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 (fup_child) experimentally derived and prediction is based upon fup in adults (fup_adult) 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 fup_child 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 fup_child and fup_adult data were obtained from literature. The protein concentration vs. age profile derived from ontogeny models were compared to observed levels. Fup_child values were calculated according to ontogeny models using both observed and QSPR-predicted fup_adult as inputs and predictive performances of ontogeny models assessed by comparing predicted fup_child 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 fup_adult values were used as input, the fup_child 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 fup_adult values were used as input, AFE of fup_child 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 fup_child for inclusion into a pediatric PBPK model is necessary to have confidence in PBPK model outputs.

摘要

基于儿科生理学的药代动力学（PBPK）模型有助于预测儿童在特定暴露条件下的PK参数。如纳入PBPK模型，药代动力学结果对血浆中未结合的分数（fup）高度敏感。很少通过实验得出儿童中的fup（fup _child），并且预测是基于成人（fup _adult）中的fup以及儿童与成人之间血浆蛋白浓度的比率。目的是（i）评估从个体发育模型得出的蛋白质浓度与年龄分布，（ii）评估fup个体发育模型的预测性能，以及（iii）确定fup_儿童的总体不确定性定量结构-属性关系（QSPR）模型和个体发育模型相结合而产生的预测。儿科的血浆白蛋白和α-酸糖蛋白（AAG）浓度数据以及fup_儿童和fup_成人数据均来自文献。将来自个体发育模型的蛋白质浓度对年龄的分布与观察到的水平进行比较。根据观察到的和QSPR预测的_成年成人作为输入，根据个体发育模型计算出成年_孩子的价值，并通过比较预测的成年_孩子来评估成年_孩子模型的预测性能到观察值。与线性或逐步模型相比，从非线性方程式得出的蛋白质浓度与年龄特征曲线与观察到的白蛋白水平更为一致。当将观察到的_成人fup值用作输入时，对于_儿童fup的数据被低估了，白蛋白和AAG个体发育模型的平均折叠误差（AFE）量分别为0.79-0.81和0.77-0.97。当使用QSPR预测的_成年fup_成人值作为输入时，对于白蛋白和AAG模型，fup_儿童的AFE分别为1.2–1.35和0.98–1.2。对于AAG，高度结合的化合物和婴儿，关于预测准确性的本体模型的选择更为重要。对于这些化合物和场景，实验确定了氟要纳入PBPK模型输出的信心，必须将_儿童纳入小儿PBPK模型。