Metformin is used as a probe for OCT2 mediated transport when investigating possible DDIs with new chemical entities. The aim of the current study was to investigate the ability of physiologically-based pharmacokinetic (PBPK) models to simulate the effects of OCT and MATE inhibition by cimetidine on metformin kinetics. PBPK models were developed, incorporating mechanistic kidney and liver sub-models for metformin (OCT and MATE substrate) and a mechanistic kidney sub-model for cimetidine. The models were used to simulate inhibition of the MATE1, MATE2-K, OCT1 and OCT2 mediated transport of metformin by cimetidine. Assuming competitive inhibition and using cimetidine Ki values determined in vitro, the predicted metformin AUC ratio was 1.0 compared to an observed value of 1.46. The observed AUC ratio could only be recovered with this model when the cimetidine Ki for OCT2 was decreased 1000-fold or the Ki's for both OCT1 and OCT2 were decreased 500-fold. An alternative description of metformin renal transport by OCT1 and OCT2, incorporating electrochemical modulation of the rate of metformin uptake together with 8-18-fold decreases in cimetidine Ki's for OCTs and MATEs, allowed recovery of the extent of the observed effect of cimetidine on metformin AUC. While the final PBPK model has limitations, it demonstrates the benefit of allowing for the complexities of passive permeability combined with active cellular uptake modulated by an electrochemical gradient and active efflux.

The levels of drug-metabolizing enzymes (DMEs) and transporter proteins in the human intestine are pertinent to determine oral drug bioavailability. Despite the paucity of reports on such measurements, it is well recognized that these values are essential for translating in vitro data on drug metabolism and transport to predict drug disposition in gut wall. In the current study, clinically relevant DMEs [cytochrome P450 (P450) and uridine 5′-diphospho-glucuronosyltransferase (UGT)] and drug transporters were quantified in total mucosal protein preparations from the human jejunum (n = 4) and ileum (n = 12) using quantification concatemer–based targeted proteomics. In contrast to previous reports, UGT2B15 and organic anion-transporting polypeptide 1 (OATP1A2) were quantifiable in all our samples. Overall, no significant disparities in protein expression were observed between jejunum and ileum. Relative mRNA expression for drug transporters did not correlate with the abundance of their cognate protein, except for P-glycoprotein 1 (P-gp) and organic solute transporter subunit alpha (OST-α), highlighting the limitations of RNA as a surrogate for protein expression in dynamic tissues with high turnover. Intercorrelations were found within P450 [2C9-2C19 (P = 0.002, R² = 0.63), 2C9–2J2 (P = 0.004, R² = 0.40), 2D6-2J2 (P = 0.002, R² = 0.50)] and UGT [1A1-2B7 (P = 0.02, R² = 0.87)] family of enzymes. There were also correlations between P-gp and several other proteins [OST-α (P < 0.0001, R² = 0.77), UGT1A6 (P = 0.009, R² = 0.38), and CYP3A4 (P = 0.007, R² = 0.30)]. Incorporating such correlations into building virtual populations is crucial for obtaining plausible characteristics of simulated individuals. SIGNIFICANCE STATEMENT A number of drug transporters were quantified for the first time in this study. Several intercorrelations of protein abundance were reported. mRNA expression levels proved to be a poor reflection of differences between individuals regarding the level of protein expression in gut. The reported abundance of drug-metabolizing enzymes and transporters and their intercorrelations will contribute to better predictions of oral drug bioavailability and drug-drug interactions by linking in vitro observations to potential outcomes through physiologically based pharmacokinetic models.

This study aimed to derive quantitative abundance values for key hepatic transporters suitable for in vitro–in vivo extrapolation within a physiologically based pharmacokinetic modeling framework. A meta-analysis was performed whereby data on abundance measurements, sample preparation methods, and donor demography were collated from the literature. To define values for a healthy Caucasian population, a subdatabase was created whereby exclusion criteria were applied to remove samples from non-Caucasian individuals, those with underlying disease, or those with subcellular fractions other than crude membrane. Where a clinically relevant active genotype was known, only samples from individuals with an extensive transporter phenotype were included. Authors were contacted directly when additional information was required. After removing duplicated samples, the weighted mean, geometric mean, standard deviation, coefficient of variation, and between-study homogeneity of transporter abundances were determined. From the complete database containing 24 transporters, suitable abundance data were available for 11 hepatic transporters from nine studies after exclusion criteria were applied. Organic anion transporting polypeptides OATP1B1 and OATP1B3 showed the highest population abundance in healthy adult Caucasians. For several transporters, the variability in abundance was reduced significantly once the exclusion criteria were applied. The highest variability was observed for OATP1B3 > OATP1B1 > multidrug resistance protein 2 > multidrug resistance gene 1. No relationship was found between transporter expression and donor age. To our knowledge, this study provides the first in-depth analysis of current quantitative abundance data for a wide range of hepatic transporters, with the aim of using these data for in vitro–in vivo extrapolation, and highlights the significance of investigating the background of tissue(s) used in quantitative transporter proteomic studies. Similar studies are now warranted for other ethnicities.

Over the last 5 years the quantification of transporter-protein absolute abundances has dramatically increased in parallel to the expanded use of in vitro–in vivo extrapolation (IVIVE) and physiologically based pharmacokinetics (PBPK)-linked models, for decision-making in pharmaceutical company drug development pipelines and regulatory submissions. Although several research groups have developed laboratory-specific proteomic workflows, it is unclear if the large range of reported variability is founded on true interindividual variability or experimental variability resulting from sample preparation or the proteomic methodology used. To assess the potential for methodological bias on end-point abundance quantification, two independent laboratories, the University of Manchester (UoM) and Bertin Pharma (BPh), employing different proteomic workflows, quantified the absolute abundances of Na/K-ATPase, P-gp, and breast cancer resistance protein (BCRP) in the same set of biologic samples from human intestinal and Caco-2 cell membranes. Across all samples, P-gp abundances were significantly correlated (P = 0.04, Rs = 0.72) with a 2.4-fold higher abundance (P = 0.001) generated at UoM compared with BPh. There was a systematically higher BCRP abundance in Caco-2 cell samples quantified by BPh compared with UoM, but not in human intestinal samples. Consequently, a similar intestinal relative expression factor (REF), derived from distal jejunum and Caco-2 monolayer samples, between laboratories was found for P-gp. However, a 2-fold higher intestinal REF was generated by UoM (2.22) versus BPh (1.11). We demonstrate that differences in absolute protein abundance are evident between laboratories and they probably result from laboratory-specific methodologies relating to peptide choice.