In Vitro-In Vivo Extrapolation Scaling Factors for Intestinal P-glycoprotein and Breast Cancer Resistance Protein: Part II. The Impact of Cross-Laboratory Variations of Intestinal Transporter Relative Expression Factors on Predicted Drug Disposition

Physiologically based in vitro - In vivo correlation of modified release oral formulations with non-linear intestinal absorption: A case study using mirabegron

Establishing an in vitro - in vivo correlation (IVIVC) for oral modified release (MR) formulations would make it possible to substitute an in vitro dissolution test for human bioequivalence (BE) studies when changing the formulation or manufacturing methods. However, the number of IVIVC applications and approvals are reportedly low. One of the main reasons for failure to obtain IVIVCs using conventional methodologies may be the lack of consideration of the dissolution and absorption mechanisms of drugs in the physiological environment. In particular, it is difficult to obtain IVIVC using conventional methodologies for drugs with non-linear absorption processes. Therefore, the aim of the present study was to develop a physiologically based biopharmaceutics model (PBBM) that enables Level A IVIVCs for mirabegron MR formulations with non-linear absorption characteristics. Using human pharmacokinetic (PK) data for immediate-release formulations of mirabegron, the luminal drug concentration-dependent membrane permeation coefficient was calculated through curve fitting. The membrane permeation coefficient data were then applied to the human PK data of the MR formulations to estimate the in vivo dissolution rate by curve fitting. It was assumed that in vivo dissolution could be described using a zero-order rate equation. Furthermore, a Levy plot was generated using the estimated in vivo dissolution rate and the in vitro dissolution rate obtained from the literature. Finally, the dissolution rate of the MR formulations from the Levy plot was applied to the PBBM to predict the oral PK of the mirabegron MR formulations. This PB-IVIVC approach successfully generated linear Levy plots with slopes of almost 1.0 for MR formulations with different dose strengths and dissolution rates. The Cmax values of the MR formulations were accurately predicted using this approach, whereas the prediction errors for AUC exceeded the Level A IVIVC criteria. This can be attributed to the incomplete description of colonic absorption in the current PBBM.

Comparison of Relative Activity versus Relative Expression Factors (RAF versus REF) in Predicting Glucuronidation Mediated Drug Clearance Using Recombinant UGTs

PURPOSE

Predicting the quantitative fraction of glucuronidation (fgluc) by individual UDP-glucuronosyltransferase enzymes (UGTs) is challenging due to the lack of selective inhibitors and inconsistent activity of recombinant UGT systems (rUGTs). Our study compares the relative expression versus activity factors (REF versus RAF) to predict fgluc based on rUGT data to human liver and intestinal microsomes (HLM and HIM).

METHODS

REF scalars were derived from a previous in-house proteomics study for eleven UGT enzymes (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT1A10, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17), whereas RAF was calculated by measuring activities in rUGTs to microsomes of selective UGT probe substrates. Protein-normalized activity factor (pnAF) values were generated after correcting activity of individual UGTs to their corresponding protein abundance. The utility of REF and RAF in predicting fgluc was assessed for three UGT substrates-diclofenac, vorinostat, and raltegravir.

RESULTS

The REF values ranged from 0.02 to 1.75, RAF based on activity obtained in rUGTs to HLM/HIM were from 0.1 to 274. pnAF values were ~ 5 to 80-fold, except for UGT2B4 and UGT2B15, where pnAF was ~ 180 and > 1000, respectively. The results revealed confounding effect of differential specific activities (per pmol) of rUGTs in fgluc prediction.

CONCLUSION

The data suggest that the activity of UGT enzymes was significantly lower when compared to their activity in microsomes at the same absolute protein amount (pmol). Collectively, results of this study demonstrate poor and variable specific activity of different rUGTs (per pmol protein), as determined by pnAF values, which should be considered in fgluc scaling.

Understanding CYP3A4 and P-gp mediated drug-drug interactions through PBPK modeling - Case example of pralsetinib

