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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.
Abstract:
Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the prediction of PK parameters in children under specific exposure conditions. Pharmacokinetic outcomes are highly sensitive to fraction unbound in plasma (fup) as incorporated into PBPK models. Rarely is fup in children (fupchild) experimentally derived and prediction is based upon fup in adults (fupadult) as well as a ratio of plasma protein concentrations between children and adults. The objectives were to (i) evaluate protein concentration vs. age profile derived from ontogeny models, (ii) assess predictive performances of fup ontogeny models, and (iii) determine overall uncertainty in fupchild prediction resulting from a combination of quantitative structure-property relationship (QSPR) model and ontogeny models. The plasma albumin and alpha-acid glycoprotein (AAG) concentration data for pediatrics and fupchild and fupadult data were obtained from literature. The protein concentration vs. age profile derived from ontogeny models were compared to observed levels. Fupchild values were calculated according to ontogeny models using both observed and QSPR-predicted fupadult as inputs and predictive performances of ontogeny models assessed by comparing predicted fupchild to observed values. Protein concentrations vs. age profiles derived from non-linear equations were more congruent with observed albumin levels than linear or step-wise models. When observed fupadult values were used as input, the fupchild data were under-predicted with average fold error (AFE) amounts ranging 0.79-0.81 and 0.77-0.97 for albumin and AAG ontogeny models, respectively. When QSPR-predicted fupadult values were used as input, AFE of fupchild ranged 1.2-1.35 and 0.98-1.2 for albumin and AAG models, respectively. The choice of ontogeny model with respect to prediction accuracy is more important for AAG, highly bound compounds and infants. For these compounds and scenarios, experimental determination of fupchild for inclusion into a pediatric PBPK model is necessary to have confidence in PBPK model outputs.
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