Changes in individual drug-independent system parameters during virtual paediatric pharmacokinetic trials:

Khaled Abduljalil1, Masoud Jamei, Amin Rostami-Hodjegan

  • 1Simcyp Ltd (a Certara Company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK.

The AAPS Journal
|April 5, 2014
PubMed

Insights

This study introduces age progression into pediatric physiologically based pharmacokinetic (PBPK) models. Time-varying PBPK models provide more accurate drug exposure predictions in neonates and infants during prolonged studies.

Area of Science:

  • Pharmacokinetics
  • Pediatric Drug Development
  • Computational Modeling

Background:

  • Traditional pediatric physiologically based pharmacokinetic (PBPK) models often fail to account for real-time growth and maturation.
  • This limitation is significant in prolonged neonatal studies where physiological changes impact drug exposure.

Purpose of the Study:

  • To develop and validate a pediatric PBPK model incorporating age progression for continuous updating of physiological parameters.
  • To improve the prediction of drug pharmacokinetics (PK) in neonates and infants during extended study durations.

Main Methods:

  • Re-analyzed Simcyp pediatric PBPK model parameters to incorporate time-varying individual characteristics.
  • Devised a parameter re-definition schedule within the Simcyp simulator for prolonged studies.
  • Applied the time-varying PBPK model to predict sildenafil and phenytoin pharmacokinetics in neonates.

Main Results:

  • A 1-hour re-sampling schedule was necessary for infants under 3.5 days old to accurately predict PK due to rapid CYP3A4 abundance changes.
  • The required re-sampling frequency decreased with age, reaching biweekly by 6 months.
  • Time-varying PBPK models demonstrated improved prediction accuracy for sildenafil and phenytoin PK at the end of prolonged studies compared to fixed models.

Conclusions:

  • Pediatric PBPK models that incorporate time-varying parameters offer more mechanistic and accurate pharmacokinetic predictions in neonates and infants.
  • Age progression in PBPK models is crucial for understanding drug behavior during critical developmental periods.

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