Pralsetinib, a potent and selective inhibitor of oncogenic RET fusion and RET mutant proteins, is a substrate of the drug metabolizing enzyme CYP3A4 and a substrate of the efflux transporter P-gp based on in vitro data. Therefore, its pharmacokinetics (PKs) may be affected by co-administration of potent CYP3A4 inhibitors and inducers, P-gp inhibitors, and combined CYP3A4 and P-gp inhibitors. With the frequent overlap between CYP3A4 and P-gp substrates/inhibitors, pralsetinib is a challenging and representative example of the need to more quantitatively characterize transporter-enzyme interplay. A physiologically-based PK (PBPK) model for pralsetinib was developed to understand the victim drug-drug interaction (DDI) risk for pralsetinib. The key parameters driving the magnitude of pralsetinib DDIs, the P-gp intrinsic clearance and the fraction metabolized by CYP3A4, were determined from PBPK simulations that best captured observed DDIs from three clinical studies. Sensitivity analyses and scenario simulations were also conducted to ensure these key parameters were determined with sound mechanistic rationale based on current knowledge, including the worst-case scenarios. The verified pralsetinib PBPK model was then applied to predict the effect of other inhibitors and inducers on the PKs of pralsetinib. This work highlights the challenges in understanding DDIs when enzyme-transporter interplay occurs, and demonstrates an important strategy for differentiating enzyme/transporter contributions to enable PBPK predictions for untested scenarios and to inform labeling.

Novel Insights in Drug Transporter Sciences: the Year 2021 in Review

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding of drug transporters' role in drug disposition.As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue.

Application of proteomic data in the translation of in vitro observations to associated clinical outcomes

Translation of information on drug exposure and effect is facilitated by in silico models that enable extrapolation of in vitro measurements to in vivo clinical outcomes. These models integrate drug-specific data with information describing physiological processes and pathological changes, including alterations to proteins involved in drug absorption, distribution and elimination. Over the past 15 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. In this review, we explore current and emerging applications of targeted and global (untargeted) proteomics in translational pharmacology as well as strategies for improved integration into model-based drug development.

Inflammation Induces Changes in the Functional Expression of P-gp, BCRP, and MRP2: An Overview of Different Models and Consequences for Drug Disposition

The ATP-binding cassette (ABC) transporters play a key role in drug pharmacokinetics. These membrane transporters expressed within physiological barriers can be a source of pharmacokinetic variability. Changes in ABC transporter expression and functionality may consequently affect the disposition of substrate drugs, resulting in different drug exposure. Inflammation, present in several acute and chronic diseases, has been identified as a source of modulation in drug transporter expression leading to variability in drug response. Its regulation may be particularly dangerous for drugs with a narrow therapeutic index. In this context, numerous in vitro and in vivo models have shown up- or downregulation in the expression and functionality of ABC transporters under inflammatory conditions. Nevertheless, the existence of contradictory data and the lack of standardization for the models used have led to a less conclusive interpretation of these data.

Reduced physiologically-based pharmacokinetic model of dabigatran etexilate-dabigatran and its application for prediction of intestinal P-gp-mediated drug-drug interactions

BACKGROUND

Dabigatran etexilate (DABE) has been suggested as a clinical probe for intestinal P-glycoprotein (P-gp)-mediated drug-drug interaction (DDI) studies and, as an alternative to digoxin. Clinical DDI data with various P-gp inhibitors demonstrated a dose-dependent inhibition of P-gp with DABE. The aims of this study were to develop a joint DABE (prodrug)-dabigatran reduced physiologically-based-pharmacokinetic (PBPK) model and to evaluate its ability to predict differences in P-gp DDI magnitude between a microdose and a therapeutic dose of DABE.

METHODS

A joint DABE-dabigatran PBPK model was developed with a mechanistic intestinal model accounting for the regional P-gp distribution in the gastrointestinal tract. Model input parameters were estimated using DABE and dabigatran pharmacokinetic (PK) clinical data obtained after administration of DABE alone or with a strong P-gp inhibitor, itraconazole, and over a wide range of DABE doses (from 375 µg to 400 mg). Subsequently, the model was used to predict extent of DDI with additional P-gp inhibitors and with different DABE doses.

RESULTS

The reduced DABE-dabigatran PBPK model successfully described plasma concentrations of both prodrug and metabolite following administration of DABE at different dose levels and when co-administered with itraconazole. The model was able to capture the dose dependency in P-gp mediated DDI. Predicted magnitude of itraconazole P-gp DDI was higher at the microdose (predicted vs. observed median fold-increase in AUC_+inh/AUC_control (min-max) = 5.88 (4.29-7.93) vs. 6.92 (4.96-9.66) ) compared to the therapeutic dose (predicted median fold-increase in AUC_+inh/AUC_control = 3.48 (2.37-4.84) ). In addition, the reduced DABE-dabigatran PBPK model predicted successfully the extent of DDI with verapamil and clarithromycin as P-gp inhibitors. Model-based simulations of dose staggering predicted the maximum inhibition of P-gp when DABE microdose was concomitantly administered with itraconazole solution; simulations also highlighted dosing intervals required to minimise the DDI risk depending on the DABE dose administered (microdose vs. therapeutic).

