In Vitro-In Vivo Extrapolation (IVIVE) data from cell–based transport assays can be included within Physiologically-Based Pharmacokinetic (PBPK) models that aim to predict time-dependent profiles of drug disposition. For this purpose, drug-dependent kinetic transporter data (i.e., Jmax/Km) are combined with system-dependent data (e.g. tissue transporter expression in a population). Relative Expression Factors (REFs), the ratios of transporters’ expression in vivo to those in the in vitro system, are also required to gain realistic estimates of the mass of drug transferred across a membrane when scaling from in vitro data. Currently, these models have used relative measurements of intestinal transporter expression from immunoblotting1 rather than absolute abundances from quantitative targeted absolute proteomics (QTAP) techniques to generate intestinal REFs. The absolute protein abundances of P-glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) were determined in Caco-2 cells and human distal jejunum enterocyte membranes using a QTAP quantification concatamer (QconCAT) strategy. Scalars for P-gp (REFiP-gp) and BCRP (REFiBCRP) were generated from these absolute abundance data and compared to immunoblotting scalars from the literature2,3. IVIVE-PBPK simulations using the Simcyp population-based simulator (Version 14 Release 1) were performed to assess the impact of absolute abundance or immunoblotting-based REFiP-gp on the plasma concentrations of the P-gp probe digoxin. To verify the relative contribution of intestinal P-gp to the overall intestinal transport of digoxin, the DDI with rifampicin, a P-gp inducer (3.5-fold4), was investigated. REFiBCRP was used to assess the regional-specific absorption and plasma concentrations of a theoretical compound (TC-1); a highly permeable, basic compound with BCRP intrinsic clearance, where jejunal absorption was highest and the fraction of dose absorbed (fa) in the jejunum was sensitive to alterations in small intestine transit time. There was a 5-fold lower REFiP-gp (0.4) generated from absolute abundance data compared to that generated by immunoblotting (2), providing a 1.2 and 1.3-fold higher area under the plasma concentration-time curve (AUC) and maximal plasma concentration (Cmax) for digoxin, respectively. REFiP-gp from both laboratories lead to digoxin Cmax values within observed ranges5,6. The P-gp activity data for digoxin were obtained from the same laboratory as the REFiP-gp from immunoblotting. When increasing the REFiP-gp from 0.4 from QTAP data to 1.4, to reflect rifampicin induced P-gp expression, this failed to capture the observed DDI, yet the DDI was recovered by inducing the immunoblot REF of 2 by 3.5-fold to 7. As expected, to recover the rifampicin DDI when using the induced REFiP-gp from QTAP data, a 4.2-fold higher Jmax is required.There was a 1.9-fold higher REFiBCRP (2.22) generated from absolute abundance data compared to immunoblotting (1.19), leading to a maximum 1.5-fold higher fa in the distal jejunum and a 1.2-fold higher Cmax for TC-1. When using REF¬iBCRP from both laboratories, a considerable overlap was demonstrated for Cmax across a population of 100 virtual individuals. Laboratory-specific differences in REFs may lead to different IVIVE-PBPK outcomes. While a wide-range of REFiP-gp could be used (0.1-to-5) to attain observed digoxin Cmax values, only a specific REF in combination with the corresponding in vitro kinetic data will allow a realistic recovery of the active contribution to the overall membrane transport. Furthermore, it was shown that inter-individual variability in other physiological parameters that govern fa and Cmax within each individual are more relevant than the differences in REFiBCRP of the currently available scalars. References: Neuhoff et al., 2013, J Pharm Sci, 102: 3145-60. –  Troutman and Thakker, 2003, Pharm Res, 20: 1210-1224. –  Von Richter et al., 2009, Naunyn Schmiedebergs Arch Pharmacol, 379: 11-26. –  Greiner et al., 1999, J Clin Invest, 104: 147-53. –  Reitman et al., 2011, Clin Pharmacol Ther, 89: 234-42. –  Versufyft et al., 2003, Clin Pharmacol Ther, 73: 51-60.