title: Potential benefit of Bayesian forecasting for therapeutic drug monitoring in neonates.
abstract: Therapeutic drug monitoring in neonate has been hampered by invasiveness of blood samplings raising ethical problems. A methodologic approach has been developped in adults and in children that is still unsufficiently developped in neonates, the Bayesian forecasting of drug plasma concentration. This method is particularly attractive in neonates using a few blood samples from an individual patient and more informations from a prior patient sample representative of the population the individual patient belongs to. The present article aims at reviewing the different procedures and methods to minimize invasiveness during therapeutic drug monitoring in neonate and at reviewing the methods for improving the quality of different dose adjustments using a Bayesian approach.
authors.affiliation: Perinatal and Pediatric Pharmacology, Saint-Vincent de Paul Hospital, René Descartes University, Paris, France. gerard.pons@svp.ap-hop-paris.fr
authors.forename: Gérard
authors.initials: G
authors.lastname: Pons
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Tréluyer
authors.forename: Jérôme
authors.initials: J
authors.lastname: Dimet
authors.forename: Yann
authors.initials: Y
authors.lastname: Merlé
mesh_terms: D001499:Bayes Theorem; D016903:Drug Monitoring / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D007231:Infant, Newborn; D004364:Pharmaceutical Preparations / Q000008:administration & dosage
chemical_list: D004364:Pharmaceutical Preparations