CONCLUSIONS

This study provides a modelling framework for the evaluation of P-gp inhibitory potential of new molecular entities using DABE as a clinical probe. Simulations of dose staggering and regional differences in the extent of intestinal P-gp inhibition for DABE microdose and therapeutic dose provide model-based guidance for design of prospective clinical P-gp DDI studies.

Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes

Model-based assessment of the effects of liver disease on drug pharmacokinetics requires quantification of changes in enzymes and transporters responsible for drug metabolism and disposition. Different proteomic methods are currently used for protein quantification in tissues and in vitro systems, each with specific procedures and requirements. The outcome of quantitative proteomic assays using four different methods (one targeted and three label-free) applied to the same sample set was compared in this study. Three pooled cirrhotic liver microsomal samples corresponding to cirrhosis with nonalcoholic fatty liver disease, biliary disease, or cancer and a control microsomal pool were analyzed using quantification concatemer-based targeted proteomics, the total protein approach (TPA), high three ion intensity (Hi3) approach, and intensity-based absolute quantification (iBAQ) to determine the absolute and relative abundance in disease compared with control. The relative abundance data provided a "disease perturbation factor" (DPF) for each target protein. Absolute and relative abundances generated by standard-based label-free methods (iBAQ and Hi3) showed good agreement with targeted proteomics (limited bias and scatter), but TPA (standard-free method) overestimated absolute abundances by approximately 2-fold. The DPF was consistent between different proteomic methods but varied between enzymes and transporters, indicating discordance of effects of cirrhosis on various metabolism-related proteins. The DPF ranged from no change (e.g., for glucuronosyltransferase-1A6 in nonalcoholic fatty liver disease group) to less than 0.3 (e.g., carboxylesterases-1 in cirrhosis of biliary origin). SIGNIFICANCE STATEMENT: This study demonstrated that relative changes in enzymes and transporters (DPF) are independent of the quantitative proteomic methods used. Standard-based label-free methods, such as high three ion intensity (Hi3) and intensity-based absolute quantification (iBAQ) methods, were less biased and more precise than the total protein approach (TPA) when compared with targeted data. The DPF reconciled differences across proteomic methods observed with absolute levels. Using this approach, differences were revealed in the expression of enzymes/transporters in cirrhosis associated with different etiologies.

Optimization of dose and route of administration of the P-glycoprotein inhibitor, valspodar (PSC-833) and the P-glycoprotein and breast cancer resistance protein dual-inhibitor, elacridar (GF120918) as dual infusion in rats

Transporters can play a key role in the absorption, distribution, metabolism, and excretion of drugs. Understanding these contributions early in drug discovery allows for more accurate projection of the clinical pharmacokinetics. One method to assess the impact of transporters in vivo involves co‐dosing specific inhibitors. The objective of the present study was to optimize the dose and route of administration of a P‐glycoprotein (P‐gp) inhibitor, valspodar (PSC833), and a dual P‐gp/breast cancer resistance protein (BCRP) inhibitor, elacridar (GF120918), by assessing the transporters’ impact on brain penetration and absorption. A dual‐infusion strategy was implemented to allow for flexibility with dose formulation. The chemical inhibitor was dosed intravenously via the femoral artery, and a cassette of known substrates was infused via the jugular vein. Valspodar or elacridar was administered as 4.5‐hour constant infusions over a range of doses. To assess the degree of inhibition, the resulting ratios of brain and plasma concentrations, Kp's, of the known substrates were compared to the vehicle control. These data demonstrated that doses greater than 0.9 mg/hr/kg valspodar and 8.9 mg/hr/kg elacridar were sufficient to inhibit P‐gp‐ and BCRP‐mediated efflux at the blood‐brain barrier in rats without any tolerability issues. Confirmation of BBB restriction by efflux transporters in preclinical species allows for subsequent prediction in humans based upon the proteomic expression at rodent and human BBB. Overall, the approach can also be applied to inhibition of efflux at other tissues (gut absorption, liver clearance) or can be extended to other transporters of interest using alternate inhibitors.

