Mechanistic Modeling of Hepatic Transport from Cells to Whole Body: Application to Napsagatran and Fexofenadine

Pharmacokinetics and Disposition of Heparin-Binding Growth Factor Midkine Antisense Oligonucleotide Nanoliposomes in Experimental Animal Species and Prediction of Human Pharmacokinetics Using a Physiologically Based Pharmacokinetic Model

Encapsulating the antisense oligonucleotide drug MK-ASODN with nanoliposomes greatly improved its potency and targeting to the heparin-binding growth factor midkine. The disposition and pharmacokinetic (PK) parameters of MK-ASODN nanoliposomes were studied in monkeys and rats, and the human PK parameters were predicted based on preclinical data using a physiologically based pharmacokinetic (PBPK) model. Following intravenous injection, the drug plasma concentration rapidly declined in a multiexponential manner, and the drug was rapidly transferred to tissues from the circulation. The terminal t_1/2 in plasma was clearly longer than that of the unmodified antisense nucleic acid drug. According to the AUC,MK-ASODN nanoliposomes were mainly distributed in the kidney, spleen, and liver. . MK-ASODN nanoliposomes were highly plasma protein bound, limiting their urinary excretion. Very little MK-ASODN nanoliposomes were detected in urine or feces. The plasma disposition of MK-ASODN nanoliposomes appeared nonlinear over the studied dose range of 11.5–46 mg kg⁻¹. The monkey PBPK model of MK-ASODN nanoliposomes was well established and successfully extrapolated to predict MK-ASODN nanoliposome PK in humans. These disposition and PK data support further development in phase I clinical studies.

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.

Predicting the Effects of Different Triazole Antifungal Agents on the Pharmacokinetics of Tamoxifen

Tamoxifen is an antiestrogen drug that is widely used in the adjuvant chemotherapy of estrogen receptor-α (ERα)-positive breast cancer. Chemotherapy could suppress immune function in breast cancer patients, which may cause invasive fungal infections (IFIs). Triazoles (voriconazole, fluconazole, and itraconazole) were commonly used for IFI. The physiologically based pharmacokinetic (PBPK) models were developed to investigate the influence of different triazoles on tamoxifen pharmacokinetics in this paper. To investigate the influence of different triazoles (voriconazole, fluconazole, itraconazole) on tamoxifen pharmacokinetics. Adjusted physicochemical data and pharmacokinetic parameters of voriconazole, fluconazole, itraconazole, and tamoxifen were obtained from published literatures. PBPK models were built and verified in healthy subjects using GastroPlus™. Voriconazole, itraconazole, and tamoxifen were administered orally. Fluconazole was administered intravenously. Simulated plasma concentration-time curves of the voriconazole, fluconazole, itraconazole, and tamoxifen showed good agreement with the observed profiles, respectively. The DDI simulations showed that the pharmacokinetic parameters of tamoxifen were increased by various degrees when coadministered with different triazoles. In healthy subjects, the area under the plasma concentration-time curve from 0 to t h (AUC_0-t) of tamoxifen was increased by 41%, 5%, and1% when coadministrated with voriconazole, fluconazole, and itraconazole, respectively. The PBPK models adequately characterized the pharmacokinetics of tamoxifen and triazoles. Among the three triazoles, voriconazole exhibited the greatest effect on tamoxifen pharmacokinetics. In clinical practice, an effective dosage adjustment of tamoxifen may need to be considered and TDM for tamoxifen is advisable to guide dosing and optimize therapy when coadministered with voriconazole.

In vitro to in vivo extrapolation for high throughput prioritization and decision making

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

A Model-Based Approach To Assessing the Importance of Intracellular Binding Sites in Doxorubicin Disposition

