Models to predict unbound intracellular drug concentrations in the presence of transporters

Identification of potential SARS-CoV-2 inhibitors among well-tolerated drugs using drug repurposing and in vitro approaches

The 3C-like protease (3CLpro) is essential in the SARS-CoV-2 life cycle and a promising target for antiviral drug discovery, as no similar proteases exist in humans. This study aimed to identify effective SARS-CoV-2 inhibitors among FDA-approved drugs. Previous computational analysis revealed several drugs with high binding affinity to the 3CLpro active site. In vitro enzymatic assays confirmed that ten of these drugs effectively inhibited the enzyme. To evaluate their impact on viral replication, we used non-infectious SARS-CoV-2 sub-genomic replicons in lung and intestinal cells. Amcinonide, eltrombopag, lumacaftor, candesartan, and nelfinavir inhibited replication at low micromolar concentrations. Lumacaftor showed IC50 values of 964 nM in Caco-2 cells and 458 nM in Calu-3 cells, while candesartan had IC50 values of 714 nM and 1.05 µM, respectively. Furthermore, dual combination experiments revealed that amcinonide, pimozide, lumacaftor, and eltrombopag acted as potent inhibitors at nanomolar concentrations when combined with candesartan. This study highlights lumacaftor, candesartan, and nelfinavir as effective inhibitors of SARS-CoV-2 replication in vitro and emphasizes their potential for repurposing as antiviral treatments. These findings support future clinical trials and may lead to breakthroughs in COVID-19 treatment strategies.

Transporter-mediated drug-drug interactions: regulatory guidelines, in vitro and in vivo methodologies and translation, special populations, and the blood-brain barrier

This review, part of a special issue on drug-drug interactions (DDIs) spearheaded by the International Society for the Study of Xenobiotics (ISSX) New Investigators, explores the critical role of drug transporters in absorption, disposition, and clearance in the context of DDIs. Over the past two decades, significant advances have been made in understanding the clinical relevance of these transporters. Current knowledge on key uptake and efflux transporters that affect drug disposition and development is summarized. Regulatory guidelines from the FDA, EMA, and PMDA that inform the evaluation of potential transporter-mediated DDIs are discussed in detail. Methodologies for preclinical and clinical testing to assess potential DDIs are reviewed, with an emphasis on the utility of physiologically based pharmacokinetic (PBPK) modeling. This includes the application of relative abundance and expression factors to predict human pharmacokinetics (PK) using preclinical data, integrating the latest regulatory guidelines. Considerations for assessing transporter-mediated DDIs in special populations, including pediatric, hepatic, and renal impairment groups, are provided. Additionally, the impact of transporters at the blood-brain barrier (BBB) on the disposition of CNS-related drugs is explored. Enhancing the understanding of drug transporters and their role in drug disposition and toxicity can improve efficacy and reduce adverse effects. Continued research is essential to bridge remaining gaps in knowledge, particularly in comparison with cytochrome P450 (CYP) enzymes.

Predicting Impact of Food and Feeding Time on Oral Absorption of Drugs with a Novel Rat Continuous Intestinal Absorption Model

Intricacies in intestinal physiology, drug properties, and food effects should be incorporated into models to predict complex oral drug absorption. A previously published human continuous intestinal absorption model based on the convection-diffusion equation was modified specifically for the male Sprague-Dawley rat in this report. Species-specific physiologic conditions along intestinal length - experimental velocity and pH under fasted and fed conditions, were measured and incorporated into the intestinal absorption model. Concentration-time (C-t) profiles were measured upon a single intravenous and peroral (PO) dose for three drugs: amlodipine (AML), digoxin (DIG), and glyburide (GLY). Absorption profiles were predicted and compared with experimentally collected data under three feeding conditions: 12-hour fasted rats were provided food at two specific times after oral drug dose (1 hour and 2 hours for AML and GLY; 0.5 hours and 1 hour for DIG), or they were provided food for the entire study. Intravenous versus PO C-t profiles suggested absorption even at later times and informed design of appropriate mathematical input functions based on experimental feeding times. With this model, AML, DIG, and GLY oral C-t profiles for all feeding groups were generally well predicted, with exposure overlap coefficients in the range of 0.80-0.97. Efflux transport for DIG and uptake and efflux transport for GLY were included, modeling uptake transporter inhibition in the presence of food. Results indicate that the continuous intestinal rat model incorporates complex physiologic processes and feeding times relative to drug dose into a simple framework to provide accurate prediction of oral absorption. SIGNIFICANCE STATEMENT: A novel rat continuous intestinal model predicts drug absorption with respect to time and intestinal length. Feeding time relative to dose was modeled as a key effect. Experimental fasted/fed intestinal pH and velocity, efflux and uptake transporter expression along intestinal length, and uptake transporter inhibition in the presence of food were modeled. The model uses the pharmacokinetic profiles of three model drugs and provides a novel framework to study food effects on absorption.

Relationship between plasma and intracellular concentrations of bedaquiline and its M2 metabolite in South African patients with rifampin-resistant TB

Bedaquiline is recommended for the treatment of all patients with rifampin-resistant tuberculosis (RR-TB). Bedaquiline accumulates within cells, but its intracellular pharmacokinetics have not been characterized, which may have implications for dose optimization. We developed a novel assay using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) to measure the intracellular concentrations of bedaquiline and its primary metabolite M2 in patients with RR-TB in South Africa. Twenty-one participants were enrolled and underwent sparse sampling of plasma and peripheral blood mononuclear cells (PBMCs) at months 1, 2, and 6 of treatment and at 3 and 6 months after bedaquiline treatment completion. Intensive sampling was performed at month 2. We used noncompartmental analysis to describe plasma and intracellular exposures and a population pharmacokinetic model to explore the relationship between plasma and intracellular pharmacokinetics and the effects of key covariates. Bedaquiline concentrations from month 1 to month 6 of treatment ranged from 94.7 to 2,540 ng/ml in plasma and 16.2 to 5,478 ng/ml in PBMCs, and concentrations of M2 over the 6-month treatment period ranged from 34.3 to 496 ng/ml in plasma and 109.2 to 16,764 ng/ml in PBMCs. Plasma concentrations of bedaquiline were higher than those of M2, but intracellular concentrations of M2 were considerably higher than those of bedaquiline. In the pharmacokinetic modeling, we estimated a linear increase in the intracellular-plasma accumulation ratio for bedaquiline and M2, reaching maximum effect after 2 months of treatment. The typical intracellular-plasma ratios 1 and 2 months after start of treatment were 0.61 (95% confidence interval [CI]: 0.42 to 0.92) and 1.10 (95% CI: 0.74 to 1.63) for bedaquiline and 12.4 (95% CI: 8.8 to 17.8) and 22.2 (95% CI: 15.6 to 32.3) for M2. The intracellular-plasma ratios for both bedaquiline and M2 were decreased by 54% (95% CI: 24 to 72%) in HIV-positive patients compared to HIV-negative patients. Bedaquiline and M2 were detectable in PBMCs 6 months after treatment discontinuation. M2 accumulated at higher concentrations intracellularly than bedaquiline, supporting in vitro evidence that M2 is the main inducer of phospholipidosis.

