The Application of Physiologically Based Pharmacokinetic Modeling to Predict the Role of Drug Transporters: Scientific and Regulatory Perspectives

No dose adjustment of metformin or substrates of organic cation transporters (OCT)1 and OCT2 and multidrug and toxin extrusion protein (MATE)1/2K with fostemsavir coadministration based on modeling approaches

Fostemsavir is an approved gp120-directed attachment inhibitor and prodrug for the treatment of human immunodeficiency virus type 1 infection in combination with other antiretrovirals (ARVs) in heavily treatment-experienced adults with multi-drug resistance, intolerance, or safety concerns with their current ARV regimen. Initial in vitro studies indicated that temsavir, the active moiety of fostemsavir, and its metabolites, inhibited organic cation transporter (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs) at tested concentration of 100 uM, although risk assessment based on the current Food and Drug Administration in vitro drug-drug interaction (DDI) guidance using the mechanistic static model did not reveal any clinically relevant inhibition on OCTs and MATEs. However, a DDI risk was flagged with EMA static model predictions. Hence, a physiologically based pharmacokinetic (PBPK) model of fostemsavir/temsavir was developed to further assess the DDI risk potential of OCT and MATEs inhibition by temsavir and predict changes in metformin (a sensitive OCT and MATEs substrate) exposure. No clinically relevant impact on metformin concentrations across a wide range of temsavir concentrations was predicted; therefore, no dose adjustment is recommended for metformin when co-administered with fostemsavir.

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.

Evaluation of the drug-drug interaction potential of brigatinib using a physiologically-based pharmacokinetic modeling approach

Brigatinib is an oral anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive metastatic non-small cell lung cancer. In vitro studies indicated that brigatinib is primarily metabolized by CYP2C8 and CYP3A4 and inhibits P-gp, BCRP, OCT1, MATE1, and MATE2K. Clinical drug-drug interaction (DDI) studies with the strong CYP3A inhibitor itraconazole or the strong CYP3A inducer rifampin demonstrated that CYP3A-mediated metabolism was the primary contributor to overall brigatinib clearance in humans. A physiologically-based pharmacokinetic (PBPK) model for brigatinib was developed to predict potential DDIs, including the effect of moderate CYP3A inhibitors or inducers on brigatinib pharmacokinetics (PK) and the effect of brigatinib on the PK of transporter substrates. The developed model was able to predict clinical DDIs with itraconazole (area under the plasma concentration-time curve from time 0 to infinity [AUC∞] ratio [with/without itraconazole]: predicted 1.86; observed 2.01) and rifampin (AUC∞ ratio [with/without rifampin]: predicted 0.16; observed 0.20). Simulations using the developed model predicted that moderate CYP3A inhibitors (e.g., verapamil and diltiazem) may increase brigatinib AUC∞ by ~40%, whereas moderate CYP3A inducers (e.g., efavirenz) may decrease brigatinib AUC∞ by ~50%. Simulations of potential transporter-mediated DDIs predicted that brigatinib may increase systemic exposures (AUC∞) of P-gp substrates (e.g., digoxin and dabigatran) by 15%-43% and MATE1 substrates (e.g., metformin) by up to 29%; however, negligible effects were predicted on BCRP-mediated efflux and OCT1-mediated uptake. The PBPK analysis results informed dosing recommendations for patients receiving moderate CYP3A inhibitors (40% brigatinib dose reduction) or inducers (up to 100% increase in brigatinib dose) during treatment, as reflected in the brigatinib prescribing information.

Incubation Time Influences Organic Anion Transporter 1 Kinetics and Renal Clearance Predictions

Accurate predictions of drug uptake transporter involvement in renal excretion of xenobiotics require determination of in vitro transport kinetic parameters under initial-rate conditions. The purpose of the present study was to determine how changing the incubation time from initial rate to steady state influences ligand interactions with the renal organic anion transporter 1 (OAT1), and the impact of the different experimental conditions on pharmacokinetic predictions. Transport studies were performed with Chinese hamster ovary cells expressing OAT1 (CHO-OAT1) and the Simcyp Simulator was used for physiological-based pharmacokinetic predictions. Maximal transport rate and intrinsic uptake clearance (CL_int) for PAH decreased with increasing incubation time. The CL_int values ranged 11-fold with incubation times spanning from 15 s (CL_int,15s, initial rate) to 45 min (CL_int,45min, steady state). The Michaelis constant (K_m) was also influenced by the incubation time with an apparent increase in the Km value at longer incubation times. Inhibition potency of five drugs against PAH transport was tested using incubation times of either 15 s or 10 min. There was no effect of time on inhibition potency for omeprazole or furosemide, whereas indomethacin was less potent, and probenecid (~2-fold) and telmisartan (~7-fold) more potent with the longer incubation time. Notably, the inhibitory effect of telmisartan was reversible, albeit slowly. A pharmacokinetic model was developed for PAH using the CL_int,15s value. The simulated plasma concentration-time profile, renal clearance, and cumulative urinary excretion-time profile of PAH agreed well with reported clinical data, and the PK parameters were sensitive to the time-associated CL_int value used in the model.