Physiologically based pharmacokinetic/pharmacodynamic model for the prediction of morphine brain disposition and analgesia in adults and children

Morphine is a widely used opioid analgesic, which shows large differences in clinical response in children, even when aiming for equivalent plasma drug concentrations. Age-dependent brain disposition of morphine could contribute to this variability, as developmental increase in blood-brain barrier (BBB) P-glycoprotein (Pgp) expression has been reported. In addition, age-related pharmacodynamics might also explain the variability in effect. To assess the influence of these processes on morphine effectiveness, a multi-compartment brain physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) model was developed in R (Version 3.6.2). Active Pgp-mediated morphine transport was measured in MDCKII-Pgp cells grown on transwell filters and translated by an in vitro-in vivo extrapolation approach, which included developmental Pgp expression. Passive BBB permeability of morphine and its active metabolite morphine-6-glucuronide (M6G) and their pharmacodynamic parameters were derived from experiments reported in literature. Model simulations after single dose morphine were compared with measured and published concentrations of morphine and M6G in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF), as well as published drug responses in children (1 day– 16 years) and adults. Visual predictive checks indicated acceptable overlays between simulated and measured morphine and M6G concentration-time profiles and prediction errors were between 1 and -1. Incorporation of active Pgp-mediated BBB transport into the PB-PK/PD model resulted in a 1.3-fold reduced brain exposure in adults, indicating only a modest contribution on brain disposition. Analgesic effect-time profiles could be described reasonably well for older children and adults, but were largely underpredicted for neonates. In summary, an age-appropriate morphine PB-PK/PD model was developed for the prediction of brain pharmacokinetics and analgesic effects. In the neonatal population, pharmacodynamic characteristics, but not brain drug disposition, appear to be altered compared to adults and older children, which may explain the reported differences in analgesic effect.

Developmental processes in children can affect pharmacokinetics: “what the body does to the drug” as well as pharmacodynamics: “what the drug does to the body”. A typical example is morphine, of which the analgesic response is variable and particularly neonates suffer more often from respiratory depression, even when receiving doses corrected for differences in elimination. One way to mathematically incorporate developmental processes is by employing physiologically based pharmacokinetic/pharmacodynamic (PB-PK/PD) models, where physiological differences between individuals are incorporated. In this study, we developed a morphine PB-PK/PD model to predict brain drug disposition as well as analgesic response in adults and children, as both processes could potentially contribute to developmental variability in the effect of morphine. We found that age-related variation in BBB expression of the main morphine efflux transporter P-glycoprotein was not responsible for differences in brain exposure. In contrast, pharmacodynamic modelling suggested an increased sensitivity to morphine in neonates.

Quantification of Proteins Involved in Intestinal Epithelial Handling of Xenobiotics

The intestinal epithelium represents a natural barrier against harmful xenobiotics, while facilitating the uptake of nutrients and other substances. Understanding the interaction of chemicals with constituents of the intestinal epithelium and their fate in the body requires quantitative measurement of relevant proteins in in vitro systems and intestinal epithelium. Recent studies have highlighted the mismatch between messenger RNA (mRNA) and protein abundance for several drug‐metabolizing enzymes and transporters in the highly dynamic environment of the intestinal epithelium; mRNA abundances cannot therefore be used as a proxy for protein abundances in the gut, necessitating direct measurements. The objective was to determine the expression of a wide range proteins pertinent to metabolism and disposition of chemicals and nutrients in the intestinal epithelium. Ileum and jejunum biopsy specimens were obtained from 16 patients undergoing gastrointestinal elective surgery. Mucosal fractions were prepared and analyzed using targeted and global proteomic approaches. A total of 29 enzymes, 32 transporters, 6 tight junction proteins, 2 adhesion proteins, 1 alkaline phosphatase, 1 thioredoxin, 5 markers, and 1 regulatory protein were quantified—60 for the first time. The global proteomic method identified a further 5,222 proteins, which are retained as an open database for interested parties to explore. This study significantly expands our knowledge of a wide array of proteins important for xenobiotic handling in the intestinal epithelium. Quantitative systems biology models will benefit from the novel systems data generated in the present study and the translation path offered for in vitro to in vivo translation.

Mass spectrometry-based abundance atlas of ABC transporters in human liver, gut, kidney, brain and skin

ABC transporters (ATP-binding cassette transporter) traffic drugs and their metabolites across membranes, making ABC transporter expression levels a key factor regulating local drug concentrations in different tissues and individuals. Yet, quantification of ABC transporters remains challenging because they are large and low-abundance transmembrane proteins. Here, we analysed 200 samples of crude and membrane-enriched fractions from human liver, kidney, intestine, brain microvessels and skin, by label-free quantitative mass spectrometry. We identified 32 (out of 48) ABC transporters: ABCD3 was the most abundant in liver, whereas ABCA8, ABCB2/TAP1 and ABCE1 were detected in all tissues. Interestingly, this atlas unveiled that ABCB2/TAP1 may have TAP2-independent functions in the brain and that biliary atresia (BA) and control livers have quite different ABC transporter profiles. We propose that meaningful biological information can be derived from a direct comparison of these data sets.

