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Assessing CYP2C19 Ontogeny in Neonates and Infants Using Physiologically Based Pharmacokinetic Models: Impact of

Peng Duan1, Fang Wu1, Jason N Moore2

  • 1Office of New Drug Product, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.

CPT: Pharmacometrics & Systems Pharmacology
|December 7, 2018
PubMed

Insights

Pediatric physiologically based pharmacokinetic (PBPK) models for pantoprazole and esomeprazole were developed. Models showed variability in infants, highlighting the need for further research into CYP2C19 enzyme maturation and inhibition in this age group.

Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Pediatric Pharmacology
  • Computational Modeling

Background:

  • Physiologically based pharmacokinetic (PBPK) models are crucial for predicting drug behavior in pediatric populations.
  • Cytochrome P450 (CYP)2C19 plays a significant role in the metabolism of pantoprazole and esomeprazole.
  • Understanding age-specific drug metabolism is essential for safe and effective pediatric prescribing.

Purpose of the Study:

  • To develop and validate pediatric PBPK models for pantoprazole and esomeprazole.
  • To investigate the impact of CYP2C19 maturation and auto-inhibition on drug clearance in children and infants.
  • To identify factors influencing the accuracy of PBPK predictions in different pediatric age groups.

Main Methods:

  • Utilized Simcyp software (version 15) to construct pediatric PBPK models.
  • Incorporated age-dependent CYP2C19 maturation and auto-inhibition parameters.
  • Compared model-predicted drug clearance (CL) with observed data across various pediatric age ranges.

Main Results:

  • Pediatric PBPK models for pantoprazole and esomeprazole were successfully developed.
  • Pantoprazole clearance predictions showed good agreement (0.96-1.35) in children (1-17 years) but were less accurate in infants (0.43-0.70).
  • Esomeprazole clearance predictions were reasonable in older children (1.08-1.50) but poor in infants (0.15-0.33), improving when auto-inhibition was excluded.

Conclusions:

  • The CYP2C19 auto-inhibition model is suitable for adults and older children but requires modification for infant PBPK modeling.
  • Accurate PBPK modeling in infants necessitates a deeper understanding of CYP2C19 enzyme maturation, inhibition, and compensatory mechanisms.
  • Further research is needed to refine PBPK models for proton pump inhibitors in the pediatric population, especially neonates.

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