Novel method for kinetic analysis applied to transport by the uniporter OCT2

The kinetics of solute transport shed light on the roles these processes play in cellular physiology, and the absolute values of the kinetic parameters that quantitatively describe transport are increasingly used to model its impact on drug clearance. However, accurate assessment of transport kinetics is challenging. Although most carrier-mediated transport is adequately described by the Michaelis-Menten equation, its use presupposes that the rates of uptake used in the analysis of maximal rates of transport (Jmax) and half-saturation constants (Kt) reflect true unidirectional rates of influx from known concentrations of substrate. Most experimental protocols estimate the initial rate of transport from net substrate accumulation determined at a single time point (typically between 0.5 and 5 min) and assume it reflects unidirectional influx. However, this approach generally results in systematic underestimates of Jmax and overestimates of Kt; the former primarily due to the unaccounted impact of efflux of accumulated substrate, and the latter due to the influence of unstirred water layers. Here, we describe the bases of these time-dependent effects and introduce a computational model that analyzes the time course of net substrate uptake at several concentrations to calculate Jmax and Kt for unidirectional influx, taking into account the influence of unstirred water layers and mediated efflux. This method was then applied to calculate the kinetics of transport of 1-methyl-4-phenylpryridinium and metformin by renal organic cation transporter 2 as expressed in cultured Chinese hamster ovary cells.NEW & NOTEWORTHY Here, we describe a mathematical model that uses the time course of net substrate uptake into cells from several increasing concentrations to calculate unique kinetic parameters [maximal rates of transport (Jmax) and half-saturation constants (Kt)] of the process. The method is the first to take into consideration the common complicating factors of unstirred layers and carrier-mediated efflux in the experimental determination of transport kinetics.

Trends in FDA Transporter-Based Post Marketing Requirements and Commitments Over the Last Decade

Characterizing interactions between new molecular entities (NMEs) and drug transporters is a critical element of drug development that helps in assessing potential transporter-based drug-drug interactions (DDIs). However, not all NME new drug applications (NDAs) include a full characterization of NMEs transporter-based DDI, which necessitates the issuance of post marketing requirement (PMR)/post marketing commitment (PMC) by the US Food and Drug Administration (FDA) to characterize these potential interactions. The objective of this analysis is to identify trends in transporter-based PMRs/PMCs issued by the FDA between 2012 and 2021. A decrease in the number of transporter-based PMRs/PMCs was observed from 2012 to 2016 and an increasing trend in the number of PMRs/PMCs was observed after 2017. The majority of these transporter-based PMRs/PMCs requested clinical evaluation (48%), some requested in vitro assessment (38%), and 2.5% requested modeling and simulation assessment. Most of the PMRs/PMCs requested evaluation of NMEs as perpetrator with the efflux transporters, P-gp and/or BCRP (53%). Forty-eight percent of the PMRs/PMCs were fulfilled with 67% resulted in labelling updates. On average 2.5 years were needed for the information related to PMRs/PMCs to show in NMEs labeling. In conclusion, this analysis highlights the increased emphasis from the FDA on proper characterization of transporter-based DDI and call for the need of early characterization of NMEs-transporters interaction before initial NDA approval.

Pharmacoproteomics of Brain Barrier Transporters and Substrate Design for the Brain Targeted Drug Delivery

One of the major reasons why central nervous system (CNS)-drug development has been challenging in the past, is the barriers that prevent substances entering from the blood circulation into the brain. These barriers include the blood-brain barrier (BBB), blood-spinal cord barrier (BSCB), blood-cerebrospinal fluid barrier (BCSFB), and blood-arachnoid barrier (BAB), and they differ from each other in their transporter protein expression and function as well as among the species. The quantitative expression profiles of the transporters in the CNS-barriers have been recently revealed, and in this review, it is described how they affect the pharmacokinetics of compounds and how these expression differences can be taken into account in the prediction of brain drug disposition in humans, an approach called pharmacoproteomics. In recent years, also structural biology and computational resources have progressed remarkably, enabling a detailed understanding of the dynamic processes of transporters. Molecular dynamics simulations (MDS) are currently used commonly to reveal the conformational changes of the transporters and to find the interactions between the substrates and the protein during the binding, translocation in the transporter cavity, and release of the substrate on the other side of the membrane. The computational advancements have also aided in the rational design of transporter-utilizing compounds, including prodrugs that can be actively transported without losing potency towards the pharmacological target. In this review, the state-of-art of these approaches will be also discussed to give insights into the transporter-mediated drug delivery to the CNS.