Successful Prediction of Human Steady-State Unbound Brain-to-Plasma Concentration Ratio of P-gp Substrates Using the Proteomics-Informed Relative Expression Factor Approach

In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug's human steady-state unbound brain interstitial fluid-to-plasma concentration ratio (K_p,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P-glycoprotein, P-gp). Due to lack of good in vitro human blood-brain barrier models, we and others have advocated the use of a proteomics-informed relative expressive factor (REF) approach to predict K_p,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P-gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N-desmethyl loperamide, and metoclopramide was determined in human P-gp-transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, K_p,uu,brain of the drug was predicted using REF (ER approach). Alternatively, in vitro passive and P-gp-mediated intrinsic clearances (CLs) of these drugs, estimated using a five-compartmental model, were extrapolated to in vivo using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted K_p,uu,brain of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N-desmethyl loperamide. Using the in vitro-to-in vivo extrapolated clearance approach, K_p,uu,brain was reasonably well predicted but not the brain unbound interstitial fluid drug concentration-time profile. Therefore, we propose that the ER approach be used to predict K_p,uu,brain of CNS candidate drugs to enhance their success in development.

Consideration of the Unbound Drug Concentration in Enzyme Kinetics

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system(s) under investigation. As a consequence, the apparent kinetic parameters, such as K_m or K_i, that are derived can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components which can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

Case Study 8: Status of the Structural Mass Action Kinetic Model of P-gp-Mediated Transport Through Confluent Cell Monolayers

In the first edition of this book, we presented the basics of explicitly incorporating the lipid biochemistry into a confluent cell monolayer transport model and the novel findings of this model up to 2013, including the use of global optimization to fit the elementary rate constants and the efflux active P-glycoprotein (P-gp) membrane concentrations for the transport of four P-gp substrates across MDCKII-hMDR1-NKI confluent cell monolayers. This chapter is an update on that model, which has been focused primarily on discovering how microvilli morphology regulates the efflux active P-gp and the existence of, as yet, unidentified uptake transporters of P-gp substrates in all of the commonly used P-gp expressing cell lines used in the pharmaceutical industry, thereby adding new players to DDI predictions and IVIVE. The structural mass action kinetic model uses the general mass action reactions for P-gp binding and efflux, with the membrane structural parameters for the confluent cell monolayer to predict drug transport over time. Binding of drug to P-gp occurs within the cytosolic monolayer of the apical membrane, according to (a) the molar partition coefficient of the drug to the cytosolic monolayer and (b) the association rate constant, k₁ (M^-1 s^-1), of the drug from the basolateral or apical outer monolayers into the P-gp binding site. Release of substrate from P-gp back into the cytosolic monolayer occurs with a dissociation rate constant k_r (s^-1) or, much less frequently, into the apical aqueous chamber with an efflux rate constant k₂ (s^-1). The model fits the efflux active P-gp concentration, T(0), i.e., the P-gp whose effluxed drug actually reaches the apical aqueous chamber, as opposed to the majority of P-gp whose effluxed drug is reabsorbed back into the same or neighboring microvilli prior to reaching the apical aqueous chamber. Efflux active P-gp largely resides near the tips of the microvilli. We have shown using kinetics and structured illumination microscopy that: (a) efflux active P-gp is controlled by microvilli morphology; (b) there are apical (AT) and basolateral (BT) uptake transporters for P-gp substrates in most, if not all, P-gp expressing cell lines used in the pharmaceutical industry, which exist, but which remain unidentified; (c) the lab-to-lab variability in P-gp IC₅₀ values observed in the P-gp IC₅₀ initiative was due to the conflated inhibition of P-gp and the basolateral digoxin uptake transporters by all 15 P-gp substrates tested in that study; (d) even the IC₅₀ values for P-gp inhibition alone do not obey the Cheng-Prusoff relationship; (e) the fitted elementary rate constants and the molecular dissociation constant Ki for this kinetic model are system independent; and (f) the time dependence of product formation for these confluent cell monolayers is correlated with the P-gp V_max/K_m, when defined by its fitted elementary rate constants and uptake transporter clearances, without any steady-state assumptions.

P-glycoprotein Substrate Assessment in Drug Discovery: Application of Modeling to Bridge Differential Protein Expression Across In Vitro Tools

P-glycoprotein (P-gp) efflux assay is an integral part of discovery screening, especially for drugs requiring brain penetration as P-gp efflux ratio (ER) inversely correlates with brain exposure. However, significant variability in P-gp ER generated across cell lines can lead to misclassification of a P-gp substrate and subsequently disconnect with brain exposure data. We hypothesized that the ER depends on P-gp protein expression level in the in vitro assay. Quantitative proteomics and immunofluorescence staining were utilized to characterize P-gp protein expression and localization in four recombinant cell lines, over-expressing human or mouse P-gp isoforms, followed by functional evaluation. Efflux data generated in each cell line was compared against available rodent brain distribution data. The results suggested that the cell line with highest P-gp expression (hMDCK-MDR1 sourced from NIH) led to greatest dynamic range for efflux; thus, proving to be the most sensitive model to predict brain penetration. Cell lines with lower P-gp expression exhibited the greatest tendency for compound-dependent in vitro efflux saturation leading to false negative results. Ultimately, P-gp kinetics were characterized using a compartmental model to generate system-independent parameters to resolve such discrepancy. This study highlights the need for careful choice of well characterized P-gp in vitro tools and utility of modeling techniques to enable appropriate interpretation of the data.

Impact of In Vitro Passive Permeability in a P-gp-transfected LLC-PK1 Model on the Prediction of the Rat and Human Unbound Brain-to-Plasma Concentration Ratio

PURPOSE

More accurate prediction of the extent of drug brain exposure in early drug discovery and understanding potential species differences could help to guide medicinal chemistry and avoid unnecessary animal studies. Hence, the aim of the current study was to validate the use of a P-gp transfected LLC-PK1 model to predict the unbound brain-to-plasma concentration ratio (Kp_uu,brain) in rats and humans.

