Physiologically Based Pharmacokinetic Modeling Framework to Predict Neonatal Pharmacokinetics of Transplacentally Acquired Emtricitabine, Dolutegravir, and Raltegravir

Background and objectiveLittle is understood about neonatal pharmacokinetics immediately after delivery and during the first days of life following intrauterine exposure to maternal medications. Our objective was to develop and evaluate a novel, physiologically based pharmacokinetic modeling workflow for predicting perinatal and postnatal disposition of commonly used antiretroviral drugs administered prenatally to pregnant women living with human immunodeficiency virus.MethodsUsing previously published, maternal-fetal, physiologically based pharmacokinetic models for emtricitabine, dolutegravir, and raltegravir built with PK-Sim/MoBi®, placental drug transfer was predicted in late pregnancy. The total drug amount in fetal compartments at term delivery was estimated and subsequently integrated as initial conditions in different tissues of a whole-body, neonatal, physiologically based pharmacokinetic model to predict drug concentrations in the neonatal elimination phase after birth. Neonatal elimination processes were parameterized according to published data. Model performance was assessed by clinical data.ResultsNeonatal physiologically based pharmacokinetic models generally captured the initial plasma concentrations after delivery but underestimated concentrations in the terminal phase. The mean percentage error for predicted plasma concentrations was - 71.5%, - 33.8%, and 76.7% for emtricitabine, dolutegravir, and raltegravir, respectively. A sensitivity analysis suggested that the activity of organic cation transporter 2 and uridine diphosphate glucuronosyltransferase 1A1 during the first postnatal days in term newborns is ~11% and ~30% of that in adults, respectively.ConclusionsThese findings demonstrate the general feasibility of applying physiologically based pharmacokinetic models to predict washout concentrations of transplacentally acquired drugs in newborns. These models can increase the understanding of pharmacokinetics during the first postnatal days and allow the prediction of drug exposure in this vulnerable population