Recent Advances in Drug Transporter Sciences: Highlights From the Year 2020

Drug Metabolism Reviews has an impressive track record of providing scientific reviews in the area of xenobiotic biotransformation over 47 years. It has consistently proved to be resourceful to many scientists from pharmaceutical industry, academia, regulatory agencies working in diverse areas including enzymology, pharmacology, pharmacokinetics and toxicology. Over the last 5 years Drug metabolism Reviews has annually published an industry commentary aimed to highlight novel insights and approaches that have made significant impacts on the field of biotransformation (led by Cyrus Khojasteh). We hope to continue this tradition by providing an overview of advances made in the field of drug transporters during 2020. The field of drug transporters is rapidly evolving as they play an essential role in drug absorption, distribution, clearance and elimination. In this review we have selected outstanding drug transporter articles that have significantly contributed to moving forward the field of transporter science with respect to translation and improved understanding of diverse aspects including uptake clearance, clinical biomarkers, induction, proteomics, emerging transporters and tissue targeting.The theme of this review consists of synopsis that summarizes each article followed by our commentary. The objective of this work is not to provide a comprehensive review but rather exemplify novel insights and state-of-the-art highlights of recent research that have advanced our understanding of drug transporters in drug disposition. We are hopeful that this effort will prove useful to the scientific community and as such request feedback, and further extend an invitation to anyone interested in contributing to future reviews.

Hepatic transporter-mediated pharmacokinetic drug-drug interactions: Recent studies and regulatory recommendations

Transporter-mediated drug-drug interactions are one of the major mechanisms in pharmacokinetic-based drug interactions and correspondingly affecting drugs' safety and efficacy. Regulatory bodies underlined the importance of the evaluation of transporter-mediated interactions as a part of the drug development process. The liver is responsible for the elimination of a wide range of endogenous and exogenous compounds via metabolism and biliary excretion. Therefore, hepatic uptake transporters, expressed on the sinusoidal membranes of hepatocytes, and efflux transporters mediating the transport from hepatocytes to the bile are determinant factors for pharmacokinetics of drugs, and hence, drug-drug interactions. In parallel with the growing research interest in this area, regulatory guidances have been updated with detailed assay models and criteria. According to well-established preclinical results, observed or expected hepatic transporter-mediated drug-drug interactions can be taken into account for clinical studies. In this paper, various methods including in vitro, in situ, in vivo, in silico approaches, and combinational concepts and several clinical studies on the assessment of transporter-mediated drug-drug interactions were reviewed. Informative and effective evaluation by preclinical tools together with the integration of pharmacokinetic modeling and simulation can reduce unexpected clinical outcomes and enhance the success rate in drug development.

Evaluation of Pharmacokinetic Drug-Drug Interactions: A Review of the Mechanisms, In Vitro and In Silico Approaches

Pharmacokinetic drug–drug interactions (DDIs) occur when a drug alters the absorption, transport, distribution, metabolism or excretion of a co-administered agent. The occurrence of pharmacokinetic DDIs may result in the increase or the decrease of drug concentrations, which can significantly affect the drug efficacy and safety in patients. Enzyme-mediated DDIs are of primary concern, while the transporter-mediated DDIs are less understood but also important. In this review, we presented an overview of the different mechanisms leading to DDIs, the in vitro experimental tools for capturing the factors affecting DDIs, and in silico methods for quantitative predictions of DDIs. We also emphasized the power and strategy of physiologically based pharmacokinetic (PBPK) models for the assessment of DDIs, which can integrate relevant in vitro data to simulate potential drug interaction in vivo. Lastly, we pointed out the future directions and challenges for the evaluation of pharmacokinetic DDIs.

Assessing OATP1B1- and OATP1B3-Mediated Drug-Drug Interaction Potential of Vemurafenib Using R-Value and Physiologically-Based Pharmacokinetic Models

Organic anion transporting polypeptides (OATP) 1B1 and OATP1B3 are important determinants of transporter-mediated drug-drug interactions (DDIs). Current studies assessed the OATP1B1 and OATP1B3-mediated DDI potential of vemurafenib, a kinase inhibitor drug with high protein binding and low aqueous solubility, using R-value and physiologically-based pharmacokinetic (PBPK) models. The total half-maximal inhibitory concentration (IC50,total) values of vemurafenib against OATP1B1 and OATP1B3 were determined in 100% human plasma in transporter-overexpressing human embryonic kidney 293 stable cell lines. The unbound fraction of vemurafenib in human plasma before (fu,plasma) and after addition into the uptake assay plate (fu,plasma,inc) were determined by rapid equilibrium dialysis. There was no statistically significant difference between fu,plasma and fu,plasma,inc. Vemurafenib IC50,total values against OATP1B1 and OATP1B3 are 175 ± 82 and 231 ± 26 μM, respectively. The R-values [R = 1 + fu,plasma × Iin,max/(fu,plasma,inc × IC50,total)] were then simplified as R = 1+Iin,max/IC50,total, and were 1.76 and 1.57 for OATP1B1 and OATP1B3, respectively. The simulated pravastatin AUC ratio was 1.28 when a single dose of pravastatin (40 mg) was co-administered with vemurafenib (960 mg, twice daily) at steady-state, compared to pravastatin alone. Both R-value and PBPK models predict that vemurafenib has the potential to cause OATP1B1- and OATP1B3-mediated DDIs.

