title: Predictive performance of a recently developed population pharmacokinetic model for morphine and its metabolites in new datasets of (preterm) neonates, infants and children.
abstract: OBJECTIVE
  Model validation procedures are crucial when models are to be used to develop new dosing algorithms. In this study, the predictive performance of a previously published paediatric population pharmacokinetic model for morphine and its metabolites in children younger than 3 years (original model) is studied in new datasets that were not used to develop the original model.
  
  
  METHODS
  Six external datasets including neonates and infants up to 1 year were obtained from four different research centres. These datasets contained postoperative patients, ventilated patients and patients on extracorporeal membrane oxygenation (ECMO) treatment. Basic observed versus predicted plots, normalized prediction distribution error analysis, model refitting, bootstrap analysis, subpopulation analysis and a literature comparison of clearance predictions were performed with the new datasets to evaluate the predictive performance of the original morphine pharmacokinetic model.
  
  
  RESULTS
  The original model was found to be stable and the parameter estimates were found to be precise. The concentrations predicted by the original model were in good agreement with the observed concentrations in the four datasets from postoperative and ventilated patients, and the model-predicted clearances in these datasets were in agreement with literature values. In the datasets from patients on ECMO treatment with continuous venovenous haemofiltration (CVVH) the predictive performance of the model was good as well, whereas underprediction occurred, particularly for the metabolites, in patients on ECMO treatment without CVVH.
  
  
  CONCLUSIONS
  The predictive value of the original morphine pharmacokinetic model is demonstrated in new datasets by the use of six different validation and evaluation tools. It is herewith justified to undertake a proof-of-principle approach in the development of rational dosing recommendations - namely, performing a prospective clinical trial in which the model-based dosing algorithm is clinically evaluated.
authors.affiliation: Division of Pharmacology, LeidenAmsterdam Center for Drug Research, Leiden, The Netherlands.
authors.forename: Elke H J
authors.initials: EH
authors.lastname: Krekels
authors.forename: Joost
authors.initials: J
authors.lastname: DeJongh
authors.forename: Richard A
authors.initials: RA
authors.lastname: van Lingen
authors.forename: Caroline D
authors.initials: CD
authors.lastname: van der Marel
authors.forename: Imti
authors.initials: I
authors.lastname: Choonara
authors.forename: Anne M
authors.initials: AM
authors.lastname: Lynn
authors.forename: Meindert
authors.initials: M
authors.lastname: Danhof
authors.forename: Dick
authors.initials: D
authors.lastname: Tibboel
authors.forename: Catherijne A J
authors.initials: CA
authors.lastname: Knibbe
mesh_terms: D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D009020:Morphine / Q000493:pharmacokinetics*; D009022:Morphine Derivatives / Q000378:metabolism; D015203:Reproducibility of Results
chemical_list: D009022:Morphine Derivatives; C035349:morphine-6-glucuronide; D009020:Morphine; C018108:morphine-3-glucuronide