Prediction of Maternal and Fetal Exposure to Escitalopram, Sertraline, and Paroxetine by Combining Human Ex Vivo Placenta Perfusion Data and Physiologically Based Pharmacokinetic Modeling.

Background: Depression is common in pregnant women, and selective serotonin reuptake inhibitors (SSRIs) are the most widely used antidepressants during pregnancy. Pregnancy is a period of major physiological changes that impact drug pharmacokinetics (PK). To date, there is limited information about the placental transfer of antidepressants, and differences in fetal exposure between drugs are poorly characterized.

Aims: We aimed to develop physiologically based pharmacokinetic (PBPK) models to assess maternal and fetal exposure to sertraline, escitalopram and paroxetine across pregnancy.

Methods: Transplacental parameters from ex vivo human placenta perfusion experiments were estimated using mixed-effects modeling in Monolix and integrated in pregnancy PBPK models in Simcyp PBPK Simulator. After evaluation of the models by comparison with observed data from literature, maternal PK profiles and fetal exposure at different trimesters of pregnancy were simulated.

Results: The pregnancy PBPK models accurately predicted maternal and fetal concentration time-courses of SSRIs. Simulations showed a decrease in maternal concentrations during pregnancy for all three SSRIs, affecting both total and unbound concentrations. In the third trimester, residual concentrations were predicted to decrease by 56% and 43% for sertraline, 55% and 49% for escitalopram, and 90% and 88% for paroxetine, for total and unbound concentrations respectively. Cord blood-to-maternal plasma area-under-curve (fm AUC) ratios over 24 h were calculated based on model predictions. By late pregnancy, fm AUC ratios were 0.45 for sertraline, 0.91 for escitalopram, and 0.58 for paroxetine.

Conclusions: Quantitative prediction of antidepressants exposure using PBPK modeling integrating ex vivo data will help to better understand the impact of pregnancy-related physiological changes on the PK of these drugs and support evidence-based pharmacotherapy for depression during pregnancy.