The dual orexin receptor antagonist daridorexant does not affect the pharmacokinetics of the BCRP substrate rosuvastatin

Daridorexant is a dual orexin receptor antagonist in clinical development for the treatment of insomnia. Breast-cancer resistant protein (BCRP) is an efflux pump expressed in intestinal epithelium and hepatocytes, contributing to the absorption, distribution, and elimination of drugs and endogenous compounds. In vitro, daridorexant inhibits BCRP with an IC50 of 3.0 μmol/L. The BCRP substrate rosuvastatin is a cholesterol-lowering drug, recommended for clinical drug-drug interaction (DDI) studies. In order to exclude an inhibitory effect of daridorexant on BCRP, this single-centre, open-label, two-treatment Phase 1 study investigated the effect of daridorexant at steady state on the pharmacokinetics (PK) of single-dose rosuvastatin in 20 healthy male subjects. In addition, safety and tolerability were assessed. A single oral dose of 10 mg rosuvastatin on Day 1 was followed by 96 hours observation. Thereafter, 25 mg daridorexant was administered once daily (o.d.) on Days 5-8 and in combination with 10 mg rosuvastatin on Day 8. On Days 9-12, subjects received 25 mg daridorexant alone. PK sampling was performed up to 120 hours after treatment administration. The results showed that concomitant administration of 25 mg daridorexant o.d. at steady state did not affect the exposure parameters of rosuvastatin in a relevant way, as indicated by the ratios of geometric means (GMRs) ([rosuvastatin + daridorexant]/[rosuvastatin alone]) of 0.93 for both Cmax and AUC0-∞ . Administration of a single dose of 10 mg rosuvastatin, multiple doses of 25 mg daridorexant alone or in combination were well tolerated. Taken together, daridorexant and BCRP substrates can be safely co-administered.

Effect of P-glycoprotein (P-gp) Inducers on Exposure of P-gp Substrates: Review of Clinical Drug-Drug Interaction Studies

Understanding transporter-mediated drug-drug interactions (DDIs) for investigational agents is important during drug development to assess DDI liability, its clinical relevance, and to determine appropriate DDI management strategies. P-glycoprotein (P-gp) is an efflux transporter that influences the pharmacokinetics (PK) of various compounds. Assessing transporter induction in vitro is challenging and is not always predictive of in vivo effects, and hence there is a need to consider clinical DDI studies; however, there is no clear guidance on when clinical evaluation of transporter induction is required. Furthermore, there is no proposed list of index transporter inducers to be used in clinical studies. This review evaluated DDI studies with known P-gp inducers to better understand the mechanism and site of P-gp induction, as well as the magnitude of induction effect on the exposure of P-gp substrates. Our review indicates that P-gp and cytochrome P450 (CYP450) enzymes are co-regulated via the pregnane xenobiotic receptor (PXR) and the constitutive androstane receptor (CAR). The magnitude of the decrease in substrate drug exposure by P-gp induction is generally less than that of CYP3A. Most P-gp inducers reduced total bioavailability with a minor impact on renal clearance, despite known expression of P-gp at the apical membrane of the kidney proximal tubules. Rifampin is the most potent P-gp inducer, resulting in an average reduction in substrate exposure ranging between 20 and 67%. For other inducers, the reduction in P-gp substrate exposure ranged from 12 to 42%. A lower reduction in exposure of the P-gp substrate was observed with a lower dose of the inducer and/or if the administration of the inducer and substrate was simultaneous, i.e. not staggered. These findings suggest that clinical evaluation of the impact of P-gp inducers on the PK of investigational agents that are substrates for P-gp might be warranted only for compounds with a relatively steep exposure-efficacy relationship.

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.

Molecular and cellular physiology of organic cation transporter 2

Organic cation transporters play a critical role in mediating the distribution of cationic pharmaceuticals. Indeed, organic cation transporter (OCT)2 is the initial step in the renal secretion of organic cations and consequently plays a defining role in establishing the pharmacokinetics of many cationic drugs. Although a hallmark of OCTs is their broad selectivity, this characteristic also makes them targets for unwanted, adverse drug-drug interactions (DDIs), making them a focus for efforts to develop models of ligand interaction that could predict and preempt these adverse interactions. This review discusses the molecular characteristics of these transporters as well as the evidence that established the OCTs as key players in the distribution of organic cations. However, the primary focus is the present understanding of the complexity of ligand interaction with OCTs, particularly OCT2, including evidence for the presence of multiple ligand-binding sites and the influence of substrate structure on the affinity of the transporter for inhibitory ligands. This leads to a discussion of the complexities associated with the development of protocols for assessing the inhibitory potential of new molecular entities to perpetrate unwanted DDIs, the criteria that should be considered in the interpretation of the results of such protocols, and the challenges associated with development of models capable of predicting unwanted DDIs.

Current trends in drug metabolism and pharmacokinetics

Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication. In this review we provided an overview of recent research on PK with focus on the following aspects: (1) an update on drug-metabolizing enzymes and transporters in the determination of PK, as well as advances in xenobiotic receptors and noncoding RNAs (ncRNAs) in the modulation of PK, providing new understanding of the transcriptional and posttranscriptional regulatory mechanisms that result in inter-individual variations in pharmacotherapy; (2) current status and trends in assessing drug-drug interactions, especially interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated interactions; (3) advances in understanding the effects of diseases on PK, particularly changes in metabolizing enzymes and transporters with disease progression; (4) trends in mathematical modeling including physiologically-based PK modeling and novel animal models such as CRISPR/Cas9-based animal models for DMPK studies; (5) emerging non-classical xenobiotic metabolic pathways and the involvement of novel metabolic enzymes, especially non-P450s. Existing challenges and perspectives on future directions are discussed, and may stimulate the development of new research models, technologies, and strategies towards the development of better drugs and improved clinical practice.