METHODS

MOCK-, Mdr1a- and MDR1-transfected LLC-PK1 monolayers were applied in a transwell setup to quantify the bidirectional transport for 12 specific P-gp substrates, 48 UCB drug discovery compounds, 11 compounds with reported rat in situ brain perfusion data and 6 compounds with reported human Kp_uu,brain values. The in vitro transport data were introduced in a minimal PBPK model (SIVA®) to determine the transport parameters. These parameters were combined with the differences between in vitro and in vivo passive permeability as well as P-gp expression levels (as determined by LC-MS/MS), to predict the Kp_uu,brain.

RESULTS

A 10-fold difference between in vitro and in vivo passive permeability was observed. Incorporation of the differences between in vitro and in vivo passive permeability and P-gp expression levels resulted in an improved prediction of rat (AAFE 2.17) and human Kp_uu,brain (AAFE 2.10).

CONCLUSIONS

We have succesfully validated a methodology to use a P-gp overexpressing LLC-PK1 cell line to predict both rat and human Kp_uu,brain by correcting for both passive permeability and P-gp expression levels.

Simplified Method to Determine the Efflux Ratio on P-Glycoprotein Substrates Using Three-Compartment Model Analysis for Caco-2 Cell Assay Data

PURPOSE

Multiple time-point sampling is required in transcellular transport studies to accurately calculate the appropriate efflux ratio (ER). Our study sought to develop a simplified method to determine the ER in Caco-2 cells.

METHODS

The equation for the ER was derived from a three-compartment model of apical to basal and basal to apical transport. Transcellular transport studies were conducted with 10 non-P-glycoprotein (P-gp) and 6 P-gp substrates in Caco-2 cells, and the ER was calculated using this equation.

RESULTS

The equation for the ER used the concentration ratio in the receiver compartment at the same time-point; therefore, the ER can theoretically be calculated using only a single point. The ER of all non-P-gp substrates tested was close to 1 at all sampling times. The ERs of cyclosporine A calculated from the concentration ratio at 30, 60, 90, and 120 min incubation were 2.93, 6.43, 7.12, and 9.57, respectively, and the ER at 120 min was almost identical to the theoretical value (9.62) calculated using three-compartment model analysis. The other 5 P-gp substrates showed a similar tendency. Single-point sampling can be used to accurately calculate ER at 120 min.

CONCLUSIONS

Single-point sampling is a promising approach for calculating appropriate ERs in the drug discovery stage.

A hybrid model to evaluate the impact of active uptake transport on hepatic distribution of atorvastatin in rats

1. Mathematical modeling remains a useful tool to study the impact of transporters on overall and intracellular drug disposition. The impact of organic anion transporter protein mediated uptake on atorvastatin systemic and intracellular pharmacokinetics, specifically distribution volume, was studied in rats with mathematical modeling and conducting in vivo pharmacokinetic studies for atorvastatin in presence and absence of rifampicin. A previously developed 5-compartment explicit membrane model for the liver was combined with a compartmental model to develop a semi-physiological hybrid model for atorvastatin disposition. 2. Rifampicin treatment resulted in a decrease in systemic clearance and steady-state distribution volume, and an increase in half-life of atorvastatin. The hybrid model predicted higher unbound intracellular liver atorvastatin concentrations than unbound plasma concentrations in both rifampicin treated and untreated groups, indicating involvement of uptake transporters. The intracellular unbound concentrations during the distributive phase were unaffected by rifampicin. The dependence of clearance on blood flow as well as hepatic uptake for atorvastatin (a moderate-to-high extraction ratio drug) can explain this lack of change in intracellular concentrations if there is incomplete inhibition of transport at the tested rifampicin dose. 3. The hybrid model successfully allowed the evaluation of effect of active uptake on intracellular and plasma atorvastatin disposition.

Methods to Predict Volume of Distribution

PURPOSE OF REVIEW

Prior to human studies, knowledge of drug disposition in the body is useful to inform decisions on drug safety and efficacy, first in human dosing, and dosing regimen design. It is therefore of interest to develop predictive models for primary pharmacokinetic parameters, clearance, and volume of distribution. The volume of distribution of a drug is determined by the physiological properties of the body and physiochemical properties of the drug, and is used to determine secondary parameters, including the half-life. The purpose of this review is to provide an overview of current methods for the prediction of volume of distribution of drugs, discuss a comparison between the methods, and identify deficiencies in current predictive methods for future improvement.

RECENT FINDINGS

Several volumes of distribution prediction methods are discussed, including preclinical extrapolation, physiological methods, tissue composition-based models to predict tissue:plasma partition coefficients, and quantitative structure-activity relationships. Key factors that impact the prediction of volume of distribution, such as permeability, transport, and accuracy of experimental inputs, are discussed. A comparison of current methods indicates that in general, all methods predict drug volume of distribution with an absolute average fold error of 2-fold. Currently, the use of composition-based PBPK models is preferred to models requiring in vivo input.

SUMMARY

Composition-based models perfusion-limited PBPK models are commonly used at present for prediction of tissue:plasma partition coefficients and volume of distribution, respectively. A better mechanistic understanding of important drug distribution processes will result in improvements in all modeling approaches.

Three-Compartment Model Analysis with Minimal Sampling Points in the Caco-2 Permeability Assay

The purpose of this study was to establish a modified method of three-compartment model analysis that minimized the sampling frequency. A Caco-2 permeability assay was performed on ten structurally diverse compounds with passive diffusion. A three-compartment model was analyzed by a conventional method and a method with fewer sampling points, called the simplified method, using concentration-time profiles in the donor, intracellular, and receiver compartments. The concentration-time profiles in all compartments were well described by the conventional method. The calculated unbound fraction of intracellular (fu₂) and apparent permeability coefficient (P_app) were 0.0107-1.22 and 0.886-146 × 10^-6 cm/s, respectively. The simplified method also described the concentration profiles in the compartments of all ten compounds except one, ibuprofen. The difference in values calculated by the simplified method compared to the conventional method was between -7 and 7% for fu₂ and between -6 and 42% for P_app. These results suggested that the parameter values from the simplified method were comparable with those from the conventional method. The simplified method may be a promising approach to improve the throughput of three-compartment model analyses of Caco-2 permeability assays in the early stages of drug discovery.

