title: Population clinical pharmacology of children: modelling covariate effects.
abstract: BACKGROUND
  Population modelling using mixed effects models provides a means to study variability in paediatric drug responses among individuals representative of those in whom the drug will be used clinically.
  
  
  CONCLUSIONS
  Explanatory covariates explain the predictable part of the between-individual variability. Growth and development are two major aspects of children not seen in adults. These aspects can be investigated by using size and age as covariates. Problems attributable to co-linearity can be approached by using size as the first covariate. Size standardisation is achieved using allometric scaling, a mechanistic approach that has a strong theoretical and empirical basis. Age is used to describe the maturation of clearance. The quantitative models (linear, exponential, first-order, variable slope sigmoidal) used to describe this maturation process vary depending on the span of the ages under investigation. Measures of response are not always straightforward and can be more difficult to quantify in children.
  
  
  CONCLUSIONS
  Covariate investigation in children is improving the understanding of developmental aspects of drug disposition and effects in the paediatric population, ultimately leading to more effective use of medications.
authors.affiliation: Department of Anaesthesiology, University of Auckland, Auckland, New Zealand. briana@adhb.govt.nz
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Anderson
authors.forename: Karel
authors.initials: K
authors.lastname: Allegaert
authors.forename: Nicholas H G
authors.initials: NH
authors.lastname: Holford
mesh_terms: D001830:Body Surface Area; D001835:Body Weight; D002648:Child; D003404:Creatinine / Q000097:blood; D005919:Glomerular Filtration Rate; D006801:Humans; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D010599:Pharmacokinetics; D010600:Pharmacology
chemical_list: D003404:Creatinine