Laure-Hélène Préta1, Naïm Bouazza1,2,3, Frantz Foissac1,2,3, Léo Froelicher1,4, Saïk Urien1,2, Victoria Buth3, Sihem Benaboud1,4, Jean-Marc Tréluyer1,2,3,4, Gabrielle Lui1,3,4
1Université Paris Cité, INSERM, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, Inserm et Université Paris Cité, 2Unité de Recherche Clinique, Université Paris Cité Necker/Cochin, Hôpital Tarnier, 3CIC-1419 Inserm, Cochin-Necker, 4Service de Pharmacologie Clinique, AP-HP, Hôpital Cochin
Introduction/Objectives: Depression is common among pregnant women and selective serotonin reuptake inhibitors (SSRIs) are the most commonly used antidepressants during pregnancy [1]. Pregnancy is a period of significant physiological changes that affect drug pharmacokinetics (PK) [2]. To date, there is limited information on the placental transfer of antidepressants and the differences in fetal exposure between drugs are poorly characterized [3]. The aim of this study was to predict maternal and fetal exposure to three widely used SSRIs – sertraline, escitalopram, and paroxetine – across different trimesters of pregnancy, using a physiologically based pharmacokinetic (PBPK) model combined with ex vivo data. Methods: PBPK models were first developed and evaluated for the 3 antidepressant drugs for non-pregnant population. Estimated transplacental transfer parameters from ex-vivo human placenta perfusion experiments were then incorporated into a pregnancy PBPK model (p-PBPK) for each SSRI to predict both, maternal and fetal concentrations. Ex vivo data were obtained from a previous placental perfusion study of the human cotyledon [4]. Transplacental parameters were estimated through mixed-effects modeling with a physiologically-based mechanistic placenta (PBMP) model, using Monolix 2023R1 (Lixoft, Antony, France). The PBMP model was derived from Roelofsen et al. [5] and adapted by adding a placental clearance. Evaluation of the p-PBPK model was done by comparing observed maternal and cord blood concentrations to predicted concentrations. The p-PBPK model was then used to simulate maternal pharmacokinetic profiles and fetal exposure across pregnancy at gestational weeks 15, 25 and 37 at the following doses: sertraline 100 mg/day, escitalopram 10 mg/day and paroxetine 20 mg/day. All simulations were performed with Simcyp PBPK Simulator version 22 (Certara, Sheffield, UK). Results: A total of 28 placentas (10 for sertraline, 9 for escitalopram and 9 for paroxetine) were modeled using a population approach. A PBMP model, for which unbound maternal uptake/efflux and fetal uptake/efflux clearances were estimated, satisfactorily described the ex vivo data. An additional parameter standing for placental clearance was also estimated for all three drugs and improved significantly the fit. The p-PBPK models accurately predicted maternal and fetal concentration time-courses of these SSRIs. According to p-PBPK models, a decrease in exposure during pregnancy relative to non-pregnant period should be expected, affecting both total and unbound concentrations. Notably, in the third trimester, a decrease in residual concentrations was predicted, with reductions of -56 % and -43 % for sertraline, -55 % and -49 % for escitalopram, and -90 % and -88 % for paroxetine, for total and unbound concentrations respectively. To assess fetal exposure relative to the mother, cord blood-to-maternal plasma area under curve (fm AUC) ratios over 24 hours were calculated based on model predictions. By the end of pregnancy, fm AUC ratios were 0.45 for sertraline, 0.91 for escitalopram, and 0.58 for paroxetine. Overall, sertraline appeared to have the lowest fetal exposure relative to the mother while maintaining maternal concentrations within the recommended therapeutic range. Escitalopram was the molecule with the highest fetal-to-maternal exposure. Finally, paroxetine appeared to have an intermediate fetal-to-maternal exposure, but a substantial drop in maternal concentrations was predicted. Conclusions: Three p-PBPK models have been developed to quantitatively predict sertraline, escitalopram and paroxetine exposure during pregnancy. This work confirms the benefit of integrating ex vivo human cotyledon perfusion data into PBPK modeling. Finally, this work provides a good overview of maternal and fetal exposure trends throughout pregnancy and can serve as a starting point to support clinical decision-making and therapeutic monitoring. References: [1] Bénard-Laribière, A. et al. Br J Clin Pharmacol (2018) 84, 1764–1775. [2] Pariente, G. et al. PLoS Med 13 (2016) e1002160. [3] Zheng, L., Yang, H. & Dallmann, A. J Clin Pharmacol (2022) 62 Suppl 1, S115–S128 [4] Préta LH et al. [Manuscript submitted for publication]. (2025) [5] Roelofsen, D. et al. Toxicology in Vitro (2022) 85, 105471.
Reference: PAGE 33 (2025) Abstr 11636 [www.page-meeting.org/?abstract=11636]
Poster: Drug/Disease Modelling - Paediatrics