Modeling Gadoxetate Liver Uptake and Efflux Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Enables Preclinical Quantification of Transporter Drug-Drug Interactions

OBJECTIVES

The aim of this study was to model the in vivo transporter-mediated uptake and efflux of the hepatobiliary contrast agent gadoxetate in the liver. The efficacy of the proposed technique was assessed for its ability to provide quantitative insights into drug-drug interactions (DDIs), using rifampicin as inhibitor.

MATERIALS AND METHODS

Three groups of C57 mice were scanned twice with a dynamic gadoxetate-enhanced magnetic resonance imaging protocol, using a 3-dimensional spoiled gradient-echo sequence for approximately 72 minutes. Before the second magnetic resonance imaging session, 2 of the groups received a rifampicin dose of 20 (n = 7) or 40 (n = 7) mg/kg, respectively. Data from regions of interest in the liver were analyzed using 2 simplifications of a 2-compartment uptake and efflux model to provide estimates for the gadoxetate uptake rate (ki) into the hepatocytes and its efflux rate (kef) into the bile. Both models were assessed for goodness-of-fit in the group without rifampicin (n = 9), and the appropriate model was selected for assessing the ability to monitor DDIs in vivo.

RESULTS

Seven of 9 mice from the group without rifampicin were assessed for model implementation and reproducibility. A simple 3 parameter model (ki, kef, and extracellular space, vecs) adequately described the observed liver concentration time series with mean ki = 0.47 ± 0.11 min and mean kef = 0.039 ± 0.016 min. Visually, the area under the liver concentration time profile was reduced for the groups receiving rifampicin. Furthermore, tracer kinetic modeling demonstrated a significant dose-dependent decrease in the uptake (5.9- and 17.3-fold decrease for 20 mg/kg and 40 mg/kg, respectively) and efflux rates (2.2- and 7.9-fold decrease) compared with the first scan for each group.

CONCLUSIONS

This study presents the first in vivo implementation of a 2-compartment uptake and efflux model to monitor DDIs at the transporter-protein level, using the clinically relevant organic anion transporting polypeptide inhibitor rifampicin. The technique has the potential to be a novel alternative to other methods, allowing real-time changes in transporter DDIs to be measured directly in vivo.

Membrane transporter data to support kinetically-informed chemical risk assessment using non-animal methods: Scientific and regulatory perspectives

Humans are continuously exposed to low levels of thousands of industrial chemicals, most of which are poorly characterised in terms of their potential toxicity. The new paradigm in chemical risk assessment (CRA) aims to rely on animal-free testing, with kinetics being a key determinant of toxicity when moving from traditional animal studies to integrated in vitro-in silico approaches. In a kinetically informed CRA, membrane transporters, which have been intensively studied during drug development, are an essential piece of information. However, how existing knowledge on transporters gained in the drug field can be applied to CRA is not yet fully understood. This review outlines the opportunities, challenges and existing tools for investigating chemical-transporter interactions in kinetically informed CRA without animal studies. Various environmental chemicals acting as substrates, inhibitors or modulators of transporter activity or expression have been shown to impact TK, just as drugs do. However, because pollutant concentrations are often lower in humans than drugs and because exposure levels and internal chemical doses are not usually known in contrast to drugs, new approaches are required to translate transporter data and reasoning from the drug sector to CRA. Here, the generation of in vitro chemical-transporter interaction data and the development of transporter databases and classification systems trained on chemical datasets (and not only drugs) are proposed. Furtheremore, improving the use of human biomonitoring data to evaluate the in vitro-in silico transporter-related predicted values and developing means to assess uncertainties could also lead to increase confidence of scientists and regulators in animal-free CRA. Finally, a systematic characterisation of the transportome (quantitative monitoring of transporter abundance, activity and maintenance over time) would reinforce confidence in the use of experimental transporter/barrier systems as well as in established cell-based toxicological assays currently used for CRA.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.

Drug Transporters in Xenobiotic Disposition and Pharmacokinetic Prediction

Drug transporters are widely expressed in organs and tissue barriers throughout human and animal bodies. Studies over the last two decades have identified various ATP-binding cassette and solute carrier transporters that play critical roles in the absorption, distribution, metabolism, and elimination of drugs and xenobiotics. This special section contains more than 20 original manuscripts and reviews that cover the most recent advances in the areas of drug transporter research, including the basic biology and function of transporters, expression of drug transporters in organ and tissue barriers, the mechanisms underlying regulation of transporter expression, transporter-mediated drug disposition in animal models, and the development and utilization of new technologies in drug transporter study, as well as pharmacokinetic modeling and simulation to assess transporter involvement in drug disposition and drug-drug interactions. We believe that the topics covered in this special section will advance our understanding of the roles of transporters in drug disposition, efficacy, and safety.

