Development of a Generic Physiologically-Based Pharmacokinetic Model for Lactation and Prediction of Maternal and Infant Exposure to Ondansetron via Breast Milk.

Journal Article (Journal Article;Systematic Review)

Ondansetron is commonly used in breastfeeding mothers to treat nausea and vomiting. There is limited information in humans regarding safety of ondansetron exposure to nursing infants and no adequate study looking at ondansetron pharmacokinetics during lactation. We developed a generic physiologically-based pharmacokinetic lactation model for small molecule drugs and applied this model to predict ondansetron transfer into breast milk and characterize infant exposure. Drug-specific model inputs were parameterized using data from the literature. Population-specific inputs were derived from a previously conducted systematic literature review of anatomic and physiologic changes in postpartum women. Model predictions were evaluated using ondansetron plasma and breast milk concentration data collected prospectively from 78 women in the Commonly Used Drugs During Lactation and infant Exposure (CUDDLE) study. The final model predicted breast milk and plasma exposures following a single 4 mg dose of intravenous ondansetron in 1,000 simulated women who were 2 days postpartum. Model predictions showed good agreement with observed data. Breast milk median prediction error (MPE) was 18.4% and median absolute prediction error (MAPE) was 53.0%. Plasma MPE was 32.5% and MAPE was 43.2%. The model-predicted daily and relative infant doses were 0.005 mg/kg/day and 3.0%, respectively. This model adequately predicted ondansetron passage into breast milk. The calculated low relative infant dose indicates that mothers receiving ondansetron can safely breastfeed. The model building blocks and population database are open-source and can be adapted to other drugs.

Full Text

Duke Authors

Cited Authors

  • Job, KM; Dallmann, A; Parry, S; Saade, G; Haas, DM; Hughes, B; Berens, P; Chen, J-Y; Fu, C; Humphrey, K; Hornik, C; Balevic, S; Zimmerman, K; Watt, K

Published Date

  • May 2022

Published In

Volume / Issue

  • 111 / 5

Start / End Page

  • 1111 - 1120

PubMed ID

  • 35076931

Electronic International Standard Serial Number (EISSN)

  • 1532-6535

Digital Object Identifier (DOI)

  • 10.1002/cpt.2530

Language

  • eng

Conference Location

  • United States