Predicting Drug Transfer Into Human Milk With the Simcyp Simulator: A Contribution From the ConcePTION Project.

Abstract

Physiologically-based pharmacokinetic (PBPK) modeling can support decision-making on maternal medication use during breastfeeding. This study aimed to enhance lactation PBPK models in two ways. First, the utility of integrating permeability- versus perfusion-limited distribution to human milk was explored using the Simcyp Simulator. Secondly, for permeability-limited models, drug-specific bidirectional intrinsic clearance across the blood-milk barrier, predicted from drug physicochemical properties, was incorporated into lactation PBPK models. Initially, reference PBPK models were developed and verified against published clinical data. Geometric Mean Fold Error (GMFE; ~accuracy) and Average Fold Error (AFE; ~bias) for these models ranged from 1.13-1.51 and 0.68-1.42, respectively. These verified models were then extended to lactation PBPK models applying either permeability- or perfusion-limited assumptions for drug distribution across the blood-milk barrier. The lactation PBPK models were applied to predict drug concentrations in human milk and relative infant doses (RID) for 11 small molecule drugs with diverse physicochemical and disposition profiles. The models successfully predicted observed plasma PK, human milk concentration-time profiles, and milk-to-plasma ratios. Nine drugs had RID values below the safety threshold of 25%, while levetiracetam and nevirapine showed relatively higher RIDs (up to 21%). Based on these findings, a decision tree is proposed to guide the selection between permeability- or perfusion-limited distribution models in future lactation PBPK applications using Simcyp. This workflow can be extended beyond the 11 model drugs evaluated, supporting broader infant risk assessment for maternal medication during lactation.