Evaluation of Drug Biliary Excretion Using Sandwich-Cultured Human Hepatocytes

Evaluation of hepatobiliary transport of drugs is an important challenge, notably during the development of new molecular identities. In this context, sandwich-cultured human hepatocytes (SCHH) have been proposed as an interesting and integrated tool for predicting in vitro biliary excretion of drugs. The present review was therefore designed to summarize key findings about SCHH, including their establishment, their main functional features and their use for the determination of canalicular transport and the prediction of in vivo biliary clearance and hepatobiliary excretion-related drug-drug interactions. Reviewed data highlight the fact that SCHH represent an original and probably unique holistic in vitro approach to predict biliary clearance in humans, through taking into account sinusoidal drug uptake, passive drug diffusion, drug metabolism and sinusoidal and canalicular drug efflux. Limits and proposed refinements for SCHH-based analysis of drug biliary excretion, as well as putative human alternative in vitro models to SCHH are also discussed.

A Tiered Approach for the Evaluation of the Safety of Botanicals Used as Dietary Supplements: An Industry Strategy

Exposure to botanicals in dietary supplements is increasing across many geographies; with increased expectations from consumers, regulators, and industry stewards centered on quality and safety of these products. We present a tiered approach to assess the safety of botanicals, and an in silico decision tree to address toxicity data gaps. Tier 1 describes a Threshold of Toxicologic Concern (TTC) approach that can be used to assess the safety of conceptual levels of botanicals. Tier 2 is an approach to document a history of safe human use for botanical exposures higher than the TTC. An assessment of botanical-drug interaction (BDI) may also be necessary at this stage. Tier 3 involves botanical chemical constituent identification and safety assessment and the in silico approach as needed. Our novel approaches to identify potential hazards and establish safe human use levels for botanicals is cost and time efficient and minimizes reliance on animal testing.

Cellular Pharmacokinetic Model-Based Analysis of Genistein, Glyceollin, and MK-571 Effects on 5 (and 6)-Carboxy-2',7'-Dichloroflourescein Disposition in Caco-2 Cells

Pharmacokinetic modeling was used to describe 5 (and 6)-carboxy-2',7'-dichloroflourescein (CDF) disposition in Caco-2 cells following CDF or CDFDA (CDF diacetate) dosing. CDF transcellular flux was modeled by simple passive diffusion. CDFDA dosing models were based on simultaneous fitting of CDF levels in apical, basolateral, and intracellular compartments. Predicted CDF efflux was 50% higher across the apical versus the basolateral membrane. This difference was similar following apical and basolateral CDFDA dosing, despite intracellular levels being 3-fold higher following basolateral dosing, thus supporting nonsaturable CDF efflux kinetics. A 3-compartment catenary model with intracellular CDFDA hydrolysis described CDF disposition. This model predicted that apical CDF efflux was not altered in the presence of MK-571, and that basolateral membrane clearance was enhanced to account for reduced intracellular CDF in the presence of this multidrug resistance-associated protein (MRP) inhibitor. Similar effects were predicted for glyceollin, while genistein exposure had no predicted effects on CDF efflux. These modulator effects are discussed in the context of model predicted intracellular CDF concentrations relative to reports of CDF affinity (measured by Km) for MRP2 and MRP3. This model-based analysis confirms the complexity of efflux kinetics and suggests that other transporters may have contributed to CDF efflux.

Physiologically Based Pharmacokinetic Modeling Suggests Limited Drug-Drug Interaction Between Clopidogrel and Dasabuvir

Dasabuvir, a nonnucleoside NS5B polymerase inhibitor, is a sensitive substrate of cytochrome P450 (CYP) 2C8 with a potential for drug-drug interaction (DDI) with clopidogrel. A physiologically based pharmacokinetic (PBPK) model was developed for dasabuvir to evaluate the DDI potential with clopidogrel, the acyl-β-D glucuronide metabolite of which has been reported as a strong mechanism-based inhibitor of CYP2C8 based on an interaction with repaglinide. In addition, the PBPK model for clopidogrel and its metabolite were updated with additional in vitro data. Sensitivity analyses using these PBPK models suggested that CYP2C8 inhibition by clopidogrel acyl-β-D glucuronide may not be as potent as previously suggested. The dasabuvir and updated clopidogrel PBPK models predict a moderate increase of 1.5-1.9-fold for Cmax and 1.9-2.8-fold for AUC of dasabuvir when coadministered with clopidogrel. While the PBPK results suggest there is a potential for DDI between dasabuvir and clopidogrel, the magnitude is not expected to be clinically relevant.

Chemoresistance in cancer cells: exosomes as potential regulators of therapeutic tumor heterogeneity

Drug resistance in cancer cells remains a fundamental challenge. Be it nontargeted or targeted drugs, the presence of intrinsic or acquired cancer cell resistance remains a great obstacle in chemotherapy. Conventionally, a spectrum of cellular mechanisms defines drug resistance including overexpression of antiapoptotic proteins and drug efflux pumps, mutations in target and synergistic activation of prosurvival pathways in tumor cells. In addition to these well-studied routes, exosome-induced chemoresistance is emerging as a novel mechanism. Mechanistically, exosomes impart resistance by direct drug export, transport of drug efflux pumps and miRNAs exchange among cells. Moreover, exosome signaling creates ‘therapeutic tumor heterogeneity’ and favorably condition tumor microenvironment. Here, we discuss exosomes’ role in chemoresistance and possibilities of developing novel therapeutic strategies.

Evaluation of transporters in drug development: Current status and contemporary issues

Transporters govern the access of molecules to cells or their exit from cells, thereby controlling the overall distribution of drugs to their intracellular site of action. Clinically relevant drug-drug interactions mediated by transporters are of increasing interest in drug development. Drug transporters, acting alone or in concert with drug metabolizing enzymes, can play an important role in modulating drug absorption, distribution, metabolism and excretion, thus affecting the pharmacokinetics and/or pharmacodynamics of a drug. The drug interaction guidance documents from regulatory agencies include various decision criteria that may be used to predict the need for in vivo assessment of transporter-mediated drug-drug interactions. Regulatory science research continues to assess the prediction performances of various criteria as well as to examine the strength and limitations of each prediction criterion to foster discussions related to harmonized decision criteria that may be used to facilitate global drug development. This review discusses the role of transporters in drug development with a focus on methodologies in assessing transporter-mediated drug-drug interactions, challenges in both in vitro and in vivo assessments of transporters, and emerging transporter research areas including biomarkers, assessment of tissue concentrations, and effect of diseases on transporters.

