(T1530-11-61) Physiologically-Based Pharmacokinetic Model to Predict Milk Drug Concentrations of Breast Cancer Resistance Protein Substrates

Purpose: The purpose of the study is to develop a mechanistic lactation physiologically-based pharmacokinetic (PBPK) modeling approach incorporating BCRP mediated transport kinetics to simulate the concentration-time profiles of several BCRP drug substrates.

Methods: Five BCRP drug substrates acyclovir, bupropion, cimetidine, ciprofloxacin, and nitrofurantoin were selected to build the model. The PBPK model to predict drug concentration in the milk was constructed with the built-ion module of the Simcyp™ population-based ADME simulator (V21 R1; Simcyp Limited, Sheffield, UK). The drug absorption was described with the advanced dissolution, absorption and metabolism (ADAM) model unless the drug was dose intravenously. Drug distribution was described using method 2 or method 3 of the full PBPK model. Drug elimination process was characterized using enzyme kinetics module, and lactation was described with the permeability limited module. We combine the bottom up and top down PBPK modeling approaches together with literature reported data to optimize and determine a set of parameters that are applicable for all the five drugs. The predictive performance of the PBPK models was assessed by comparing predicted pharmacokinetic profiles and milk-to-plasma (M/P) ratio with clinically reported data.

Results: The models generated a reasonably good prediction of the concentration-time profiles of those drugs in the milk. The predicted M/P ratios for acyclovir, bupropion, cimetidine, ciprofloxacin and nitrofurantoin were 2.48, 3.70, 3.55, 1.21 and 5.78, which were all within 1.5-fold of the observed values.

Conclusion: We believe that this PBPK lactation modeling approach is a useful tool in predicting milk pharmacokinetics profiles and M/P ratios for transporter drug substrates. The model performance is expected to be further improved when more physiological parameters during lactation are available.

Acknowledgments: The authors acknowledge the funding support from the US Food and Drug Administration (FDA) Office of Women’s Health. We also thank Simcyp Limited., a Certara Company, for providing academic licenses for the Simcyp Population-based Simulator.

Concentration time profiles of the drugs in plasma (left) and milk (right). Squares represent the mean values of observed data, the lines represent model predicted mean (solid lines) and the 5th and 95th percentiles (dashed lines).