Predicting neonatal pharmacokinetics from prior data using population pharmacokinetic modeling

J Clin Pharmacol. 2015 Oct;55(10):1175-83. doi: 10.1002/jcph.524. Epub 2015 Jun 9.

Abstract

Selection of the first dose for neonates in clinical trials is very challenging. The objective of this analysis was to assess if a population pharmacokinetic (PK) model developed with data from infants to adults is predictive of neonatal clearance and to evaluate what age range of prior PK data is needed for informative modeling to predict neonate exposure. Two sources of pharmacokinetic data from 8 drugs were used to develop population models: (1) data from all patients > 2 years of age, and (2) data from all nonneonatal patients aged > 28 days. The prediction error based on the models using data from subjects > 2 years of age showed bias toward overprediction, with median average fold error (AFE) for CL predicted/CLobserved greater than 1.5. The bias for predicting neonatal PK was improved when using all prior PK data including infants as opposed to an assessment without infant PK data, with the median AFE 0.91. As an increased number of pediatric trials are conducted in neonates under the Food and Drug Administration Safety and Innovation Act, dose selection should be based on the best estimates of neonatal pharmacokinetics and pharmacodynamics prior to conducting efficacy and safety studies in neonates.

Keywords: neonates; pharmacokinetics; population PK.

MeSH terms

  • Child, Preschool
  • Humans
  • Infant
  • Models, Biological*
  • Pharmaceutical Preparations / metabolism
  • Pharmacokinetics*

Substances

  • Pharmaceutical Preparations