Doxorubicin is an anticancer agent, which binds reversibly to topoisomerase I and II, intercalates to DNA base pairs, and generates free radicals. Doxorubicin has a high tissue:plasma partition coefficient and high intracellular binding to the nucleus and other subcellular compartments. The metabolite doxorubicinol has an extensive tissue distribution. This porcine study investigated whether the traditional implementation of tissue binding, described by the tissue:plasma partition coefficient (K_p,t), could be used to appropriately analyze and/or simulate tissue doxorubicin and doxorubicinol concentrations in healthy pigs, when applying a physiologically based pharmacokinetic (PBPK) model approach, or whether intracellular binding is required in the semi-PBPK model. Two semi-PBPK models were developed and evaluated using doxorubicin and doxorubicinol concentrations in healthy pig blood, bile, and urine and kidney and liver tissues. In the generic semi-PBPK model, tissue binding was described using the conventional K_p,t approach. In the binding-specific semi-PBPK model, tissue binding was described using intracellular binding sites. The best semi-PBPK model was validated against a second data set of healthy pig blood and bile concentrations. Both models could be used for analysis and simulations of biliary and urinary excretion of doxorubicin and doxorubicinol and plasma doxorubicinol concentrations in pigs, but the binding-specific model was better at describing plasma doxorubicin concentrations. Porcine tissue concentrations were 400- to 1250-fold better captured by the binding-specific model. This model adequately predicted plasma doxorubicin concentration-time and biliary doxorubicin excretion profiles against the validation data set. The semi-PBPK models applied were similarly effective for analysis of plasma concentrations and biliary and urinary excretion of doxorubicin and doxorubicinol in healthy pigs. Inclusion of intracellular binding in the doxorubicin semi-PBPK models was important to accurately describe tissue concentrations during in vivo conditions.

Influence of different proton pump inhibitors on the pharmacokinetics of voriconazole

This study aimed to determine the influence of proton pump inhibitors (PPIs) on the pharmacokinetics of voriconazole and to characterise potential drug-drug interactions (DDIs) between voriconazole and various PPIs (omeprazole, esomeprazole, lansoprazole and rabeprazole). Using adjusted physicochemical data and the pharmacokinetic (PK) parameters of voriconazole and PPIs, physiologically based pharmacokinetic (PBPK) models were built and were verified in healthy subjects using GastroPlus^TM to predict the plasma concentration-time profiles of voriconazole and PPIs. These models were then used to assess potential DDIs for voriconazole when administered with PPIs. The results indicated the PBPK model-simulated plasma concentration-time profiles of both voriconazole and PPIs were consistent with the observed profiles. In addition, the DDI simulations suggested that the PK values of voriconazole increased to various degrees when combined with several PPIs. The area under the plasma concentration-time curve for the time of the simulation (AUC_0-t) of voriconazole was increased by 39%, 18%, 12% and 1% when co-administered with omeprazole, esomeprazole, lansoprazole and rabeprazole, respectively. Omeprazole was the most potent CYP2C19 inhibitor tested, whereas rabeprazole had no influence on voriconazole (omeprazole > esomeprazole > lansoprazole > rabeprazole). However, in consideration of the therapeutic concentration range, dosage adjustment of voriconazole is unnecessary regardless of which PPI was co-administered.

Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards

A computational framework was developed to assist in screening and prioritizing chemicals based on their dosimetry, toxicity, and potential exposures. The overall strategy started with contextualizing chemical activity observed in high-throughput toxicity screening (HTS) by mapping these assays to biological events described in Adverse Outcome Pathways (AOPs). Next, in vitro to in vivo (IVIVE) extrapolation was used to convert an in vitro dose to an external exposure level, which was compared with potential exposure levels to derive an AOP-based margins of exposure (MOE). In this study, the framework was applied to estimate MOEs for chemicals that can potentially cause developmental toxicity following a putative AOP for fetal vasculogenesis/angiogenesis. A physiologically based pharmacokinetic (PBPK) model was developed to describe chemical disposition during pregnancy, fetal, neonatal, and infant to adulthood stages. Using this life-stage PBPK model, maternal exposures were estimated that would yield fetal blood levels equivalent to the chemical concentration that altered in vitro activity of selected HTS assays related to the most sensitive vasculogenesis/angiogenesis putative AOP. The resulting maternal exposure estimates were then compared with potential exposure levels using literature data or exposure models to derive AOP-based MOEs.

Does the Systemic Plasma Profile Inform the Liver Profile? Analysis Using a Physiologically Based Pharmacokinetic Model and Individual Compounds

The physiologically based pharmacokinetic (PBPK) model for liver transporter substrates has been established previously and used for predicting drug-drug interactions (DDI) and for clinical practice guidance. So far, nearly all the published PBPK models for liver transporter substrates have one or more hepatic clearance processes (i.e., active uptake, passive diffusion, metabolism, and biliary excretion) estimated by fitting observed systemic data. The estimated hepatic clearance processes are then used to predict liver concentrations and DDI involving either systemic or liver concentration. However, the accuracy and precision of such predictions are unclear. In this study, we try to address this question by using the PBPK model to generate simulated compounds for which we know both systemic and liver profiles. We then developed an approach to assess the accuracy and precision of predicted liver concentration. With hepatic clearance processes estimated using plasma data, model predictions of liver are typically accurate (i.e., true value is bounded by predicted maximum and minimum); however, only for a few compounds are predictions also precise. The results of the current study indicate that extra attention is required when using the current PBPK approach to predict liver concentration and DDI for transporter substrates dependent upon liver concentrations.