In Vitro and in Silico Tools To Assess Extent of Cellular Uptake and Lysosomal Sequestration of Respiratory Drugs in Human Alveolar Macrophages

Accumulation of respiratory drugs in human alveolar macrophages (AMs) has not been extensively studied in vitro and in silico despite its potential impact on therapeutic efficacy and/or occurrence of phospholipidosis. The current study aims to characterize the accumulation and subcellular distribution of drugs with respiratory indication in human AMs and to develop an in silico mechanistic AM model to predict lysosomal accumulation of investigated drugs. The data set included 9 drugs previously investigated in rat AM cell line NR8383. Cell-to-unbound medium concentration ratio (K_p,cell) of all drugs (5 μM) was determined to assess the magnitude of intracellular accumulation. The extent of lysosomal sequestration in freshly isolated human AMs from multiple donors (n = 5) was investigated for clarithromycin and imipramine (positive control) using an indirect in vitro method (±20 mM ammonium chloride, NH₄Cl). The AM cell parameters and drug physicochemical data were collated to develop an in silico mechanistic AM model. Three in silico models differing in their description of drug membrane partitioning were evaluated; model (1) relied on octanol-water partitioning of drugs, model (2) used in vitro data to account for this process, and model (3) predicted membrane partitioning by incorporating AM phospholipid fractions. In vitro K_p,cell ranged >200-fold for respiratory drugs, with the highest accumulation seen for clarithromycin. A good agreement in K_p,cell was observed between human AMs and NR8383 (2.45-fold bias), highlighting NR8383 as a potentially useful in vitro surrogate tool to characterize drug accumulation in AMs. The mean K_p,cell of clarithromycin (81, CV = 51%) and imipramine (963, CV = 54%) were reduced in the presence of NH₄Cl by up to 67% and 81%, respectively, suggesting substantial contribution of lysosomal sequestration and intracellular binding in the accumulation of these drugs in human AMs. The in vitro data showed variability in drug accumulation between individual human AM donors due to possible differences in lysosomal abundance, volume, and phospholipid content, which may have important clinical implications. Consideration of drug-acidic phospholipid interactions significantly improved the performance of the in silico models; use of in vitro K_p,cell obtained in the presence of NH₄Cl as a surrogate for membrane partitioning (model (2)) captured the variability in clarithromycin and imipramine K_p,cell observed in vitro and showed the best ability to predict correctly positive and negative lysosomotropic properties. The developed mechanistic AM model represents a useful in silico tool to predict lysosomal and cellular drug concentrations based on drug physicochemical data and system specific properties, with potential application to other cell types.

Intracellular drug bioavailability: a new predictor of system dependent drug disposition

Intracellular drug exposure is influenced by cell- and tissue-dependent expression of drug-transporting proteins and metabolizing enzymes. Here, we introduce the concept of intracellular bioavailability (F_ic) as the fraction of extracellular drug available to bind intracellular targets, and we assess how F_ic is affected by cellular drug disposition processes. We first investigated the impact of two essential drug transporters separately, one influx transporter (OATP1B1; SLCO1B1) and one efflux transporter (P-gp; ABCB1), in cells overexpressing these proteins. We showed that OATP1B1 increased F_ic of its substrates, while P-gp decreased F_ic. We then investigated the impact of the concerted action of multiple transporters and metabolizing enzymes in freshly-isolated human hepatocytes in culture configurations with different levels of expression and activity of these proteins. We observed that F_ic was up to 35-fold lower in the configuration with high expression of drug-eliminating transporters and enzymes. We conclude that F_ic provides a measurement of the net impact of all cellular drug disposition processes on intracellular bioavailable drug levels. Importantly, no prior knowledge of the involved drug distribution pathways is required, allowing for high-throughput determination of drug access to intracellular targets in highly defined cell systems (e.g., single-transporter transfectants) or in complex ones (including primary human cells).

Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport

Accurate prediction of drug target activity and rational dosing regimen design require knowledge of drug concentrations at the target. It is important to understand the impact of processes such as membrane permeability, partitioning, and active transport on intracellular drug concentrations. The present study aimed to predict intracellular unbound atorvastatin concentrations and characterize the effect of enzyme-transporter interplay on these concentrations. Single-pass liver perfusion studies were conducted in rats using atorvastatin (ATV, 1 µM) alone at 4°C and at 37°C in presence of rifampin (RIF, 20 µM) and 1-aminobenzotriazole (ABT, 1 mM), separately and in combination. The unbound intracellular ATV concentration was predicted with a five-compartment explicit membrane model using the parameterized diffusional influx clearance, active basolateral uptake clearance, and metabolic clearance. Chemical inhibition of uptake and metabolism at 37°C proved to be better controls relative to studies at 4°C. The predicted unbound intracellular concentration at the end of the 50-minute perfusion in the +ABT , +ABT+RIF, and the ATV-only groups was 6.5 µM, 0.58 µM, and 5.14 µM, respectively. The predicted total liver concentrations and amount recovered in bile were within 0.94-1.3 fold of the observed value in all groups. The fold difference in total liver concentration did not always extrapolate to the fold difference in predicted unbound concentration across groups. Together, these results support the use of compartmental modeling to predict intracellular concentrations in dynamic organ-based systems. These predictions can provide insight into the role of uptake transporters and metabolizing enzymes in determining drug tissue concentrations.

Assessing Natural Product-Drug Interactions: An End-to-End Safety Framework

The use of natural products (NPs), including herbal medicines and other dietary supplements, by North Americans continues to increase across all age groups. This population has access to conventional medications, with significant polypharmacy observed in older adults. Thus, the safety of the interactions between multi-ingredient NPs and drugs is a topic of paramount importance. Considerations such as history of safe use, literature data from animal toxicity and human clinical studies, and NP constituent characterization would provide guidance on whether to assess NP-drug interactions experimentally. The literature is replete with reports of various NP extracts and constituents as potent inhibitors of drug metabolizing enzymes, and transporters. However, without standard methods for NP characterization or in vitro testing, extrapolating these reports to clinically-relevant NP-drug interactions is difficult. This lack of a clear definition of risk precludes clinicians and consumers from making informed decisions about the safety of taking NPs with conventional medications. A framework is needed that describes an integrated robust approach for assessing NP-drug interactions; and, translation of the data into formulation alterations, dose adjustment, labelling, and/or post-marketing surveillance strategies. A session was held at the 41st Annual Summer Meeting of the Toxicology Forum in Colorado Springs, CO, to highlight the challenges and critical components that should be included in a framework approach.

