INTRODUCTION: Lofexidine (LUCEMYRA®) is the only FDA-approved, non-opioid, non-addictive treatment for opioid withdrawal symptoms, crucial for postpartum and pregnant women affected by the opioid crisis. Despite its clinical importance, data on its secretion into breast milk is limited. This study aims to develop a novel, microfluidic-based blood-milk-barrier on a chip model, a static human mammary cell transwell model, and a physiologically based pharmacokinetic (PBPK) lactation model to estimate the breast milk secretion of lofexidine, thereby ensuring maternal and infant safety and improving withdrawal management. METHODS: A novel microfluidic device was developed to build a mammary epithelium-on-a-chip model, and a transwell plate was used to develop a static mammary epithelium using a human noncarcinogenic mammary epithelial cell (MEC) population that can form an integrated barrier with tight junctions. Both models were used to evaluate the transfer of lofexidine through the in vitro mammary cell barrier. The fraction of unbound lofexidine in the breast milk was determined by a Rapid Equilibrium Dialysis (RED) assay. Eleven approaches, including a novel, previously published in vitro to in vivo extrapolation (IVIVE) approach and various other approaches, were used to estimate milk-to-plasma (M/P) ratios of lofexidine. A whole-body lactation PBPK model was built using Simcyp® simulator v22 and used to predict the concentration-time profiles of lofexidine in both human plasma and breast milk. RESULTS: A subpopulation of human normal mammary epithelial MCF10A cells (named MCF10A-TJ) was identified to form an integrated barrier that reaches trans-epithelial electrical resistance (TEER) values of over 1000 Ω·cm CONCLUSION: This study introduces comprehensive and novel approaches to predict lofexidine secretion into breast milk. Most predictions suggest higher lofexidine concentration in milk than in plasma, raising potential safety concerns for opioid withdrawal management. Further pharmacokinetic clinical lactation studies are needed to validate these predictions.