Hepatic drug transporters: the journey so far

INTRODUCTION

The key role of transporter biology in both the manifestation and treatment of disease is now firmly established. Experiences of sub-optimal drug exposure due to drug-transporter interplay have supported incorporation of studies aimed at understanding the interactions between compounds and drug transporters much earlier in drug discovery. While drug transporters can impact the most pivotal pharmacokinetic parameter with respect to human dose and exposure projections, clearance, at a renal or hepatobiliary level, the latter will form the focus of this perspective.

AREAS COVERED

A synopsis of guidelines on which transporters to study together with an overview of the currently available toolkit is presented. A perspective on when to conduct studies with various hepatic transporters is also provided together with structural "alerts" which should prompt early investigation.

EXPERT OPINION

Great progress has been made in individual laboratories and via consortia to understand the role of drug transporters in disease, drug disposition, drug-drug interactions and toxicity. A systematic analysis of the value posed by the available approaches and an inter-lab comparison now seems warranted. The emerging ability to use physico-chemical properties to guide future screening cascades promises to revolutionise the efficiency of early drug discovery.

In Vitro Assessment of Uptake and Lysosomal Sequestration of Respiratory Drugs in Alveolar Macrophage Cell Line NR8383

Purpose

To assess accumulation and lysosomal sequestration of 9 drugs used in respiratory indications (plus imipramine as positive control) in the alveolar macrophage (AM) cell line NR8383.

Methods

For all drugs, uptake at 5 μM was investigated at 37 and 4°C to delineate active uptake and passive diffusion processes. Accumulation of basic clarithromycin, formoterol and imipramine was also assessed over 0.1–100 μM concentration range. Lysosomal sequestration was investigated using ammonium chloride (NH₄Cl), monensin and nigericin. Impact of lysosomal sequestration on clarithromycin accumulation kinetics was investigated.

Results

Both cell-to-medium concentration ratio (K_p) and uptake clearance (CL_uptake) ranged > 400-fold for the drugs investigated. The greatest K_p was observed for imipramine (391) and clarithromycin (82), in contrast to no accumulation seen for terbutaline. A concentration-dependent accumulation was evident for the basic drugs investigated. Imipramine and clarithromycin K_p and CL_uptake were reduced by 59–85% in the presence of NH₄Cl and monensin/nigericin, indicating lysosomal accumulation, whereas lysosomal sequestration was not pronounced for the other 8 respiratory drugs. Clarithromycin uptake rate was altered by NH₄Cl, highlighting the impact of subcellular distribution on accumulation kinetics.

Conclusions

This study provides novel evidence of the utility of NR8383 for investigating accumulation and lysosomal sequestration of respiratory drugs in AMs.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-015-1753-8) contains supplementary material, which is available to authorized users.

Comparative Proteomic Analysis of Human Liver Tissue and Isolated Hepatocytes with a Focus on Proteins Determining Drug Exposure

Freshly isolated human hepatocytes are considered the gold standard for in vitro studies of liver functions, including drug transport, metabolism, and toxicity. For accurate predictions of the in vivo outcome, the isolated hepatocytes should reflect the phenotype of their in vivo counterpart, i.e., hepatocytes in human liver tissue. Here, we quantified and compared the membrane proteomes of freshly isolated hepatocytes and human liver tissue using a label-free shotgun proteomics approach. A total of 5144 unique proteins were identified, spanning over 6 orders of magnitude in abundance. There was a good global correlation in protein abundance. However, the expression of many plasma membrane proteins was lower in the isolated hepatocytes than in the liver tissue. This included transport proteins that determine hepatocyte exposure to many drugs and endogenous compounds. Pathway analysis of the differentially expressed proteins confirmed that hepatocytes are exposed to oxidative stress during isolation and suggested that plasma membrane proteins were degraded via the protein ubiquitination pathway. Finally, using pitavastatin as an example, we show how protein quantifications can improve in vitro predictions of in vivo liver clearance. We tentatively conclude that our data set will be a useful resource for improved hepatocyte predictions of the in vivo outcome.

