Predicting pharmacokinetics in children using PK-Sim®

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Objective: Approaches that are able to predict potential differences in the pharmacokinetic behavior of a compound in children compared to adults are highly desirable for dosage adjustment, therapeutic response analysis and risk assessment. Physiology-based pharmacokinetic (PBPK) modeling allows for the simulation of concentration-time profiles in plasma and other organs based on a combination of physiological parameters such as organ volumes and blood flow rates with substance specific parameters including organ/plasma-partition coefficients, permeability coefficients and elimination rate constants. PK-Sim^® is a software tool designed to account for age dependent physiology from birth to sub-adults, which are critical elements for PK prediction in children (1). The objective of this study was to determine the appropriateness of PK-Sim^® to correctly predict plasma concentration-time curves and PK parameters (volume of distribution, elimination half-lives) of model compounds such as morphine and levofloxacin.

Methods: Experimental plasma concentration-time data and PK parameter information following intravenous administration was gathered from the literature for various age groups. Predictions were generated in PK-Sim^® for each literature study using the mean age and weight of the subjects, as reported. Additional input information comprised of physio-chemical properties, clearance, administration regime and protein binding prediction (2).

Results: Trends associated with the differing age groups as well as experimental plasma concentration-time curves were extremely well represented by PK-Sim^® predictions. Preterm and term neonates had greater plasma concentrations in comparison to children 6 months of age and older. Children greater than 6 months had lower plasma concentrations in comparison to adults. This is a result of both the age-dependence of clearance and disposition.

Conclusion: PK-Sim^® is very well suited for the prediction of plasma concentration-time data and PK parameters in children from birth to sub-adults. This approach will not only aid in clinical trial development but has the potential to reduce the number of required subjects.

References:
[1] Willmann S, Lippert J, Sevestre M, Solodenko J, Fois F, Schmitt W. PK-Sim: a physiologically based pharmacokinetic ‘whole-body’ model. Biosilico 2003; 1:121-4.
[2] McNamara PJ, Alcorn J. Protein binding predictions in infants. AAPS PharmSci 2002; 4(1):8.