title: Population pharmacokinetic analysis of netilmicin in neonates and infants with use of a nonparametric method.
abstract: BACKGROUND
  Although the therapeutic and toxic effects of netilmicin are related to its plasma concentration, its pharmacokinetics in neonates and infants and the influence of clinical and biological variables have been only partially assessed.
  
  
  METHODS
  Therapeutic drug monitoring data collected from 186 neonates and 95 infants receiving netilmicin were analyzed with a nonparametric population approach. The influence of gestational and postnatal age, weight, Apgar score, and creatinine and urea plasma concentrations on the pharmacokinetic parameters was assessed. The neonate and infant groups were each randomly divided into a learning sample and a validation sample. The population analysis was performed on each learning subgroup with the nonparametric maximum likelihood (NPML) method. In the validation group, the data were used to assess the concentration predictability. Because there is no specific netilmicin formulation for neonates and infants, an error model was proposed to account for errors attributable to dilution processes when preparing the infusion.
  
  
  RESULTS
  In neonates, the covariates that reduced expected variance of plasma clearance by more than 10% were postnatal age, body weight, and plasma creatinine, as well as plasma urea and creatinine in infants. Body weight and sex played a significant role in explaining the variability of the volume of distribution. The accuracy of the concentration predictability assessed in the validation samples was satisfactory, and no significant bias was found.
  
  
  CONCLUSIONS
  These findings help explain the large interindividual variability of the pharmacokinetics of netilmicin and the influence of the clinical and laboratory covariates in neonates and infants.
authors.affiliation: Pharmacologie Périnatale et Pédiatrique, Université René-Descartes, Hôpital Saint Vincent de Paul, and INSERM U346, CHU Pitié-Salpétrière, Paris, France. jim.treluyer@svp.ap-hop-paris.fr
authors.forename: J M
authors.initials: JM
authors.lastname: Tréluyer
authors.forename: Y
authors.initials: Y
authors.lastname: Merlé
authors.forename: A
authors.initials: A
authors.lastname: Semlali
authors.forename: G
authors.initials: G
authors.lastname: Pons
mesh_terms: D000367:Age Factors; D000704:Analysis of Variance; D001034:Apgar Score; D001499:Bayes Theorem; D003404:Creatinine / Q000097:blood; D005260:Female; D005839:Gentamicins / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D005865:Gestational Age; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007262:Infusions, Intravenous; D008297:Male; D009428:Netilmicin / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D011159:Population Surveillance; D015203:Reproducibility of Results; D018709:Statistics, Nonparametric; D014508:Urea / Q000097:blood
chemical_list: D005839:Gentamicins; D009428:Netilmicin; D014508:Urea; D003404:Creatinine