Evidence map›Paper›PMID 41014441›Full record

ArticleClinical pharmacokinetics2025

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

Laure-Hélène Préta, Naïm Bouazza, Frantz Foissac, Léo Froelicher, Saïk Urien, Victoria Buth, Sihem Benaboud, Jean-Marc Tréluyer, Gabrielle Lui

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Article in Clinical pharmacokinetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Laure-Hélène PrétaUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France. laurehelene.preta@aphp.fr.ORCID 0000-0002-3141-5925
Naïm BouazzaUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Frantz FoissacUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Léo FroelicherUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Saïk UrienUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Victoria ButhCIC-1419 Inserm, Cochin-Necker, Paris, France.
Sihem BenaboudUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Jean-Marc TréluyerUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.
Gabrielle LuiUniversité Paris Cité, Inserm, Pharmacologie et évaluation des thérapeutiques chez l'enfant et la femme enceinte, 75006, Paris, France.

Funding

Fondation pour la Recherche Médicale (FRM) FDM202206015346Groupement d'intérêt scientifique - Centre français pour les 3R (GIS-FC3R) 22FC3R-018
6 · The paper itself

Abstract

backgroundDepression 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.

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

methodsTransplacental 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.

resultsThe 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.

conclusionsQuantitative 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.

Indexed as

Maternal ExposureMaternal-Fetal ExchangeModels, BiologicalPlacentaSelective Serotonin Reuptake InhibitorsEscitalopramFemaleHumansParoxetinePregnancySertralineEscitalopramParoxetineSelective Serotonin Reuptake InhibitorsSertraline

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.