(M1430-02-09) A PBPK Model for Prediction of Apixaban and Rivaroxaban Secretion into Milk

Purpose: Apixaban and rivaroxaban are FDA-approved oral anticoagulants utilized for the prevention of stroke and systemic embolism in patients with nonvalvular atrial fibrillation. Additionally, they are employed for the treatment and prevention of deep vein thrombosis (DVT) and pulmonary embolism (PE). This research focuses on estimating drug secretion into milk through a PBPK-based lactation model. The model employs several methodologies, such as a static human mammary cell permeability model, a Caco-2 cell permeability model, and the Rapid Equilibrium Dialysis (RED) assay. The data obtained from these methods were integrated into the PBPK model, which successfully predicted the milk-to-plasma (M/P) ratios of both drugs.

Methods: To simulate a static mammary epithelium, a transwell plate was used with a population of human noncarcinogenic mammary epithelial cells (MECs) that can form an integrated barrier featuring tight junctions. The Caco-2 permeability model was employed to mimic the absorption process in vivo. The unbound amounts of apixaban and rivaroxaban in breast milk collected from donors were quantified using the RED assay. The passive diffusive clearance of drugs across the breast milk barrier was determined using permeability data from MCF10A-TJ cells. This was calculated through published equations involving the apparent permeability on MCF10A-TJ cells, the total surface area of the alveoli, and a scaling factor of 130. Additionally, the efflux ratio (ER) from the MCF10A-TJ cell line helped calculate the efflux clearance contribution. The systemic lactation PBPK model was used to simulate the concentration-time profiles of apixaban and rivaroxaban in breast milk. A whole-body lactation PBPK model was developed using the Simcyp® simulator V23 to predict the concentration-time profiles of both drugs in human plasma and breast milk.

Results: A subpopulation of human normal mammary epithelial MCF10A cells (MCF10A-TJ), cultured using custom-designed maintenance and boosting media, formed a composite barrier with trans-epithelial electrical resistance (TEER) values exceeding 500 Ω-cm². This model was validated with clinical data for apixaban and rivaroxaban in plasma. For apixaban, the ratios of predicted to clinical data for T_max, C_max, and AUC in plasma were 0.98, 1.09, and 1.05, respectively. The ratios of predicted to clinical data for T_max, C_max, and AUC in milk were 0.98, 1.04, and 1.11, respectively. For rivaroxaban, the ratios of predicted to clinical data for T_max, C_max, and AUC in plasma were 0.73, 1.10, and 0.95, respectively. The corresponding ratios for milk were 1.04, 0.96, and 0.82, respectively. The results of M/P from IVIVE are 1.51 and 0.43 for apixaban and rivaroxaban, respectively.

Conclusion: Through the integration of a static human mammary cell permeability model, a human colon carcinoma cell (Caco-2) permeability model, and the Rapid Equilibrium Dialysis (RED) assay, along with published data on converting permeability into breast-milk barrier passive diffusion clearance and further calculations for efflux clearance, a whole-body lactation PBPK model was established, which the predictions of the M/P ratio were accurate to within 10%. This is another advancement in the use of model-based precision drug delivery at the bedside for breastfeeding patients. This systematic and comprehensive approach presents an innovative strategy for harmonizing batch-top experiments with PBPK analysis.

References: Andrews, L., Benken, S., Tan, X., & Wenzler, E. (2021). Pharmacokinetics and dialytic clearance of apixaban during in vitro continuous renal replacement therapy. BMC Nephrology, 22(1), 45.
Byon, W., Garonzik, S., Boyd, R. A., & Frost, C. E. (2019). Apixaban: A Clinical Pharmacokinetic and Pharmacodynamic Review. Clinical Pharmacokinetics, 58(10), 1265–1279.
Yang, H., Xue, I., Gu, Q., Zou, P., Zhang, T., Lu, Y., Fisher, J., & Tran, D. (2022). Developing an In Vitro to In Vivo Extrapolation (IVIVE) Model to Predict Human Milk-to-Plasma Drug Concentration Ratios. Molecular pharmaceutics, 19(7), 2506–2517.
Terrier, J., Gaspar, F., Gosselin, P., Raboud, O., Lenoir, C., Rollason, V., Csajka, C., Samer, C., Fontana, P., Daali, Y., Reny, J., & for the OptimAT study group. (2023). Apixaban and rivaroxaban’s physiologically‐based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side. CPT: Pharmacometrics & Systems Pharmacology, 12(12), 1872–1883.
Zhang, T., Zou, P., Fang, Y., & Li, Y. (2022). Physiologically based pharmacokinetic model to predict drug concentrations of breast cancer resistance protein substrates in milk. Biopharmaceutics & Drug Disposition, 43(6), 221–232.
Zhao, Y., Arya, R., Couchman, L., & Patel, J. P. (2020). Are apixaban and rivaroxaban distributed into human breast milk to clinically relevant concentrations? Blood, 136(15), 1783–1785.
Grillo JA, Zhao P, Bullock J, et al. Utility of a physiologicallybased pharmacokinetic (PBPK) modeling approach to quantitatively predict a complex drug-drug-disease interaction scenario for rivaroxaban during the drug review process: implications for clinical practice. Biopharm Drug Dispos. 2012;33(2):99-110.
Mueck W, Stampfuss J, Kubitza D, Becka M. Clinical pharmacokinetic and pharmacodynamic profile of rivaroxaban. Clin Pharmacokinet. 2014;53(1):1-16.
Byon W, Garonzik S, Boyd RA, Frost CE. Apixaban: a clinical pharmacokinetic and pharmacodynamic review. Clin Pharmacokinet. 2019;58(10):1265-1279.
EMA. Eliquis. European Medicines Agency; 2018. Accessed February 9, 2023.
Zhang D, He K, Herbst JJ, et al. Characterization of efflux transporters involved in distribution and disposition of apixaban. Drug Metab Dispos. 2013;41(4):827-835.
Hubatsch, I., Ragnarsson, E. G., & Artursson, P. (2007). Determination of drug permeability and prediction of drug absorption in Caco-2 monolayers. Nature protocols, 2(9), 2111–2119.
Ye, Z., Zetterberg, C., & Gao, H. (2017). Automation of plasma protein binding assay using rapid equilibrium dialysis device and Tecan workstation. Journal of pharmaceutical and biomedical analysis, 140, 210–214.

Acknowledgements: This research was funded by the Food and Drug Administration (FDA) Office of Women's Health (OWH), grant number 75F40122C00043, 75F40123C00208. We also thank Simcyp Limited., a Certara Company, for providing academic licenses for the Simcyp Population-based Simulator.

Concentration–time profiles of rivaroxaban in plasma (left) and milk (right). Squares represent the mean values of 2 lactating women after receiving a single oral dose of 20 mg rivaroxaban; the lines represent model predicted mean (solid lines) and the 5th and 95th percentiles (dashed lines)

Concentration–time profiles of apixaban in plasma (left) and milk (right). Squares represent the values of 1 lactating woman after receiving 2 doses of 5 mg apixaban, each 12 hours apart; the lines represent model predicted mean (solid lines) and the 5th and 95th percentiles (dashed lines)

Clinical and predicted TMax, CMax, AUC, and M/P ratios for Apixaban and Rivaroxaban in plasma and milk, along with their respective ratios.