Physiologically Based Pharmacokinetic Modeling in Regulatory Science: An Update From the U.S. Food and Drug Administration's Office of Clinical Pharmacology

This commentary provides an update on the status of physiologically based pharmacokinetic modeling and simulation at the U.S. Food and Drug Administration's Office of Clinical Pharmacology. Limitations and knowledge gaps in integration of physiologically based pharmacokinetic approach to inform regulatory decision making, as well as the importance of scientific engagement with drug developers who intend to use this approach, are highlighted.

Transporters in Drug Development: Scientific and Regulatory Considerations

Transporters can affect a drug's pharmacokinetics (PK) by controlling absorption, distribution, and elimination processes. They can also affect a drug's pharmacodynamics (PD) by influencing its access to the site of action. More recently, transporters have become important as drug targets (e.g., urate transporter inhibitors as treatment for gout and sodium/glucose cotransporter-2 inhibitors for treating type 2 diabetes). As such, it is important to consider the role of transporters during drug development.

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.

Development of a Physiologically Based Pharmacokinetic Model of Ethionamide in the Pediatric Population by Integrating Flavin-Containing Monooxygenase 3 Maturational Changes Over Time

Currently, ethionamide is the most frequently prescribed second-line antituberculosis drug in children. After extensive metabolism by flavin-containing monooxygenase (FMO) isoform 3 in the liver, the drug may exert cytotoxic effects. The comparison of children in different age groups revealed a significant age-related increase in ethionamide elimination in vivo. However, to date, the exact mechanism underlying this dynamic increase in ethionamide elimination has not been elucidated. We hypothesized that the age-dependent changes in ethionamide elimination were predominantly a result of the progressive increases in the expression and metabolic capacity of FMO3 during childhood. To test this hypothesis, a full physiologically based pharmacokinetic (PBPK) model of ethionamide was established and validated in adults through incorporation of comprehensive metabolism and transporter profiles, then expanded to the pediatric population through integration of FMO3 maturational changes over time. Thus, a good prediction PBPK model was validated successfully both in adults and children and applied to demonstrate the critical contribution of FMO3 in the mechanistic elimination pathway of ethionamide. In addition, a significant correlation between clearance and age was observed in children by accounting for ethionamide maturation, which could offer a mechanistic understanding of the age-associated changes in ethionamide elimination. In conclusion, this study underlines the benefits of in vitro-in vivo extrapolation and a quantitative PBPK approach for the investigation of transporter-enzyme interplay in ethionamide disposition and the demonstration of FMO3 ontogeny in children.

Effect of OATP1B1/1B3 Inhibitor GDC-0810 on the Pharmacokinetics of Pravastatin and Coproporphyrin I/III in Healthy Female Subjects

Developed as an oral anticancer drug to treat estrogen receptor-positive breast cancer, GDC-0810 was shown to be a potent inhibitor of organic anion-transporting polypeptide 1B1 and 1B3 (OATP1B1/1B3) from an in vitro assay. A clinical study was conducted to assess the drug-drug interaction potential between GDC-0810 and pravastatin, which is a relatively selective and sensitive OATP1B1/1B3 substrate. Fifteen healthy female subjects of non-childbearing potential were enrolled in the study. On day 1 in period 1, a single 10-mg dose of pravastatin was administered to all subjects. Following a 4-day washout period, 600 mg of GDC-0810 was administered once daily on days 5 through 8 in period 2 to achieve steady-state concentrations. On day 7, a single dose of 10-mg pravastatin was coadministered with the 600-mg GDC-0810 dose. Concentrations of pravastatin (periods 1 and 2) and GDC-0810 (period 2 only) were quantified in blood samples and subsequently used to calculate the pharmacokinetics (PK) parameters. The pravastatin mean maximal concentration and area under the curve values were approximately 20% and 41% higher, respectively, following pravastatin coadministration with GDC-0810 compared to pravastatin alone. Based on the magnitude of change in this drug-drug interaction study, dose adjustments for pravastatin (and other OATP1B1/1B3 substrates) were not considered necessary when administered with GDC-0810. Retrospectively, the endogenous biomarkers of OATP1B1/1B3, coproporphyrin I and III, were also measured and showed changes comparable to those of pravastatin, indicating their utility in detecting weak inhibition of OATP1B1/1B3 in the clinical setting.

Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective

This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.

Effects of Adamantyl Derivatives on Pharmacokinetic Behavior of Paclitaxel in Rats

Paclitaxel (PTX) is one of the most frequently used anticancer agent for treating refractory ovarian cancer, metastatic breast cancer and non-small cell lung cancer. However, its oral administration is impeded by very low bioavailability (<5%) due to the P-glycopprotein (P-gp) efflux pump effect. This study investigated in vitro and in vivo P-gp inhibitory effects of adamantyl derivatives AC-603 and AC-786 in rats. Two adamantyl derivatives tested in this study increased the cytotoxicity of daunomycin (DNM) in P-gp overexpressed cell line by inhibiting P-gp efflux function. Pharmacokinetics of PTX with orally co-administered P-gp inhibitors were assessed in rats to improve PTX absorption. The pharmacokinetic parameters of PTX were determined in rats after intravenous (2 mg/kg) or oral (25 mg/kg) administration in the presence or absence of verapamil (a positive control), AC-603 or AC-786 (0.5 mg/kg or 5 mg/kg). Compared to control group (PTX alone), experimental groups (PTX with AC-603 or AC-786) significantly increased the area under the plasma concentration-time curve of PTX following oral administration by 1.7-2.2 fold. The volume of distribution and total clearance of PTX were decreased, while other parameters were not significantly changed. In conclusion, co-administration of AC-603 or AC-786 enhanced the relative bioavailability of orally administered PTX as compared to control.

