Among pediatric patients, preterm neonates and newborns are the most vulnerable subpopulation. Rapid
developmental changes of physiological factors affecting the pharmacokinetics of drug substances in newborns require
extreme care in dose and dose regimen decisions. These decisions could be supported by in silico methods
such as physiologically-based pharmacokinetic (PBPK) modeling. In a comprehensive literature search, the physiological
information of preterm neonates that is required to establish a PBPK model has been summarized and implemented
into the database of a generic PBPK software. Physiological parameters include the organ weights and
blood flow rates, tissue composition, as well as ontogeny information about metabolic and elimination processes in
the liver and kidney. The aim of this work is to evaluate the model’s accuracy in predicting the pharmacokinetics following intravenous
administration of two model drugs with distinct physicochemical properties and elimination pathways based on earlier reported in vivo
data. To this end, PBPK models of amikacin and paracetamol have been set up to predict their plasma levels in preterm neonates. Predicted
plasma concentration-time profiles were compared to experimentally obtained in vivo data. For both drugs, plasma concentrationtime
profiles following single and multiple dosing were appropriately predicted for a large range gestational and postnatal ages. In summary,
PBPK simulations in preterm neonates appear feasible and might become a useful tool in the future to support dosing decisions in
this special patient population.
Keywords: Physiology, preterm, newborn, maturation, pharmacokinetic, amikacin, paracetamol.
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