Quantitative Proteomics of Clinically Relevant Drug-Metabolizing Enzymes and Drug Transporters and Their Intercorrelations in the Human Small Intestine

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.

Duodenum Intestine-Chip for preclinical drug assessment in a human relevant model

Induction of intestinal drug metabolizing enzymes can complicate the development of new drugs, owing to the potential to cause drug-drug interactions (DDIs) leading to changes in pharmacokinetics, safety and efficacy. The development of a human-relevant model of the adult intestine that accurately predicts CYP450 induction could help address this challenge as species differences preclude extrapolation from animals. Here, we combined organoids and Organs-on-Chips technology to create a human Duodenum Intestine-Chip that emulates intestinal tissue architecture and functions, that are relevant for the study of drug transport, metabolism, and DDI. Duodenum Intestine-Chip demonstrates the polarized cell architecture, intestinal barrier function, presence of specialized cell subpopulations, and in vivo relevant expression, localization, and function of major intestinal drug transporters. Notably, in comparison to Caco-2, it displays improved CYP3A4 expression and induction capability. This model could enable improved in vitro to in vivo extrapolation for better predictions of human pharmacokinetics and risk of DDIs.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.

Nanofibrous Scaffolds Support a 3D in vitro Permeability Model of the Human Intestinal Epithelium

Advances in drug research not only depend on high throughput screening to evaluate large numbers of lead compounds but also on the development of in vitro models which can simulate human tissues in terms of drug permeability and functions. Potential failures, such as poor permeability or interaction with efflux drug transporters, can be identified in epithelial Caco-2 monolayer models and can impact a drug candidate's progression onto the next stages of the drug development process. Whilst monolayer models demonstrate reasonably good prediction of in vivo permeability for some compounds, more developed in vitro tools are needed to assess new entities that enable closer in vivo in vitro correlation. In this study, an in vitro model of the human intestinal epithelium was developed by utilizing nanofibers, fabricated using electrospinning, to mimic the structure of the basement membrane. We assessed Caco-2 cell response to these materials and investigated the physiological properties of these cells cultured on the fibrous supports, focusing on barrier integrity and drug-permeability properties. The obtained data illustrate that 2D Caco-2 Transwell® cultures exhibit artificially high trans-epithelial electrical resistance (TEER) compared to cells cultured on the 3D nanofibrous scaffolds which show TEER values similar to ex vivo porcine tissue (also measured in this study). Furthermore, our results demonstrate that the 3D nanofibrous scaffolds influence the barrier integrity of the Caco-2 monolayer to confer drug-absorption properties that more closely mimic native gut tissue particularly for studying passive epithelial transport. We propose that this 3D model is a suitable in vitro model for investigating drug absorption and intestinal metabolism.

In Silico Prediction of the Absorption and Disposition of Cefadroxil in Humans using an Intestinal Permeability Method Scaled from Humanized PepT1 Mice

It is difficult to predict the pharmacokinetics and plasma concentration-time profiles of new chemical entities in humans based on animal data. Some pharmacokinetic parameters, such as clearance and volume of distribution, can be scaled allometrically from rodents, mammals, and nonhuman primates with good success. However, it is far more challenging to predict the oral pharmacokinetics of experimental drug candidates. In the present study, we used in situ estimates of intestinal permeability, obtained in silico and from rat, wild-type (WT), and humanized PepT1 (huPepT1) mice, to predict the systemic exposure of cefadroxil, an orally administered model compound, under a variety of conditions. Using the GastroPlus simulation software program (Simulations Plus, Lancaster, CA), we found that the C max and area under the plasma concentration-time curve from time zero to the last measurable concentration of cefadroxil were better predicted using intestinal permeability estimates (both segmental and jejunal) from huPepT1 than from WT mice, and that intestinal permeabilities based on in silico and rat estimates gave worse predictions. We also observed that accurate predictions were possible for cefadroxil during oral dose escalation (i.e., 5, 15, and 30 mg/kg cefadroxil), a drug-drug interaction study (i.e., 5 mg/kg oral cefadroxil plus 45 mg/kg oral cephalexin), and an oral multiple dose study [i.e., 500 mg (6.7 mg/kg) cefadroxil every 6 hours]. Finally, the greatest amount of cefadroxil was absorbed in duodenal and jejunal segments of the small intestine after a 5 mg/kg oral dose. Thus, by combining a humanized mouse model and in silico software, the present study offers a novel strategy for better translating preclinical pharmacokinetic data to oral drug exposure during first-in-human studies.