The Role of the Kidney in Drug Elimination: Transport, Metabolism, and the Impact of Kidney Disease on Drug Clearance

Recent advances in the identification and characterization of renal drug transporters and drug-metabolizing enzymes has led to greater understanding of their roles in drug and chemical elimination and in modulation of the intrarenal exposure and response to drugs, nephrotoxic compounds, and physiological mediators. Furthermore, there is increasing awareness of the potential importance of drug-drug interactions (DDIs) arising from inhibition of renal transporters, and regulatory agencies now provide recommendations for the evaluation of transporter-mediated DDIs. Apart from the well-recognized effects of kidney disease on renal drug clearance, there is a growing body of evidence demonstrating that the nonrenal clearances of drugs eliminated by certain transporters and drug-metabolizing enzymes are decreased in patients with chronic kidney disease (CKD). Based on these observations, renal impairment guidance documents of regulatory agencies recommend pharmacokinetic characterization of both renally cleared and nonrenally cleared drugs in CKD patients to inform possible dosage adjustment.

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.

Physiologically Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Coadministered With Ritonavir

Management of comorbidities and medications is complex in HIV-1-infected patients. The overall objective of this project was to develop separate physiologically based pharmacokinetic (PBPK) substrate models for the protease inhibitors darunavir and lopinavir. These protease inhibitors are used in the treatment of HIV infection. Both darunavir and lopinavir are coadministered with another medication that inhibits cytochrome (CYP) 3A. The current project focused on PBPK modeling for darunavir and lopinavir coadministered with ritonavir. Darunavir and lopinavir PBPK models that accounted for ritonavir CYP3A inhibition effects (linked PBPK models) were developed. The linked PBPK models were then used to predict the effect on darunavir or lopinavir exposure from CYP modulators. In the next step, the predicted effect of hepatic impairment was evaluated. Additional exploratory analyses predicted CYP3A inhibition effects on darunavir or lopinavir exposure in simulated hepatically impaired subjects. The linked PBPK models reasonably predicted darunavir or lopinavir exposure based on simulations with CYP inhibitors or inducers. Exploratory simulations using the linked darunavir or lopinavir PBPK models indicated CYP3A inhibition may further increase darunavir or lopinavir exposure in patients with hepatic impairment.

Prediction of renal transporter-mediated drug-drug interactions for a drug which is an OAT substrate and inhibitor using PBPK modelling

A PBPK modelling approach was used to predict organic anion transporter (OAT) mediated drug-drug interactions involving S44121, a substrate and an inhibitor of OAT1 and OAT3. Model predictions were then compared to the results of a clinical DDI study which was carried out to investigate the interaction of S44121 with probenecid, tenofovir and ciprofloxacin. PBPK models were developed and qualified using existing clinical data, and inhibition constants were determined in vitro. The model predictions for S44121 as an OAT inhibitor were similar to the results obtained from the clinical DDI study, with no interaction observed for tenofovir or ciprofloxacin in the presence of S44121. An observed AUC ratio of 2.2 was obtained for S44121 in the presence of probenecid, which was slightly higher than the model predicted AUC ratio of 1.6. A DDI study in the monkey was also carried out for the interaction between S44121 and probenecid, since the monkey has previously been reported to be a good preclinical model for OAT-mediated DDI. However, this study highlighted a species difference in the major route of S44121 elimination between monkey (mainly hepatic metabolism) and human (mainly renal excretion of unchanged drug), rendering a comparison between the two DDI studies difficult. Overall, for S44121 the PBPK modelling approach gave a better prediction of the extent of DDI than the static predictions based on inhibitor C_max and IC₅₀, therefore this can be considered a potentially valuable tool within drug development.

A Prediction Method for P-glycoprotein-Mediated Drug-Drug Interactions at the Human Blood-Brain Barrier From Blood Concentration-Time Profiles, Validated With PET Data

The purpose of this study was to establish physiologically based pharmacokinetic models to predict in humans the brain concentration-time profiles and P-glycoprotein (Pgp)-mediated brain drug-drug interactions between the model Pgp substrate (R)-[¹¹C]verapamil (VPM), the model dual Pgp/breast cancer resistance protein (BCRP) substrate [¹¹C]tariquidar (TQD), and the Pgp inhibitor tariquidar. The model predictions were validated with results from positron emission tomography studies in humans. Using these physiologically based pharmacokinetic models, the differences between predicted and observed areas under the concentration-time curves (AUC) of VPM and TQD in the brain were within a 1.2-fold and 2.5-fold range, respectively. Also, brain AUC increases of VPM and TQD after Pgp inhibitor administration were predicted with 2.5-fold accuracy when in vitro inhibition constant or half-maximum inhibitory concentration values of tariquidar were used. The predicted rank order of the magnitude of AUC increases reflected the results of the clinical positron emission tomography studies. Our results suggest that the established models can predict brain exposure from the respective blood concentration-time profiles and rank the magnitude of the Pgp-mediated brain drug-drug interaction potential for both Pgp and Pgp/BCRP substrates in humans.