Prediction of the pharmacokinetics and tissue distribution of levofloxacin in humans based on an extrapolated PBPK model

This study developed a physiologically based pharmacokinetic (PBPK) model in intraabdominally infected rats and extrapolated it to humans to predict the levofloxacin pharmacokinetics and penetration into tissues. Twelve male rats with intraabdominal infections induced by Escherichia coli received a single dose of 50 mg/kg body weight of levofloxacin. Blood plasma was collected at 5, 10, 20, 30, 60, 120, 240, 480 and 1440 min after injection, respectively. A PBPK model was developed in rats and extrapolated to humans using GastroPlus software. The predictions were assessed by comparing predictions and observations. In the plasma concentration-versus-time profile of levofloxacin in rats, C max was 23.570 μg/ml at 5 min after intravenous injection, and t1/2 was 2.38 h. The plasma concentration and kinetics in humans were predicted and validated by the observed data. Levofloxacin penetrated and accumulated with high concentrations in the heart, liver, kidney, spleen, muscle and skin tissues in humans. The predicted tissue-to-plasma concentration ratios in abdominal viscera were between 1.9 and 2.3. When rat plasma concentrations were known, extrapolation of a PBPK model was a method to predict the drug pharmacokinetics and penetration in humans. Levofloxacin had good penetration into the liver, kidney and spleen as well as other tissues in humans. This pathological model extrapolation may provide a reference for the study of antiinfective PK/PD. In our study, levofloxacin penetrated well into abdominal organs. Also ADR monitoring should be implemented when using levofloxacin.

Prediction of Pharmacokinetics and Penetration of Moxifloxacin in Human with Intra-Abdominal Infection Based on Extrapolated PBPK Model

The aim of this study is to develop a physiologically based pharmacokinetic (PBPK) model in intra-abdominal infected rats, and extrapolate it to human to predict moxifloxacin pharmacokinetics profiles in various tissues in intra-abdominal infected human. 12 male rats with intra-abdominal infections, induced by Escherichia coli, received a single dose of 40 mg/kg body weight of moxifloxacin. Blood plasma was collected at 5, 10, 20, 30, 60, 120, 240, 480, 1440 min after drug injection. A PBPK model was developed in rats and extrapolated to human using GastroPlus software. The predictions were assessed by comparing predictions and observations. In the plasma concentration versus time profile of moxifloxcinin rats, C_max was 11.151 µg/mL at 5 min after the intravenous injection and t_1/2 was 2.936 h. Plasma concentration and kinetics in human were predicted and compared with observed datas. Moxifloxacin penetrated and accumulated with high concentrations in redmarrow, lung, skin, heart, liver, kidney, spleen, muscle tissues in human with intra-abdominal infection. The predicted tissue to plasma concentration ratios in abdominal viscera were between 1.1 and 2.2. When rat plasma concentrations were known, extrapolation of a PBPK model was a method to predict drug pharmacokinetics and penetration in human. Moxifloxacin has a good penetration into liver, kidney, spleen, as well as other tissues in intra-abdominal infected human. Close monitoring are necessary when using moxifloxacin due to its high concentration distribution. This pathological model extrapolation may provide reference to the PK/PD study of antibacterial agents.

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.

A mechanistic framework for in vitro-in vivo extrapolation of liver membrane transporters: prediction of drug-drug interaction between rosuvastatin and cyclosporine

Background and Objectives

The interplay between liver metabolising enzymes and transporters is a complex process involving system-related parameters such as liver blood perfusion as well as drug attributes including protein and lipid binding, ionisation, relative magnitude of passive and active permeation. Metabolism- and/or transporter-mediated drug–drug interactions (mDDIs and tDDIs) add to the complexity of this interplay. Thus, gaining meaningful insight into the impact of each element on the disposition of a drug and accurately predicting drug–drug interactions becomes very challenging. To address this, an in vitro–in vivo extrapolation (IVIVE)-linked mechanistic physiologically based pharmacokinetic (PBPK) framework for modelling liver transporters and their interplay with liver metabolising enzymes has been developed and implemented within the Simcyp Simulator^®.