A physiologically based pharmacokinetic model for valacyclovir established based on absolute expression quantity of hPEPT1 and its application

In this study, a physiologically based pharmacokinetic (PBPK) model was established for valacyclovir based on absolute expression quantity of hPEPT1 along the entire length of the human intestine and other reliable in vitro, in vivo observed data. The PBPK model-3 defined acyclovir as metabolite of valacyclovir and simulated the plasma concentration-time profiles of valacyclovir and acyclovir simultaneously. It was validated strictly by a series of observed plasma concentration-time profiles. The average fold error (AFE) and absolute average fold error (AAFE) values were all smaller than 2. Then, it was used to quantitatively evaluate the effect of hPEPT1, luminal degradation rate, drug release rate and gastric residence time on the oral absorption of valacyclovir and acyclovir. The PBPK model-3 suggests that mainly 75% of valacyclovir was absorbed by active transport of hPEPT1. The luminal degradation of valacyclovir in the upper intestinal lumen cannot be considered the only reason for its incomplete bioavailability. The plasma concentration-time profiles of valacyclovir and its metabolite acyclovir were not sensitive to dissolution rate faster than T_85% = 120 min. Prolonged gastric residence time of sustained release tablet can improve the oral absorption of valacyclovir. All in all, the PBPK model-3 in this study is reliable and accurate. It is useful for the research of clinical application and dosage forms design of valacyclovir.

Targeted LC-MS/MS Proteomics-Based Strategy To Characterize in Vitro Models Used in Drug Metabolism and Transport Studies

Subcellular fractionation of tissue homogenate provides enriched in vitro models (e.g., microsomes, cytosol, or membranes), which are routinely used in the drug metabolism or transporter activity and protein abundance studies. However, batch-to-batch or interlaboratory variability in the recovery, enrichment, and purity of the subcellular fractions can affect performance of in vitro models leading to inaccurate in vitro to in vivo extrapolation (IVIVE) of drug clearance. To evaluate the quality of subcellular fractions, we developed a simple, targeted, and sensitive LC-MS/MS proteomics-based strategy, which relies on determination of protein markers of various cellular organelles, i.e., plasma membrane, cytosol, nuclei, mitochondria, endoplasmic reticulum (ER), lysosomes, peroxisomes, cytoskeleton, and exosomes. Application of the quantitative proteomics method confirmed a significant effect of processing variables (i.e., homogenization method and centrifugation speed) on the recovery, enrichment, and purity of isolated proteins in microsomes and cytosol. Particularly, markers of endoplasmic reticulum lumen and mitochondrial lumen were enriched in the cytosolic fractions as a result of their release during homogenization. Similarly, the relative recovery and composition of the total membrane fraction isolated from cell vs tissue samples was quantitatively different and should be considered in IVIVE. Further, analysis of exosomes isolated from sandwich-cultured hepatocyte media showed the effect of culture duration on compositions of purified exosomes. Therefore, the quantitative proteomics-based strategy developed here can be applied for efficient and simultaneous determination of multiple protein markers of various cellular organelles when compared to antibody- or activity-based assays and can be used for quality control of subcellular fractionation procedures including in vitro model development for drug metabolism and transport studies.

Identification and quantification of blood-brain barrier transporters in isolated rat brain microvessels

The blood-brain barrier (BBB) maintains brain homeostasis by tightly regulating the exchange of molecules with systemic circulation. It consists primarily of microvascular endothelial cells surrounded by astrocytic endfeet, pericytes, and microglia. Understanding the make-up of transporters in rat BBB is essential to the translation of pharmacological and toxicological observations into humans. In this study, experimental workflows are presented in which the optimization of (a) isolation of rat brain microvessels (b) enrichment of endothelial cells, and (c) extraction and digestion of proteins were evaluated, followed by identification and quantification of BBB proteins. Optimization of microvessel isolation was indicated by 15-fold enrichment of endothelial cell marker Glut1 mRNA, whereas markers for other cell types were not enriched. Filter-aided sample preparation was shown to be superior to in-solution sample preparation (10251 peptides vs. 7533 peptides). Label-free proteomics was used to identify nearly 2000 proteins and quantify 1276 proteins in isolated microvessels. A combination of targeted and global proteomics was adopted to measure protein abundance of 6 ATP-binding cassette and 27 solute carrier transporters. Data analysis using proprietary Progenesis and open access MaxQuant software showed overall agreement; however, Abcb9 and Slc22a8 were quantified only by MaxQuant, whereas Abcc9 and Abcd3 were quantified only by Progenesis. Agreement between targeted and untargeted quantification was demonstrated for Abcb1 (19.7 ± 1.4 vs. 17.8 ± 2.3) and Abcc4 (2.2 ± 0.7 vs. 2.1 ± 0.4), respectively. Rigorous quantification of BBB proteins, as reported in this study, should assist with translational modeling efforts involving brain disposition of xenobiotics.

