Postpartum changes in maternal physiology and milk composition: a comprehensive database for developing lactation physiologically-based pharmacokinetic models.

Abstract

Introduction: Pharmacotherapy during lactation often lacks reliable drug safety data, resulting in delayed treatment or early cessation of breastfeeding. In silico tools, such as physiologically-based pharmacokinetic (PBPK) models, can help to bridge this knowledge gap. To increase the accuracy of these models, it is essential to account for the physiological changes that occur throughout the postpartum period.

Methods: This study aimed to collect and analyze data on the longitudinal changes in various physiological parameters that can affect drug distribution into breast milk during lactation. Following meta-analysis of the collated data, mathematical functions were fitted to the available data for each parameter. The best-performing functions were selected through numerical and visual diagnostics.

Results and discussion: The literature search identified 230 studies, yielding a dataset of 36,689 data points from 20,801 postpartum women, covering data from immediately after childbirth to 12 months postpartum. Sufficient data were obtained to describe postpartum changes in maternal plasma volume, breast volume, cardiac output, glomerular filtration rate, haematocrit, human serum albumin, alpha-1-acid glycoprotein, milk pH, milk volume, milk fat, milk protein, milk water content, and daily infant milk intake. Although data beyond 7 months postpartum were limited for some parameters, mathematical functions were generated for all parameters. These functions can be integrated into lactation PBPK models to increase their predictive power and better inform medication efficacy and safety for breastfeeding women.