Methods

In this article an IVIVE technique for liver transporters is described and a full-body PBPK model is developed. Passive and active (saturable) transport at both liver sinusoidal and canalicular membranes are accounted for and the impact of binding and ionisation processes is considered. The model also accommodates tDDIs involving inhibition of multiple transporters. Integrating prior in vitro information on the metabolism and transporter kinetics of rosuvastatin (organic-anion transporting polypeptides OATP1B1, OAT1B3 and OATP2B1, sodium-dependent taurocholate co-transporting polypeptide [NTCP] and breast cancer resistance protein [BCRP]) with one clinical dataset, the PBPK model was used to simulate the drug disposition of rosuvastatin for 11 reported studies that had not been used for development of the rosuvastatin model.

Results

The simulated area under the plasma concentration–time curve (AUC), maximum concentration (C_max) and the time to reach C_max (t_max) values of rosuvastatin over the dose range of 10–80 mg, were within 2-fold of the observed data. Subsequently, the validated model was used to investigate the impact of coadministration of cyclosporine (ciclosporin), an inhibitor of OATPs, BCRP and NTCP, on the exposure of rosuvastatin in healthy volunteers.

Conclusion

The results show the utility of the model to integrate a wide range of in vitro and in vivo data and simulate the outcome of clinical studies, with implications for their design.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-013-0097-y) contains supplementary material, which is available to authorized users.

Effects of verapamil on the pharmacokinetics and hepatobiliary disposition of fexofenadine in pigs

The pharmacokinetics (PK) of fexofenadine (FEX) in pigs were investigated with the focus on exploring the interplay between hepatic transport and metabolism when administered intravenously (iv) alone or with verapamil. The in vivo pig model enabled simultaneous sampling from plasma (pre-liver, post-liver and peripheral), bile and urine. Each animal was administered FEX 35mg iv alone or with verapamil 35mg. Plasma, bile and urine were analyzed with liquid chromatography-tandem mass spectrometry. Non-compartmental analysis (NCA) was used to estimate traditional PK parameters. In addition, a physiologically based pharmacokinetic (PBPK) model consisting of 11 compartments (6 tissues +5 sample sites) was applied for mechanistic elucidation and estimation of individual PK parameters. FEX had a terminal half-life of 1.7h and a liver extraction of 3%. The fraction of the administered dose of unchanged FEX excreted into the bile was 25% and the bile exposure was more than 100 times higher than the portal vein total plasma exposure, indicating carrier-mediated (CM) disposition processes in the liver. 23% of the administered dose of FEX was excreted unchanged in the urine. An increase in FEX plasma exposure (+50%) and a decrease in renal clearance (-61%) were detected by NCA as a direct effect of concomitant administration of verapamil. However, analysis of the PBPK model also revealed that biliary clearance was significantly inhibited (-53%) by verapamil. In addition, PBPK analysis established that metabolism and CM uptake were important factors in the disposition of FEX in the liver. In conclusion, this study demonstrated that CM transport of FEX in both liver and kidneys was inhibited by a single dose of verapamil.

The role of transporters in toxicity and disease

The significance of transporters in the disposition, metabolism, and elimination of drugs is well recognized. One gap in our knowledge is a comprehensive understanding of how drug transporters change functionality (their amount and activity) in response to disease and how disease and its inevitable pathology change transporter expression. In this issue of Drug Metabolism and Disposition a series of review and primary research articles are presented to highlight the importance of transporters in toxicity and disease. Because of the central role of the liver in drug metabolism, many of the articles in this theme issue focus on transporters in the liver and how pathology or alterations in physiology affects transporter expression. The contributing authors have also considered the role of transporters in drug interactions as well as drug-induced liver injury. Noninvasive approaches to assessing transporter function in vivo are also described. Several articles highlight important issues in oncology where toxicity must be balanced against efficacy. In total, this theme issue will provide a stepping-stone to future studies that will establish a more comprehensive understanding of transporters in disease.

Reduced physiologically-based pharmacokinetic model of repaglinide: impact of OATP1B1 and CYP2C8 genotype and source of in vitro data on the prediction of drug-drug interaction risk

PURPOSE

To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model.

METHODS

Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CLuptake) in different genotype groups applying a population approach in NONMEM v.7.2.

RESULTS

Estimated repaglinide CLuptake corresponded to 217 and 113 μL/min/10(6) cells for SLCO1B1 c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CLuptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CLmet and CLdiff uncertainty on the CLuptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinide OATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies.

