Evaluation of models for predicting pediatric fraction unbound in plasma for human health risk assessment

Yejin Esther Yun1, Andrea N Edginton1

  • 1School of Pharmacy, University of Waterloo , Waterloo, ON, Canada.

Insights

Predicting fraction unbound in plasma (fup) in children for pediatric physiologically based pharmacokinetic (PBPK) models is crucial. Ontogeny models show variability, especially for alpha-acid glycoprotein (AAG) and infants, necessitating experimental fup determination for accurate PBPK predictions.

Area of Science:

  • Pharmacokinetics
  • Drug Metabolism and Disposition
  • Pediatric Pharmacology

Background:

  • Physiologically based pharmacokinetic (PBPK) models are vital for predicting drug behavior in children.
  • Fraction unbound in plasma (fup) is a critical input for PBPK models, but experimental fup data in pediatric populations is scarce.
  • Predictions often rely on adult fup (fupadult) and plasma protein concentration ratios, introducing uncertainty.

Purpose of the Study:

  • To evaluate age-dependent plasma protein concentration profiles using ontogeny models.
  • To assess the predictive accuracy of fup ontogeny models for pediatric populations.
  • To quantify the uncertainty in pediatric fup (fupchild) predictions arising from quantitative structure-property relationship (QSPR) and ontogeny models.

Main Methods:

  • Collected pediatric plasma albumin and alpha-acid glycoprotein (AAG) concentrations, and fupchild/fupadult data from literature.
  • Compared protein concentration-age profiles from ontogeny models against observed data.
  • Calculated fupchild using ontogeny models with observed and QSPR-predicted fupadult, assessing predictive performance against observed fupchild.

Main Results:

  • Non-linear ontogeny models better represented observed albumin concentrations compared to linear or step-wise models.
  • Using observed fupadult, fupchild was under-predicted (AFE 0.77-0.97 for AAG, 0.79-0.81 for albumin).
  • Using QSPR-predicted fupadult, AFE for fupchild ranged from 0.98-1.2 (AAG) and 1.2-1.35 (albumin).

Conclusions:

  • The choice of ontogeny model significantly impacts prediction accuracy, particularly for AAG, highly bound drugs, and infants.
  • For specific compounds and pediatric subgroups (infants, highly bound drugs), experimental fupchild determination is essential.
  • Accurate fupchild data is necessary to ensure the reliability of pediatric PBPK model outputs.

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