aimed to evaluate morphine pharmacokinetics (PKs) and exposure in critically ill neonates and infants receiving standard-of-care morphine therapy and compare a population-based approach to the model-informed Bayesian techniques.

Model-Informed Bayesian Estimation Improves the Prediction of Morphine Exposure in Neonates and Infants