Generic Workflow to Predict Medicine Concentrations in Human Milk Using Physiologically-Based Pharmacokinetic (PBPK)...

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Pediatric Pharmacology
• Reproductive Toxicology

Background:

• Maternal medication use during lactation is common, yet safety data for breastfed infants is limited.
• Accurate prediction of drug exposure in infants is crucial for ensuring medication safety.
• Physiologically-based pharmacokinetic (PBPK) modeling offers a potential solution for predicting drug transfer into human milk.

Purpose of the Study:

• To evaluate the performance of a generic PBPK model in predicting drug concentrations in human milk.
• To establish a workflow for assessing the safety of maternal medications during lactation using PBPK modeling.
• To support evidence-based safety assessments in early drug development stages.

Main Methods:

• Development of PBPK models for non-lactating adults using PK-Sim/MoBi software.
• Extension of PBPK models to incorporate lactation physiology for simulating postpartum populations.
• Simulation of plasma and human milk drug concentrations, calculating milk-to-plasma (M/P) ratios and relative infant doses for ten diverse drugs.

Main Results:

• PBPK models accurately predicted plasma concentrations (AUC and Cmax) within a two-fold error for adult models.
• Lactation PBPK models provided reasonable predictions for eight out of ten tested drugs.
• Two drugs showed overprediction of human milk concentrations and M/P ratios (>2-fold); however, no underpredictions of safety-relevant concentrations were observed.

Conclusions:

• A generic PBPK modeling workflow effectively predicts drug concentrations in human milk.
• The developed PBPK models demonstrate utility in the early safety assessment of maternal medications during lactation.
• This approach contributes to evidence-based decision-making for medication use in breastfeeding mothers and infants.