Improving Pediatric Protein Binding Estimates: An Evaluation of α1-Acid Glycoprotein Maturation in Healthy and Infected Subjects.

ABSTRACT

BACKGROUND: Differences in plasma protein levels observed between children and adults can alter the extent of xenobiotic binding in plasma, resulting in divergent patterns of exposure. OBJECTIVE: This study aims to quantify the ontogeny of α1-acid glycoprotein in both healthy and infected subjects. METHODS: Data pertaining to α1-acid glycoprotein from healthy subjects were compiled over 26 different publications. For subjects diagnosed or suspected of infection, α1-acid glycoprotein levels were obtained from 214 individuals acquired over three clinical investigations. The analysis evaluated the use of linear, power, exponential, log-linear, and sigmoid E max models to describe the ontogeny of α1-acid glycoprotein. Utility of the derived ontogeny equation for estimation of pediatric fraction unbound was evaluated using average-fold error and absolute average-fold error as measures of bias and precision, respectively. A comparison to fraction unbound estimates derived using a previously proposed linear equation was also instituted. RESULTS: The sigmoid E max model provided the comparatively best depiction of α1-acid glycoprotein ontogeny in both healthy and infected subjects. Despite median α1-acid glycoprotein levels in infected subjects being more than two-fold greater than those observed in healthy subjects, a similar ontogeny pattern was observed when levels were normalized toward adult levels. For estimation of pediatric fraction unbound, the α1-acid glycoprotein ontogeny equation derived from this work (average fold error 0.99; absolute average fold error 1.24) provided a superior predictive performance in comparison to the previous equation (average fold error 0.74; absolute average fold error 1.45). CONCLUSION: The current investigation depicts a proficient modality for estimation of protein binding in pediatrics and will, therefore, aid in reducing uncertainty associated with pediatric pharmacokinetic predictions.