A novel application of t-statistics to objectively assess the quality of IC50 fits for P-glycoprotein and other transporters

Current USFDA and EMA guidance for drug transporter interactions is dependent on IC₅₀ measurements as these are utilized in determining whether a clinical interaction study is warranted. It is therefore important not only to standardize transport inhibition assay systems but also to develop uniform statistical criteria with associated probability statements for generation of robust IC₅₀ values, which can be easily adopted across the industry. The current work provides a quantitative examination of critical factors affecting the quality of IC₅₀ fits for P-gp inhibition through simulations of perfect data with randomly added error as commonly observed in the large data set collected by the P-gp IC₅₀ initiative. The types of errors simulated were (1) variability in replicate measures of transport activity; (2) transformations of error-contaminated transport activity data prior to IC₅₀ fitting (such as performed when determining an IC₅₀ for inhibition of P-gp based on efflux ratio); and (3) the lack of well defined “no inhibition” and “complete inhibition” plateaus. The effect of the algorithm used in fitting the inhibition curve (e.g., two or three parameter fits) was also investigated. These simulations provide strong quantitative support for the recommendations provided in Bentz et al. (2013) for the determination of IC₅₀ values for P-gp and demonstrate the adverse effect of data transformation prior to fitting. Furthermore, the simulations validate uniform statistical criteria for robust IC₅₀ fits in general, which can be easily implemented across the industry. A calibration of the t-statistic is provided through calculation of confidence intervals associated with the t-statistic.

Rationalizing underprediction of drug clearance from enzyme and transporter kinetic data: from in vitro tools to mechanistic modeling

Over the years, there has been an increase in the number and quality of available in vitro tools for the assessment of clearance. Complexity of data analysis and modelling of corresponding in vitro data has increased in an analogous manner, in particular for the simultaneous characterization of transporter and metabolism kinetics, together with intracellular binding and passive diffusion. In the current chapter, the impact of different factors on the in vitro-in vivo extrapolation of clearance will be addressed in a stepwise manner, from the selection of the most adequate in vitro system and experimental design/condition to the corresponding modelling of data generated. The application of static or physiologically based pharmacokinetic models in the prediction of clearance will be discussed, highlighting limitations and current challenges of some of the approaches. Particular focus will be on the ability of in vitro and in silico predictive tools to overcome the trend of clearance underprediction. Improvements made as a result of inclusion of extrahepatic metabolism and consideration of transporter-metabolism interplay across different organs will be discussed.

Challenges of using in vitro data for modeling P-glycoprotein efflux in the blood-brain barrier

The efficacy of central nervous system (CNS) drugs may be limited by their poor ability to cross the bloodbrain barrier (BBB). Transporters, such as p-glycoprotein, may affect the distribution of many drugs into the CNS in conjunction with the restricted paracellular pathway of the BBB. It is therefore important to gain information on unbound drug concentrations in the brain in drug development to ensure sufficient drug exposure from plasma at the target site in the CNS. In vitro methods are routinely used in drug development to study passive permeability and p-glycoprotein efflux of new drugs. This review discusses the challenges in the use of in vitro data as input parameters in physiologically based pharmacokinetic (PBPK) models of CNS drug disposition of p-glycoprotein substrates. Experience with quinidine demonstrates the variability in in vitro parameters of passive permeability and active pglycoprotein efflux. Further work is needed to generate parameter values that are independent of the model and assay. This is a prerequisite for reliable predictions of drug concentrations in the brain in vivo.

In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life

The focus of CNS drug pharmacokinetics programs has recently shifted from determining the total concentrations in brain and blood to considering also unbound fractions and concentrations. Unfortunately, assessing unbound brain exposure experimentally requires demanding in vivo and in vitro studies. We propose a physical model, based on lipid binding and pH partitioning, to predict in silico the unbound volume of distribution in the brain. The model takes into account the partition of a drug into lipids, interstitial fluid and intracellular compartments of the brain. The results are in good agreement with the experimental data, suggesting that the contributions of lipid binding and pH partitioning are important in determining drug exposure in brain. The predicted values are used, together with predictions for plasma protein binding, as corrective terms in a second model to derive the unbound brain to plasma concentration ratio starting from experimental values of total concentration ratio. The calculated values of brain free fraction and passive permeability are also used to qualitatively determine the brain to plasma equilibration time in a model that shows promising results but is limited to a very small set of compounds. The models we propose are a step forward in understanding and predicting pharmacologically relevant exposure in brain starting from compounds' chemical structure and neuropharmacokinetics, by using experimental total brain to plasma ratios, in silico calculated properties and simple physics-based approaches. The models can be used in central nervous system drug discovery programs for a fast and cheap assessment of unbound brain exposure. For existing compounds, the unbound ratios can be derived from experimental values of total brain to plasma ratios. For both existing and hypothetical compounds, the unbound volume of distribution due to lipid binding and pH partitioning can be calculated starting only from the chemical structure.

Domperidone interacts with pioglitazone but not with ondansetron via common CYP metabolism in vitro

Domperidone (prokinetic agent) is frequently co-administered with pioglitazone (anitidiabetic) or ondansetron (antiemetic) in gastroparesis management. These drugs are metabolized via cytochome P-450 (CYP) 3A4, raising the possibility of interaction and adverse reactions. The concentration-dependent inhibitory effect of pioglitazone and ondansetron on domperidone hydroxylation was monitored in pooled human liver microsomes (HLM). Pioglitazone was further assessed as a mechanism-based inhibitor. Microsomal binding was evaluated in our assessment. In HLM, Vmax/Km estimates for monohydroxy domperidone formation decreased in presence of pioglitazone. Diagnostic plots indicated that pioglitazone inhibited domperidone in a partial mixed-type manner. The in vitro Ki was 1.52 µM. Predicted in vivo AUCi/AUC ratio was 1.98. Pioglitazone also exerted time-dependent inhibition on the metabolism of domperidone and the average remaining enzymatic activity decreased significantly upon preincubation with pioglitazone over 0-40 min. Diagnostic plots showed no inhibitory effect of ondansetron on domperidone hydroxylation. 6. In conclusion, pioglitazone inhibited domperidone metabolism in vitro through different complex mechanisms. Our in vitro data predict that the co-administration of these drugs can potentially trigger an in vivo drug-drug interaction.

Generating an in vitro-in vivo correlation for metabolism and liver enrichment of a hepatitis C virus drug, faldaprevir, using a rat hepatocyte model (HepatoPac)

Hepatocytes provide an integrated model to study drug metabolism and disposition. As a result of a loss of polarity or a significant decrease in the expression of enzymes and transporters, suspended and sandwich-cultured hepatocytes have limitations in determining hepatocellular drug concentrations. Underprediction of the extent of glucuronidation is also a concern for these hepatocyte models. Faldaprevir is a hepatitis C virus protease inhibitor in late-stage development that has demonstrated significant liver enrichment in in vivo rat models based on quantitative whole-body autoradiography (QWBA) and liver-to-plasma area under-the-curve ratio. In bile duct cannulated rats, the primary biliary metabolite was a glucuronide. Owing to ethical concerns, it is difficult to assess liver enrichment in humans, and a lack of in vitro and in vivo correlation of glucuronidation has been reported. The current study was conducted to verify whether a hepatocyte model, rat HepatoPac, could overcome some of these limitations and provide validity for follow-up studies with human HepatoPac. With rat HepatoPac, liver enrichment values averaged 34-fold and were consistent with rat QWBA (26.8-fold) and in vivo data (42-fold). In contrast, liver enrichment in suspended hepatocytes was only 2.8-fold. Furthermore, the extent of faldaprevir glucuronidation in HepatoPac studies was in agreement with in vivo results, with glucuronidation as the major pathway (96%). Suspended rat hepatocytes did not generate the glucuronide or two key hydroxylated metabolites that were observed in vivo. Overall, our studies suggest that HepatoPac is a promising in vitro model to predict in vivo liver enrichment and metabolism, especially for glucuronidation, and has demonstrated superiority over suspended hepatocytes.