CONCLUSIONS

The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.

Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels

Quantitative structure-activity relationship (QSAR) studies and mechanistic mathematical modeling approaches have been independently employed for analysing and predicting the transport and distribution of small molecule chemical agents in living organisms. Both of these computational approaches have been useful for interpreting experiments measuring the transport properties of small molecule chemical agents, in vitro and in vivo. Nevertheless, mechanistic cell-based pharmacokinetic models have been especially useful to guide the design of experiments probing the molecular pathways underlying small molecule transport phenomena. Unlike QSAR models, mechanistic models can be integrated from microscopic to macroscopic levels, to analyse the spatiotemporal dynamics of small molecule chemical agents from intracellular organelles to whole organs, well beyond the experiments and training data sets upon which the models are based. Based on differential equations, mechanistic models can also be integrated with other differential equations-based systems biology models of biochemical networks or signaling pathways. Although the origin and evolution of mathematical modeling approaches aimed at predicting drug transport and distribution has occurred independently from systems biology, we propose that the incorporation of mechanistic cell-based computational models of drug transport and distribution into a systems biology modeling framework is a logical next step for the advancement of systems pharmacology research.

In vitro-in vivo correlation for low-clearance compounds using hepatocyte relay method

In vitro-in vivo correlation (IVIVC) of intrinsic clearance in preclinical species of rat and dog was established using the hepatocyte relay method to support high-confidence prediction of human pharmacokinetics for low-clearance compounds. Good IVIVC of intrinsic clearance was observed for most of the compounds, with predicted values within 2-fold of the observed values. The exceptions involved transporter-mediated uptake clearance or metabolizing enzymes with extensive extrahepatic contribution. This is the first assay available to address low clearance challenges in preclinical species for IVIVC in drug discovery. It extends the utility of the hepatocyte relay method in addressing low clearance issues.

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.

Primary hepatocyte cultures as prominent in vitro tools to study hepatic drug transporters

Before any drug can be placed on the market, drug efficacy and safety must be ensured through rigorous testing. Animal models are used for this purpose, though currently increasing attention goes to the use of alternative in vitro systems. In particular, liver-based testing platforms that allow the prediction of pharmacokinetic (PK) and pharmacotoxicological properties during the early phase of drug development are of interest. They also enable the screening of potential effects on hepatic drug transporters. The latter are known to affect drug metabolism and disposition, thereby possibly underlying drug-drug interactions, which, in turn, may result in liver toxicity. Clearly, stable in vivo-like functional expression of drug transporters in hepatic in vitro settings is a prerequisite to be applicable in routine PK and pharmacotoxicological testing. In the first part of the article, an updated overview of hepatic drug transporters is provided, followed by a state-of-the-art review of drug-transporter production and activity in primary hepatocyte cultures (PHCs), being the gold-standard in vitro system. Specific focus is hereby put on strategies to maintain long-term functional expression, in casu of drug transporters, in these systems. In the second part, the use of PHCs to assess hepatobiliary transport and transporter-mediated interactions is outlined.

Effect of Ritonavir on (99m)Technetium-Mebrofenin Disposition in Humans: A Semi-PBPK Modeling and In Vitro Approach to Predict Transporter-Mediated DDIs

A semiphysiologically based pharmacokinetic (semi-PBPK) model was developed to describe a unique blood, liver, and bile clinical data set for the hepatobiliary imaging agent ^99mTechnetium–mebrofenin (^99mTc–mebrofenin), and to simulate sites/mechanisms of a ^99mTc–mebrofenin–ritonavir drug–drug interaction (DDI). The transport inhibitor ritonavir (multiple-dose: 2 × 300 mg) significantly increased systemic ^99mTc–mebrofenin exposure as compared with control (4,464 ± 1,861 vs. 1,970 ± 311 nCi min/ml; mean ± SD), without affecting overall hepatic exposure or biliary recovery. A novel extrahepatic distribution compartment was required to characterize ^99mTc–mebrofenin disposition. Ritonavir inhibited ^99mTc–mebrofenin accumulation in human sandwich-cultured hepatocytes (SCH) (half maximal inhibitory concentration (IC₅₀) = 3.46 ± 1.53 µmol/l). Despite ritonavir accumulation in hepatocytes, intracellular binding was extensive (97. 6%), which limited interactions with multidrug resistance protein 2 (MRP2)-mediated biliary excretion. These in vitro data supported conclusions from modeling/simulation that ritonavir inhibited ^99mTc–mebrofenin hepatic uptake, but not biliary excretion, at clinically relevant concentrations. This integrated approach, utilizing modeling, clinical, and in vitro data, emphasizes the importance of hepatic and extrahepatic distribution, assessment of inhibitory potential in relevant in vitro systems, and intracellular unbound concentrations to assess transporter-mediated hepatic DDIs.

