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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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Postpartum changes in maternal physiology and milk composition: a comprehensive database for developing lactation

Neel Deferm1,2, Jean Dinh1,3, Amita Pansari1

  • 1Predictive Technologies Division, Certara UK Limited, Sheffield, United Kingdom.

Frontiers in Pharmacology
|February 18, 2025
PubMed
Summary

This study developed mathematical functions for postpartum physiological changes to improve drug safety models during lactation. These models enhance the prediction of medication efficacy and safety for breastfeeding mothers.

Keywords:
PBPKbreastfeedinglactationmeta-analysismilkpostpartum

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Area of Science:

  • Pharmacology
  • Physiology
  • Computational Biology

Background:

  • Lactation pharmacotherapy lacks robust drug safety data, leading to treatment delays or breastfeeding cessation.
  • Physiologically-based pharmacokinetic (PBPK) models can predict drug behavior but require accurate postpartum physiological data.
  • Understanding longitudinal physiological changes is crucial for refining lactation PBPK models.

Purpose of the Study:

  • To collect and analyze longitudinal postpartum physiological data relevant to drug distribution into breast milk.
  • To develop mathematical functions describing these physiological changes throughout lactation.
  • To enhance the accuracy and predictive power of lactation PBPK models.

Main Methods:

  • Conducted a meta-analysis of 230 studies with 36,689 data points from 20,801 postpartum women.
  • Collected data on maternal and milk parameters from immediate postpartum to 12 months.
  • Fitted and selected mathematical functions for each physiological parameter using numerical and visual diagnostics.

Main Results:

  • Generated mathematical functions for postpartum changes in plasma volume, breast volume, cardiac output, GFR, hematocrit, albumin, AAG, milk composition, and infant intake.
  • Sufficient data were available for parameters up to 12 months postpartum, though limited beyond 7 months for some.
  • The developed functions can be integrated into lactation PBPK models.

Conclusions:

  • Mathematical functions describing postpartum physiological changes were successfully generated.
  • These functions will improve the accuracy of lactation PBPK models.
  • Enhanced PBPK models will better inform medication safety and efficacy for breastfeeding women.