Challenges with the precise prediction of ABC-transporter interactions for improved drug discovery

INTRODUCTION

Given that membrane efflux transporters can influence a drug's pharmacokinetics, efficacy and safety, identifying potential substrates and inhibitors of these transporters is a critical element in the drug discovery and development process. Additionally, it is important to predict the inhibition potential of new drugs to avoid clinically significant drug interactions. The goal of preclinical studies is to characterize a new drug as a substrate or inhibitor of efflux transporters. Areas covered: This article reviews preclinical systems that are routinely utilized to determine whether a new drug is substrate or inhibitor of efflux transporters including in silico models, in vitro membrane and cell assays, and animal models. Also included is an examination of studies comparing in vitro inhibition data to clinical drug interaction outcomes. Expert opinion: While a number of models are employed to classify a drug as an efflux substrate or inhibitor, there are challenges in predicting clinical drug interactions. Improvements could be made in these predictions through a tier approach to classify new drugs, validation of preclinical assays, and refinement of threshold criteria for clinical interaction studies.

Physiologically-based pharmacokinetic predictions of intestinal BCRP-mediated drug interactions of rosuvastatin in Koreans

It was recently reported that the C_max and AUC of rosuvastatin increases when it is coadministered with telmisartan and cyclosporine. Rosuvastatin is known to be a substrate of OATP1B1, OATP1B3, NTCP, and BCRP transporters. The aim of this study was to explore the mechanism of the interactions between rosuvastatin and two perpetrators, telmisartan and cyclosporine. Published (cyclosporine) or newly developed (telmisartan) PBPK models were used to this end. The rosuvastatin model in Simcyp (version 15)'s drug library was modified to reflect racial differences in rosuvastatin exposure. In the telmisartan–rosuvastatin case, simulated rosuvastatin C_maxI/C_max and AUC_I/AUC (with/without telmisartan) ratios were 1.92 and 1.14, respectively, and the T_max changed from 3.35 h to 1.40 h with coadministration of telmisartan, which were consistent with the aforementioned report (C_maxI/C_max: 2.01, AUC_I/AUC:1.18, T_max: 5 h → 0.75 h). In the next case of cyclosporine–rosuvastatin, the simulated rosuvastatin C_maxI/C_max and AUC_I/AUC (with/without cyclosporine) ratios were 3.29 and 1.30, respectively. The decrease in the CL_{int,BCRP,intestine} of rosuvastatin by telmisartan and cyclosporine in the PBPK model was pivotal to reproducing this finding in Simcyp. Our PBPK model demonstrated that the major causes of increase in rosuvastatin exposure are mediated by intestinal BCRP (rosuvastatin–telmisartan interaction) or by both of BCRP and OATP1B1/3 (rosuvastatin–cyclosporine interaction).

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity

Quantitative characterization of UDP-glucuronosyltransferase (UGT) enzymes is valuable in glucuronidation reaction phenotyping, predicting metabolic clearance and drug-drug interactions using extrapolation exercises based on pharmacokinetic modeling. Different quantitative proteomic workflows have been employed to quantify UGT enzymes in various systems, with reports indicating large variability in expression, which cannot be explained by interindividual variability alone. To evaluate the effect of methodological differences on end-point UGT abundance quantification, eight UGT enzymes were quantified in 24 matched liver microsomal samples by two laboratories using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT) standard, and measurements were assessed against catalytic activity in seven enzymes (n = 59). There was little agreement between individual abundance levels reported by the two methods; only UGT1A1 showed strong correlation [Spearman rank order correlation (Rs) = 0.73, P < 0.0001; R2 = 0.30; n = 24]. SIL-based abundance measurements correlated well with enzyme activities, with correlations ranging from moderate for UGTs 1A6, 1A9, and 2B15 (Rs = 0.52-0.59, P < 0.0001; R2 = 0.34-0.58; n = 59) to strong correlations for UGTs 1A1, 1A3, 1A4, and 2B7 (Rs = 0.79-0.90, P < 0.0001; R2 = 0.69-0.79). QconCAT-based data revealed generally poor correlation with activity, whereas moderate correlations were shown for UGTs 1A1, 1A3, and 2B7. Spurious abundance-activity correlations were identified in the cases of UGT1A4/2B4 and UGT2B7/2B15, which could be explained by correlations of protein expression between these enzymes. Consistent correlation of UGT abundance with catalytic activity, demonstrated by the SIL-based dataset, suggests that quantitative proteomic data should be validated against catalytic activity whenever possible. In addition, metabolic reaction phenotyping exercises should consider spurious abundance-activity correlations to avoid misleading conclusions.