Compartmental models for apical efflux by P-glycoprotein: part 2--a theoretical study on transporter kinetic parameters

PURPOSE

The impact of efflux transporters in intracellular concentrations of a drug can be predicted with modeling techniques. In Part 1, several compartmental models were developed and evaluated. The goal of Part 2 was to apply these models to the characterization and interpretation of saturation kinetic data.

METHODS

The compartmental models from Part 1 were used to evaluate a previously published dataset from cell lines expressing varying levels of P-glycoprotein. Kinetic parameters for the transporter were estimated and compared across models.

RESULTS

Fits and errors for all compartmental models were identical. All compartmental models predicted more consistent parameters than the Michaelis-Menten model. The 5-compartment model with efflux out of the membrane predicted differential impact of P-gp upon apical versus basolateral drug exposure. Finally, the saturable kinetics of active efflux along with a permeability barrier was modeled to delineate a relationship between intracellular concentration with or without active efflux versus donor concentration. This relationship was not a rectangular hyperbola, but instead was shown to be a quadratic function.

CONCLUSIONS

One approach to estimate an in vivo transporter effect is to first model an intracellular Km value from in vitro data, and use this value along with the appropriate tissue transporter expression levels and relative surface area to calculate the relevant apparent Km (or Ki) values. Together with the results from Part 1, these studies suggest that compartmental models can provide a path forward to better utilize in vitro transporter data for in vivo predictions such as physiologically based pharmacokinetic modeling.

Compartmental models for apical efflux by P-glycoprotein--part 1: evaluation of model complexity

PURPOSE

With the goal of quantifying P-gp transport kinetics, Part 1 of these manuscripts evaluates different compartmental models and Part 2 applies these models to kinetic data.

METHODS

Models were developed to simulate the effect of apical efflux transporters on intracellular concentrations of six drugs. The effect of experimental variability on model predictions was evaluated. Several models were evaluated, and characteristics including membrane configuration, lipid content, and apical surface area (asa) were varied.

RESULTS

Passive permeabilities from MDCK-MDR1 cells in the presence of cyclosporine gave lower model errors than from MDCK control cells. Consistent with the results in Part 2, model configuration had little impact on calculated model errors. The 5-compartment model was the simplest model that reproduced experimental lag times. Lipid content and asa had minimal effect on model errors, predicted lag times, and intracellular concentrations. Including endogenous basolateral uptake activity can decrease model errors. Models with and without explicit membrane barriers differed markedly in their predicted intracellular concentrations for basolateral drug exposure. Single point data resulted in clearances similar to time course data.

CONCLUSIONS

Compartmental models are useful to evaluate the impact of efflux transporters on intracellular concentrations. Whereas a 3-compartment model may be sufficient to predict the impact of transporters that efflux drugs from the cell, a 5-compartment model with explicit membranes may be required to predict intracellular concentrations when efflux occurs from the membrane. More complex models including additional compartments may be unnecessary.

Consideration of the unbound drug concentration in enzyme kinetics

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system under investigation. As a consequence, the apparent kinetic parameters that are derived, such as K m or K i, can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus, as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components that can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

A structural model for the mass action kinetic analysis of P-gp mediated transport through confluent cell monolayers

The structural model for P-gp mediated transport across confluent cell monolayers uses the generally accepted mass action reactions for P-gp binding and efflux, together with the known structural parameters for P-gp (large substrate binding site accessible from the membrane) and the apical plasma membrane in which it resides (lipid bilayer partition coefficient of substrate and volume of apical plasma membrane allow estimation of substrate concentration at binding site). The model considers binding of substrate to P-gp from within the inner leaflet of the apical membrane, with an on rate constant, k 1 (M(-1)s(-1)), and off rate constant k r (s(-1)), as well as an efflux rate constant from P-gp into the apical chamber, k 2 (s(-1)). The model also explicitly estimates the active P-gp protein level, known as P-gp efflux active surface density T(0). For each new drug, fitting these parameters requires use of multiple initial drug concentrations and multiple time points at each concentration, until steady state is reached between P-gp-mediated efflux into the apical chamber and passive permeability from apical chamber back into the cytosol. Although this model optimally requires a larger than usual dataset for analysis, it does provide important mechanistic information through estimates of these on, off and efflux rate constants, as well as efflux active P-gp surface density. This more detailed description of efflux from polarized confluent cell monolayers has (1) provided insight into the unexpected relationship between P-gp IC50 and K i in this system, (2) highlighted the kinetic need for GF120918 inhibitable apical and basolateral uptake transporters for digoxin, and (3) provided possible explanations for the extreme lab-to-lab variability in P-gp IC50 values observed for inhibition of digoxin transport. This model can also be used to distinguish between efflux active P-gp and total apical plasma membrane P-gp, which may be important when P-gp is expressed in a microvillous membrane.

Role of hepatic efflux transporters in regulating systemic and hepatocyte exposure to xenobiotics

Hepatic efflux transporters include numerous well-known and emerging proteins localized to the canalicular or basolateral membrane of the hepatocyte that are responsible for the excretion of drugs into the bile or blood, respectively. Altered function of hepatic efflux transporters due to drug-drug interactions, genetic variation, and/or disease states may lead to changes in xenobiotic exposure in the hepatocyte and/or systemic circulation. This review focuses on transport proteins involved in the hepatocellular efflux of drugs and metabolites, discusses mechanisms of altered transporter function as well as the interplay between multiple transport pathways, and highlights the importance of considering intracellular unbound concentrations of transporter substrates and/or inhibitors. Methods to evaluate hepatic efflux transport and predict the effects of impaired transporter function on systemic and hepatocyte exposure are discussed, and the sandwich-cultured hepatocyte model to evaluate comprehensively the role of hepatic efflux in the hepatobiliary disposition of xenobiotics is characterized.

