Population pharmacokinetics of phenytoin in critically ill children

Stefanie Hennig1, Ross Norris1,2,3, Quyen Tu4

  • 1School of Pharmacy, Pharmacy Australia Centre of Excellence (PACE), The University of Queensland, Brisbane, Queensland, Australia.

Insights

This study models phenytoin pharmacokinetics in critically ill children, finding that weight and albumin levels impact drug binding. This helps predict unbound phenytoin levels for better dosing in pediatric intensive care.

Area of Science:

  • Pharmacology
  • Pediatric Critical Care Medicine
  • Pharmacokinetics

Background:

  • Phenytoin is an anticonvulsant commonly used in critically ill children.
  • Understanding phenytoin pharmacokinetics, including protein binding, is crucial for effective therapeutic drug monitoring.
  • Variability in protein binding can affect phenytoin efficacy and toxicity in pediatric patients.

Purpose of the Study:

  • To characterize the population pharmacokinetics of bound and unbound phenytoin in critically ill children.
  • To investigate factors influencing phenytoin's protein binding profile in this population.
  • To develop a model for predicting unbound phenytoin concentrations.

Main Methods:

  • Population pharmacokinetic analysis of paired unbound and total phenytoin plasma concentrations.
  • Utilized a 1-compartment model with first-order absorption and a linear partition coefficient.
  • Employed visual predictive checks and bootstrapping for model evaluation.

Main Results:

  • A partition coefficient of 8.22 was estimated for phenytoin binding to albumin.
  • Weight (allometrically scaled) and albumin concentration significantly influenced the protein binding partition coefficient.
  • Nonlinear elimination of unbound phenytoin was not supported in this pediatric cohort.

Conclusions:

  • A population pharmacokinetic model effectively describes unbound phenytoin pharmacokinetics in critically ill children.
  • The model incorporates weight and albumin concentration to predict the fraction of unbound phenytoin.
  • This model can aid in optimizing phenytoin dosing and improving therapeutic outcomes in pediatric intensive care settings.

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