Developing an In Vitro to In Vivo Extrapolation (IVIVE) Model to Predict Human Milk-to-Plasma Drug Concentration Ratios.

Abstract

Determining the amount of drug transferred into human milk is critical for benefit-risk analysis of taking medication while breastfeeding. In this study, we developed an in vitro and in vivo extrapolation (IVIVE) model to predict human milk/plasma (M/P) drug concentration ratios. Drug unionized fractions at pH 7.0 (Fni,7.0) and 7.4 (Fni,7.4), drug fractions unbound in human plasma (fup) and milk (fum), and in vitro cell permeability in both directions (efflux ratio, ER) were incorporated into the IVIVE model. A multiple regression Emax model was chosen to predict fum from fup and polar surface area (PSA). A total of 97 drugs with experimental ER from Caco-2 cells were used to test the IVIVE model. The M/P ratios predicted by the IVIVE model had a 1.93-fold geometric mean fold error (GMFE) and 72% of predictions were within two-fold error (Pw2FE), which were superior to the performance of previously reported five models. The IVIVE model showed a reasonable prediction accuracy for passive diffusion drugs (GMFE = 1.71-fold, Pw2FE = 82%, N = 50), BCRP substrates (BCRP: GMFE = 1.91-fold, Pw2FE = 60%, N = 5), and substrates of P-gp and BCRP (GMFE = 1.74-fold, Pw2FE = 75%, N = 8) and a lower prediction performance for P-gp substrates (GMFE = 2.51-fold, Pw2FE = 55%, N = 22). By fitting the observed M/P ratios of 39 P-gp substrates, an optimized ER (1.61) was generated to predict the M/P ratio of P-gp substrates using the developed IVIVE model. Compared with currently available in vitro models, the developed IVIVE model provides a more accurate prediction of the drug M/P ratio, especially for passive diffusion drugs. The model performance is expected to be further improved when more experimental fum and ER data are available.