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Updated: May 1, 2026

An Intestine/Liver Microphysiological System for Drug Pharmacokinetic and Toxicological Assessment
Published on: December 3, 2020
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.
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.
Abstract:
Although both POPPK and physiologically based pharmacokinetic (PBPK) models can account for age and other covariates within a paediatric population, they generally do not account for real-time growth and maturation of the individuals through the time course of drug exposure; this may be significant in prolonged neonatal studies. The major objective of this study was to introduce age progression into a paediatric PBPK model, to allow for continuous updating of anatomical, physiological and biological processes in each individual subject over time. The Simcyp paediatric PBPK model simulator system parameters were reanalysed to assess the impact of re-defining the individual over the study period. A schedule for re-defining parameters within the Simcyp paediatric simulator, for each subject, over a prolonged study period, was devised to allow seamless prediction of pharmacokinetics (PK). The model was applied to predict concentration-time data from multiday studies on sildenafil and phenytoin performed in neonates. Among PBPK system parameters, CYP3A4 abundance was one of the fastest changing covariates and a 1-h re-sampling schedule was needed for babies below age 3.5 days in order to seamlessly predict PK (<5% change in abundance) with subject maturation. The re-sampling frequency decreased as age increased, reaching biweekly by 6 months of age. The PK of both sildenafil and phenytoin were predicted better at the end of a prolonged study period using the time varying vs fixed PBPK models. Paediatric PBPK models which account for time-varying system parameters during prolonged studies may provide more mechanistic PK predictions in neonates and infants.
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