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Incorporating Breastfeeding-Related Variability with Physiologically Based Pharmacokinetic Modeling to Predict Infant Exposure to Maternal Medication Through Breast Milk: a Workflow Applied to Lamotrigine

  • Research Article
  • Theme: Celebrating Women in the Pharmaceutical Sciences
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A Correction to this article was published on 13 July 2021

A Correction to this article was published on 10 June 2021

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Abstract

Current methods to assess risk in infants exposed to maternal medication through breast milk do not specifically account for infants most vulnerable to high drug exposure. A workflow applied to lamotrigine incorporated variability in infant anatomy and physiology, milk intake volume, and milk concentration to predict infant exposure. An adult physiologically based pharmacokinetic model of lamotrigine was developed and evaluated. The model was scaled to account for growth and maturation of a virtual infant population (n=100). Daily infant doses were simulated using milk intake volume and concentration models described by a nonlinear equation of weight-normalized intake across infant age and a linear function on the relationship of observed milk concentrations and maternal doses, respectively. Average infant plasma concentration at steady state was obtained through simulation. Models were evaluated by comparing observed to simulated infant plasma concentrations from breastfeeding infants based on a 90% prediction interval (PI). Upper AUC ratio (UAR) was defined as a novel risk metric. Twenty-five paired (milk concentrations measured) and 18 unpaired (milk concentrations unknown) infant plasma samples were retrieved from the literature. Forty-four percent and 11% of the paired and unpaired infant plasma concentrations were outside of the 90% PI, respectively. Over all ages (0–7 months), unpaired predictions captured more observed infant plasma concentrations within 90% PI than paired. UAR was 0.18–0.44 when mothers received 200 mg lamotrigine, suggesting that infants can receive 18–44% of the exposure per dose as compared to adults. UARs determined for further medications could reveal trends to better classify at-risk mother-infant pairs.

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Acknowledgements

• Canadian Institutes of Health Research (CIHR); Project Grant; Award Number: PJT-159782

• Canadian Institutes of Health Research (CIHR); Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (CGS-D), a Canada Graduate Scholarship to Honour Nelson Mandela; Award Number: DF2-171445

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Authors and Affiliations

  1. School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada

    Cindy H. T. Yeung & Andrea N. Edginton

  2. Division of Clinical Pharmacology and Toxicology, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada

    Shinya Ito

  3. Department of Pediatrics & Department of Pharmacology and Physiology, Université de Montréal, Montréal, Québec, Canada

    Julie Autmizguine

  4. Research Center, Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Québec, Canada

    Julie Autmizguine

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Contributions

I, Andrea Edginton, am contributing this section to highlight the work of the authors in this research that directly relates to the health of women and children. This important work has been championed by women as well as men. Authorship of this manuscript highlights our combined efforts to bring clarity to breastfeeding mothers and clinicians during an exceptionally vulnerable time in women’s lives. Our male co-author Shinya Ito, has spent a career focused on discovery and education in pediatric clinical pharmacology including lactation and infant exposure to medications and we most certainly consider him a champion of the cause. Julie Autmizguine, a newer independent investigator, is bringing equity to children through her research that will improve health outcomes through investigation of appropriate medication use in this population. My role in this work, and throughout my career, is in integrating the vast body of knowledge discovered by others to answer relevant clinical questions through the use of modeling and simulation. My role is also to inspire and train the next generation of knowledge translators and the first author, Cindy Yeung, is one such trainee. She brings an expertise in systematic review and clinical care guideline development from her MSc degree and we are privileged to have her extend her skill set to PBPK modeling and risk assessment. While my and Cindy’s expertise differs from that of our clinical collaborators, the strength of our Canadian team is indeed in our divergent expertise. Our varied skills, motivations, backgrounds, and beliefs allow for a problem assessment that is far richer than any one of us alone could achieve.

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Correspondence to Andrea N. Edginton.

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Yeung, C.H.T., Ito, S., Autmizguine, J. et al. Incorporating Breastfeeding-Related Variability with Physiologically Based Pharmacokinetic Modeling to Predict Infant Exposure to Maternal Medication Through Breast Milk: a Workflow Applied to Lamotrigine. AAPS J 23, 70 (2021). https://doi.org/10.1208/s12248-021-00599-5

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