Pitavastatin as an in vivo probe for studying hepatic organic anion transporting polypeptide-mediated drug-drug interactions in cynomolgus monkeys

Drug-drug interactions (DDIs) caused by the inhibition of hepatic uptake transporters such as organic anion transporting polypeptide (OATP) can affect therapeutic efficacy and cause adverse reactions. We investigated the potential utility of pitavastatin as an in vivo probe substrate for preclinically studying OATP-mediated DDIs using cynomolgus monkeys. Cyclosporine A (CsA) and rifampicin (RIF), typical OATP inhibitors, inhibited active uptake of pitavastatin into monkey hepatocytes with half-maximal inhibitory concentration values comparable with those in human hepatocytes. CsA and RIF increased the area under the plasma concentration-time curve (AUC) of intravenously administered pitavastatin in cynomolgus monkeys by 3.2- and 3.6-fold, respectively. In addition, there was no apparent prolongation of the elimination half-life of pitavastatin due to the decrease in both hepatic clearance and volume of distribution. These findings suggest that DDIs were caused by the inhibition of hepatic uptake of pitavastatin. CsA and RIF increased the AUC of orally administered pitavastatin by 10.6- and 14.8-fold, respectively, which was additionally caused by the effect of the CsA and RIF in the gastrointestinal tract. Hepatic contribution to the overall DDI for oral pitavastatin with CsA was calculated from the changes in hepatic availability and clearance, and it was shown that the magnitude of hepatic DDI was comparable between the present study and the clinical study. In conclusion, pharmacokinetic studies using pitavastatin as a probe in combination with drug candidates in cynomolgus monkeys are useful to support the assessment of potential clinical DDIs involving hepatic uptake transporters.

PBPK models for the prediction of in vivo performance of oral dosage forms

Drug absorption from the gastrointestinal (GI) tract is a highly complex process dependent upon numerous factors including the physicochemical properties of the drug, characteristics of the formulation and interplay with the underlying physiological properties of the GI tract. The ability to accurately predict oral drug absorption during drug product development is becoming more relevant given the current challenges facing the pharmaceutical industry. Physiologically-based pharmacokinetic (PBPK) modeling provides an approach that enables the plasma concentration-time profiles to be predicted from preclinical in vitro and in vivo data and can thus provide a valuable resource to support decisions at various stages of the drug development process. Whilst there have been quite a few successes with PBPK models identifying key issues in the development of new drugs in vivo, there are still many aspects that need to be addressed in order to maximize the utility of the PBPK models to predict drug absorption, including improving our understanding of conditions in the lower small intestine and colon, taking the influence of disease on GI physiology into account and further exploring the reasons behind population variability. Importantly, there is also a need to create more appropriate in vitro models for testing dosage form performance and to streamline data input from these into the PBPK models. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the current status of PBPK models available. The current challenges in PBPK set-ups for oral drug absorption including the composition of GI luminal contents, transit and hydrodynamics, permeability and intestinal wall metabolism are discussed in detail. Further, the challenges regarding the appropriate integration of results from in vitro models, such as consideration of appropriate integration/estimation of solubility and the complexity of the in vitro release and precipitation data, are also highlighted as important steps to advancing the application of PBPK models in drug development. It is expected that the "innovative" integration of in vitro data from more appropriate in vitro models and the enhancement of the GI physiology component of PBPK models, arising from the OrBiTo project, will lead to a significant enhancement in the ability of PBPK models to successfully predict oral drug absorption and advance their role in preclinical and clinical development, as well as for regulatory applications.

Quantitative prediction of repaglinide-rifampicin complex drug interactions using dynamic and static mechanistic models: delineating differential CYP3A4 induction and OATP1B1 inhibition potential of rifampicin

Repaglinide is mainly metabolized by cytochrome P450 enzymes CYP2C8 and CYP3A4, and it is also a substrate to a hepatic uptake transporter, organic anion transporting polypeptide (OATP)1B1. The purpose of this study is to predict the dosing time-dependent pharmacokinetic interactions of repaglinide with rifampicin, using mechanistic models. In vitro hepatic transport of repaglinide, characterized using sandwich-cultured human hepatocytes, and intrinsic metabolic parameters were used to build a dynamic whole-body physiologically-based pharmacokinetic (PBPK) model. The PBPK model adequately described repaglinide plasma concentration-time profiles and successfully predicted area under the plasma concentration-time curve ratios of repaglinide (within ± 25% error), dosed (staggered 0-24 hours) after rifampicin treatment when primarily considering induction of CYP3A4 and reversible inhibition of OATP1B1 by rifampicin. Further, a static mechanistic "extended net-effect" model incorporating transport and metabolic disposition parameters of repaglinide and interaction potency of rifampicin was devised. Predictions based on the static model are similar to those observed in the clinic (average error ∼19%) and to those based on the PBPK model. Both the models suggested that the combined effect of increased gut extraction and decreased hepatic uptake caused minimal repaglinide systemic exposure change when repaglinide is dosed simultaneously or 1 hour after the rifampicin dose. On the other hand, isolated induction effect as a result of temporal separation of the two drugs translated to an approximate 5-fold reduction in repaglinide systemic exposure. In conclusion, both dynamic and static mechanistic models are instrumental in delineating the quantitative contribution of transport and metabolism in the dosing time-dependent repaglinide-rifampicin interactions.

Intracellular drug concentrations and transporters: measurement, modeling, and implications for the liver

Intracellular concentrations of drugs and metabolites are often important determinants of efficacy, toxicity, and drug interactions. Hepatic drug distribution can be affected by many factors, including physicochemical properties, uptake/efflux transporters, protein binding, organelle sequestration, and metabolism. This white paper highlights determinants of hepatocyte drug/metabolite concentrations and provides an update on model systems, methods, and modeling/simulation approaches used to quantitatively assess hepatocellular concentrations of molecules. The critical scientific gaps and future research directions in this field are discussed.

ITC recommendations for transporter kinetic parameter estimation and translational modeling of transport-mediated PK and DDIs in humans

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter-knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter-mediated pharmacokinetics and drug-drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science.

Commentary: nonspecific protein binding versus membrane partitioning: it is not just semantics

Nonspecific binding or sequestration results in differences between free and total drug concentrations, both in vitro and in vivo. Membrane partitioning and not protein binding is the primary mechanism of drug sequestration. Therefore, physicochemical properties, e.g., LogP can be used to predict drug sequestration in membrane and cell-based assays. The concentration of drug in a membrane is determined by the both the rate in and out of the membrane. In contrast, membrane permeability is a function of the rate in only. This commentary discusses the origins of membrane partitioning and permeability and their impact on cellular disposition.