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Clinical Pharmacokinetics

, Volume 57, Issue 12, pp 1603–1611 | Cite as

Predicting Escitalopram Exposure to Breastfeeding Infants: Integrating Analytical and In Silico Techniques

  • Sarah R. Delaney
  • Paul R. V. Malik
  • Cristiana Stefan
  • Andrea N. Edginton
  • David A. Colantonio
  • Shinya ItoEmail author
Original Research Article
First Online:

Abstract

Background

Escitalopram is used for post-partum depression; however, there are limited pharmacokinetic data of escitalopram in milk and plasma of infants breastfed by women taking the drug.

Objective

The objective of this study was to apply physiologically-based pharmacokinetic (PBPK) modelling to predict infant drug exposure (plasma area under the curve from time zero to infinity [AUC∞]) based on drug monitoring data of escitalopram in breast milk.

Methods

Using a newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, we quantified escitalopram concentrations in milk samples of 18 breastfeeding women with escitalopram therapy at steady state, collected at three to five time points. The escitalopram concentrations in breast milk were used with infant feeding parameters from the literature to simulate infant daily dose. We used PK-Sim® to develop an adult PBPK model for escitalopram and extrapolated it to a population of 1600 infants up to 12 months of age. An integration of the simulated infant daily dose and the virtual infants with variable physiological–pharmacological parameters was used to predict drug exposure (plasma AUC∞) distribution in the population of infants breastfed by women receiving escitalopram 20 mg/day.

Results

Escitalopram concentrations in milk were 50 ± 17 ng/mL (mean ± standard deviation). The simulated infant plasma AUC∞ following escitalopram exposure through breast milk was low, with a median of 1.7% (range 0.5–5.9%) of the corresponding maternal plasma AUC∞, indicating no substantial exposure.

Conclusions

Infant exposure levels to escitalopram in breast milk are low. A PBPK modeling approach can be used to translate data on drug monitoring in milk into a population distribution of infant plasma levels for drug safety assessment.

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Notes

Acknowledgements

The authors would like to thank all the women who participated in this study, as well as the study coordinator, Sholeh Ghayoori, for recruiting participants, obtaining informed consent, sample collection and processing, and data management for this study.

Funding

This study was funded by the Canadian Institutes of Health Research, Grant no. DSA 263431.

Compliance with Ethical Standards

Conflicts of interest

Sarah R. Delaney, Paul R.V. Malik, Cristiana Stefan, Andrea N. Edginton, David A. Colantonio and Shinya Ito declare that they have no conflicts of interest that might be relevant to the contents of this article.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

40262_2018_657_MOESM1_ESM.docx (263 kb)
Supplementary material 1 (DOCX 264 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Sarah R. Delaney
    • 1
  • Paul R. V. Malik
    • 2
  • Cristiana Stefan
    • 3
  • Andrea N. Edginton
    • 2
  • David A. Colantonio
    • 1
    • 4
  • Shinya Ito
    • 1
    • 5
    Email author
  1. 1.Department of Pharmacology and ToxicologyUniversity of TorontoTorontoCanada
  2. 2.School of PharmacyUniversity of WaterlooWaterlooCanada
  3. 3.Centre for Addiction and Mental HealthTorontoCanada
  4. 4.Department of Paediatric Laboratory MedicineHospital for Sick ChildrenTorontoCanada
  5. 5.Division of Clinical Pharmacology and ToxicologyHospital for Sick ChildrenTorontoCanada

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