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High-dose naloxone, an experimental tool uncovering latent sensitisation: pharmacokinetics in humans

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Vis graf over relationer

BACKGROUND: Naloxone, an opioid receptor antagonist, is used as a pharmacological tool to detect tonic endogenous activation of opioid receptors in experimental pain models. We describe a pharmacokinetic model linking naloxone pharmacokinetics to its main metabolite after high-dose naloxone infusion.

METHODS: Eight healthy volunteers received a three-stage stepwise high-dose i.v. naloxone infusion (total dose 3.25 mg kg-1). Naloxone and naloxone-3-glucuronide (N3G) plasma concentrations were sampled from infusion onset to 334 min after infusion discontinuation. Pharmacokinetic analysis was performed using non-linear mixed effect models (NONMEM). The predictive performances of Dowling's and Yassen's models were evaluated, and target-controlled infusion simulations were performed.

RESULTS: Three- and two-compartment disposition models with linear elimination kinetics described the naloxone and N3G concentration time-courses, respectively. Two covariate models were developed: simple (weight proportional) and complex (with the shallow peripheral volume of distribution linearly increasing with body weight). The median prediction error (MDPE) and wobble for Dowling's model were -32.5% and 33.4%, respectively. For Yassen's model, the MDPE and wobble were 1.2% and 19.9%, respectively.

CONCLUSIONS: A parent-metabolite pharmacokinetic model was developed for naloxone and N3G after high-dose naloxone infusion. No saturable pharmacokinetics were observed. Whereas Dowling's model was inaccurate and over-predicted naloxone concentrations, Yassen's model accurately predicted naloxone pharmacokinetics. The newly developed covariate models may be used for high-dose TCI-naloxone for experimental and clinical practice.


TidsskriftBritish Journal of Anaesthesia
Udgave nummer2
Sider (fra-til)e204-e214
StatusUdgivet - aug. 2019

Bibliografisk note

Copyright © 2018 British Journal of Anaesthesia. All rights reserved.

ID: 58926529