Critical Issues and Optimized Practices in Quantification of Protein Abundance Level to Determine Interindividual Variability in DMET Proteins by LC-MS/MS Proteomics

Protein quantification data on drug metabolizing enzymes and transporters (collectively referred as DMET proteins) in human tissues are useful in predicting interindividual variability in drug disposition. While targeted proteomics is an emerging technique for quantification of DMET proteins, the methodology involves significant technical challenges especially when multiple samples are analyzed in a single study over a long period of time. Therefore, it is important to thoroughly address the critical variables that could affect DMET protein quantification.

Physiologically Based Oral Absorption Modelling to Study Gut-Level Drug Interactions

Physiologically based oral absorption models are in silico tools primarily used to guide formulation development and project the clinical performance of formulation variants. This commentary briefly discusses additional oral absorption model applications, focusing on gut-level drug interactions. Gut-level drug interactions can involve drug degradation, metabolic enzymes, transporters, gastrointestinal motility modulators, acid-reducing agents, and food. The growth in publications reporting physiologically based oral absorption model utilization and successful pharmacokinetic prediction (e.g., after acid-reducing agents or food coadministration) indicate that oral absorption models have achieved a level of maturity within the industry particularly over the past 15 years. Provided appropriate data and model validation, oral absorption modeling/simulation may serve as a surrogate for clinical studies by providing both mechanistic and quantitative understanding of oral delivery considerations on pharmacokinetics.

Retracted: Physiologically based pharmacokinetic predictions of intestinal BCRP-mediated effect of telmisartan on the pharmacokinetics of rosuvastatin in humans

'Physiologically based pharmacokinetic predictions of intestinal BCRP-mediated effect of telmisartan on the pharmacokinetics of rosuvastatin in humans' by Soo Hyeon Bae, Wan-Su Park, Seunghoon Han, Gab-jin Park, Jongtae Lee, Taegon Hong, Sangil Jeon and Dong-Seok Yim The above article, published online on 06 February 2017 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, the journal Editor in Chief, K. Sandy Pang, and John Wiley & Sons, Ltd. The authors retracted the paper due to errors associated with use of log D vs. log P of telmisartan as inputs of the PBPK model. The authors concluded that there are too many changes in the article to be resolved by an Erratum, and had requested a retraction. Reference Bae, S. H., Park, W.-S., Han, S., Park, G., Lee, J., Hong, T., Jeon, S., and Yim, D.-S. (2016) Physiologically based pharmacokinetic predictions of intestinal BCRP-mediated effect of telmisartan on the pharmacokinetics of rosuvastatin in humans. Biopharm. Drug Dispos., doi: 10.1002/bdd.2060.

Regional Expression Levels of Drug Transporters and Metabolizing Enzymes along the Pig and Human Intestinal Tract and Comparison with Caco-2 Cells

Intestinal transporter proteins and metabolizing enzymes play a crucial role in the oral absorption of a wide variety of drugs. The aim of the current study was to characterize better available intestinal in vitro models by comparing expression levels of these proteins and enzymes between porcine intestine, human intestine, and Caco-2 cells. We therefore determined the absolute protein expression of 19 drug transporters and the mRNA expression of 12 metabolic enzymes along the pig intestinal tract (duodenum, jejunum, ileum; N = 4), in human intestine (jejunum; N = 9), and Caco-2 cells. Expression of the included transporters and enzymes was in general well comparable between porcine and human intestinal tissue, although breast cancer resistance protein, monocarboxylate transporter 5, multidrug resistance protein (MRP) 1, MRP1, MRP3 (∼2-fold), and organic anion-transporting polypeptide (OATP) 4A1 (∼6-fold) was higher expressed in pig compared with human jejunum. Alternatively, expression level of relevant transporter proteins (glucose transporter 1, OATP4A1, MRP2, MRP1, and OATP2B1) was significantly higher (3- to 130-fold) in Caco-2 cells compared with human jejunum. Moreover, all examined CYPs showed at least a fivefold lower gene expression in Caco-2 cells compared with human jejunum, with the smallest differences for CYP1A1 and CYP3A5 and the largest difference for CYP3A4 (871-fold higher expression in human jejunum compared with Caco-2 cells). In conclusion, a comprehensive overview is provided of the expression levels of clinically relevant transporter proteins and metabolic enzymes in porcine and human intestinal tissue and Caco-2 cells, which may assist in deciding upon the most suitable model to further improve our understanding of processes that determine intestinal absorption of compounds.