Model Systems for Studying the Role of Canalicular Efflux Transporters in Drug-Induced Cholestatic Liver Disease

Bile formation is a key function of the liver. Disturbance of bile flow may lead to liver disease and is called cholestasis. Cholestasis may be inherited, for example, in progressive familial intrahepatic cholestasis or acquired, for example, by drug-mediated inhibition of bile salt export from hepatocytes into the canaliculi. The key transport system for exporting bile salts into the canaliculi is the bile salt export pump. Inhibition of the bile salt export pump by drugs is a well-established cause of drug-induced cholestasis. Investigation of the role of the multidrug resistance protein 3, essential for biliary phospholipid secretion, is emerging now. This overview summarizes current concepts and methods with an emphasis on in vitro model systems for the investigation of drug-induced cholestasis in the general context of drug-induced liver injury.

Application of the MechPeff model to predict passive effective intestinal permeability in the different regions of the rodent small intestine and colon

A major component of physiologically based pharmacokinetic (PBPK) models is the prediction of the rate and extent of absorption of orally dosed drugs for which knowledge of effective passive intestinal permeability (P_eff ) is essential. Single-pass intestinal perfusion (SPIP) studies are used to establish effective permeability in vivo but are difficult to perform in rodents, while mechanistic models to predict drug P_eff in rat and mouse have not been published. This work evaluates the predictive performance of the 'MechPeff' model to predict P_eff in the rodent intestine based upon knowledge of regional gut physiology and drug-specific physicochemical parameters. The 'MechPeff' model, built-in to the Simcyp Rat and Mouse Simulators, predicts transcellular, paracellular and mucus layer permeabilities and combines these to give the overall P_eff . The jejunal and/or ileal P_eff was predicted for 12 (4) acidic, 13 (12) basic, 10 (8) neutral and 2 (0) ampholytic drugs in the rat (mouse), spanning a wide range of MW and logP_o:w , and compared with experimental P_eff obtained using SPIP. A key input is the intrinsic transcellular permeability (P_trans,0 ) which can be derived from modelling of appropriate in vitro permeability experiments or predicted from physicochemical properties. The P_eff predictions were reasonably good when experimentally derived P_trans,0 was used; from 42 P_eff,rat values, 24 (57%) were within 3-fold, and of 19 P_eff,mouse values, 12 (63%) were within 3-fold, of observed P_eff . Considering the lack of alternative models to predict P_eff in preclinical species, and the minimal drug-specific inputs required, this model provides a valuable tool within drug discovery and development programmes. Copyright © 2017 John Wiley & Sons, Ltd.

Unequivocal evidence supporting the segregated flow intestinal model that discriminates intestine versus liver first-pass removal with PBPK modeling

Merits of the segregated flow model (SFM), highlighting the intestine as inert serosa and active enterocyte regions, with a smaller fractional (f_Q < 0.3) intestinal flow (Q_I ) perfusing the enterocyte region, are described. Less drug in the circulation reaches the enterocytes due to the lower flow (f_Q Q_I ) in comparison with drug administered into the gut lumen, fostering the idea of route-dependent intestinal removal. The SFM has been found superior to the traditional model (TM), which views the serosa and enterocytes totally as a well-mixed tissue perfused by 100% of the intestinal flow, Q_I . The SFM model is able to explain the lower extents of intestinal metabolism of enalapril, morphine and midazolam with i.v. vs. p.o. dosing. For morphine, the urine/bile ratio of the metabolite, morphine glucuronide MGurineMGbile for p.o. was 2.6× that of i.v. This was due to the higher proportion of intestinally formed morphine glucuronide, appearing more in urine than in bile due to its low permeability and greater extent of intestinal formation with p.o. administration. By contrast, the TM predicted the same MGurineMGbile for p.o. vs. i.v. The TM predicted that the contributions of the intestine:liver to first-pass removal were 46%:54% for both p.o. and i.v. The SFM predicted same 46%:54% (intestine:liver) for p.o., but 9%:91% for i.v. By contrast, the kinetics of codeine, the precursor of morphine, was described equally well by the SFM- and TM-PBPK models, a trend suggesting that intestinal metabolism of codeine is negligible. Fits to these PBPK models further provide insightful information towards metabolite formation: available fractions and the fractions of hepatic and total clearances that form the metabolite in question. The SFM-PBPK model is useful to identify not only the presence of intestinal metabolism but the contributions of the intestine and liver for metabolite formation. Copyright © 2016 John Wiley & Sons, Ltd.