Ethnic variability in the plasma exposures of OATP1B1 substrates such as HMG-CoA reductase inhibitors: a kinetic consideration of its mechanism

Because the plasma exposure levels of rosuvastatin in Asians are generally twice those in Caucasians, the starting dose for Asians in the United States is set to half of that for non-Asians. However, the precise role of ethnicity in the clearance of rosuvastatin has not yet been clarified. This review focuses on ethnic variability in the clinical pharmacokinetics of 3-hydroxy-3-methylglutaryl co-enzyme A (HMG-CoA) reductase inhibitors (statins) and angiotensin II receptor antagonists. The mechanisms of such variability are discussed quantitatively, with building a hypothetical model for pravastatin, and validated against other statins. Our analyses suggest that the ethnic variability in the plasma exposure of statins cannot be explained only by the difference in the allele frequencies of organic anion-transporting polypeptide (OATP)1B1 and breast cancer resistance protein (BCRP), and the intrinsic ethnic variability in the activity of OATP1B1 (the ratio of Japanese/Caucasians is 0.584) must be considered. Further work and validation with additional data will clarify the applicability of this model to other OATP1B1 substrates.

Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling

AIM

To develop and evaluate a whole-body physiologically based pharmacokinetic (WB-PBPK) model of bisoprolol and to simulate its exposure and disposition in healthy adults and patients with renal function impairment.

METHODS

Bisoprolol dispositions in 14 tissue compartments were described by perfusion-limited compartments. Based the tissue composition equations and drug-specific properties such as log P, permeability, and plasma protein binding published in literatures, the absorption and whole-body distribution of bisoprolol was predicted using the 'Advanced Compartmental Absorption Transit' (ACAT) model and the whole-body disposition model, respectively. Renal and hepatic clearances were simulated using empirical scaling methods followed by incorporation into the WB-PBPK model. Model refinements were conducted after a comparison of the simulated concentration-time profiles and pharmacokinetic parameters with the observed data in healthy adults following intravenous and oral administration. Finally, the WB-PBPK model coupled with a Monte Carlo simulation was employed to predict the mean and variability of bisoprolol pharmacokinetics in virtual healthy subjects and patients.

RESULTS

The simulated and observed data after both intravenous and oral dosing showed good agreement for all of the dose levels in the reported normal adult population groups. The predicted pharmacokinetic parameters (AUC, C(max), and T(max)) were reasonably consistent (<1.3-fold error) with the observed values after single oral administration of doses ranging from of 5 to 20 mg using the refined WB-PBPK model. The simulated plasma profiles after multiple oral administration of bisoprolol in healthy adults and patient with renal impairment matched well with the observed profiles.

CONCLUSION

The WB-PBPK model successfully predicts the intravenous and oral pharmacokinetics of bisoprolol across multiple dose levels in diverse normal adult human populations and patients with renal insufficiency.

Use of physiologically based pharmacokinetic modeling for assessment of drug-drug interactions

Interactions between co-administered medicines can reduce efficacy or lead to adverse effects. Understanding and managing such interactions is essential in bringing safe and effective medicines to the market. Ideally, interaction potential should be recognized early and minimized in compounds that reach late stages of drug development. Physiologically based pharmacokinetic models combine knowledge of physiological factors with compound-specific properties to simulate how a drug behaves in the human body. These software tools are increasingly used during drug discovery and development and, when integrating relevant in vitro data, can simulate drug interaction potential. This article provides some background and presents illustrative examples. Physiologically based models are an integral tool in the discovery and development of drugs, and can significantly aid our understanding and prediction of drug interactions.

Utility of drug depletion-time profiles in isolated hepatocytes for accessing hepatic uptake clearance: identifying rate-limiting steps and role of passive processes

Drug depletion-time profiles in isolated hepatocytes, as well as microsomes, have become a standard method of assessing hepatic metabolic clearance in vitro. There is a previously described adaptation of the depletion approach to allow determination of hepatic uptake by transporters in addition to metabolism (Drug Metab Dispos 35:859-865, 2007). Dual incubations are performed where one set of incubations undergo conventional methodology, whereas for the second set, cells and media are separated for determination of drug loss from the media. The utility of this dual incubation approach has been assessed using eight drugs (atorvastatin, clarithromycin, erythromycin, fexofenadine, pitavastatin, repaglinide, rosuvastatin, and saquinavir) with a range of active uptake, passive permeability, cell binding, and metabolic characteristics. Four of these compounds (fexofenadine, rosuvastatin, pitavastatin, and atorvastatin) show a biphasic time profile when assessing drug loss from media indicative of hepatic uptake before elimination within the hepatocyte, which is distinct from the time profile in a conventional incubation, and show higher clearances. The four other compounds (clarithromycin, saquinavir, erythromycin, and repaglinide) show identical depletion-time profiles (and clearances) in both sets of incubations. Whether or not the biphasic nature (and higher clearance) is evident, indicating transporter activity for a particular drug, appears to be dependent on its passive permeability. Using the parameter K(pu) to reflect the relative importance of hepatic transporters versus passive diffusion, a value of 10 was identified as a cutoff for whether the biphasic nature was evident; those compounds in excess of 10 show this characteristic clearly. There appears to be no relationship between the presence of the biphasic nature and any other parameter, including cellular binding, extent of metabolism, or the magnitude of active uptake.

Membrane transporters in drug development

Membrane transporters have wide, but specific tissue distributions. They can impact on multiple endogenous and xenobiotic processes. Knowledge and awareness within the pharmaceutical industry of their impact on drug absorption, distribution, metabolism and elimination (ADME) and drug safety is growing rapidly. Clinically important transporter-mediated drug-drug interactions (DDIs) have been observed. Up to nine diverse transporters are implicated in the DDIs of a number of widely prescribed drugs, posing a significant challenge to the pharmaceutical industry. There is a complex interplay between multiple transporters and/or enzymes in the ADME and pharmacogenomics of drugs. Integrating these different mechanisms to understand their relative contributions to ADME is a key challenge. Many different factors complicate the study of membrane transporters in drug development. These include a lack of specific substrates and inhibitors, non-standard in vitro tools, and competing/complementary mechanisms (e.g. passive permeability and metabolism). Discovering and contextualizing the contribution of membrane transporters to drug toxicity is a significant new challenge. Drug interactions with key membrane transporters are routinely assessed for central nervous system (CNS) drug discovery therapies, but are not generally considered across the wider drug discovery. But, there is interest in utilizing membrane transporters as drug delivery agents. Computational modeling approaches, notably physiology-based/pharmacokinetic (PB/PK) modeling are increasingly applied to transporter interactions, and permit integration of multiple ADME mechanisms. Because of the range of tissues and transporters of interest, robust transporter, in vitro to in vivo, scaling factors are required. Empirical factors have been applied, but absolute protein quantitation will probably be required.

The emerging role of transport systems in liver function tests

Liver function tests are of critical importance for the management of patients with severe or terminal liver disease. They are also used as prognostic tools for planning liver resections. In recent years many transport systems have been identified that also transport substances employed in liver function tests. Such substances include endogenous bilirubin or exogenously administered indocyanine green, agents for magnetic resonance imaging, agents for single photon emission computed tomography or agents for breath tests. The increasing functional and molecular information on the respective transport systems should improve the management and as a result the outcome of patients scheduled for liver surgery or transplantation. To achieve the latter goal, clinical studies that assess individual patients' liver function over the course of their disease with liver function tests are needed to firmly establish and validate recently introduced and novel liver function markers.

The evolution of the OATP hepatic uptake transport protein family in DMPK sciences: from obscure liver transporters to key determinants of hepatobiliary clearance

Over the last two decades the impact on drug pharmacokinetics of the organic anion transporting polypeptides (OATPs: OATP-1B1, 1B3 and 2B1), expressed on the sinusoidal membrane of the hepatocyte, has been increasingly recognized. OATP-mediated uptake into the hepatocyte coupled with subsequent excretion into bile via efflux proteins, such as MRP2, is often referred to as hepatobiliary excretion. OATP transporter proteins can impact some drugs in several ways including pharmacokinetic variability, pharmacodynamic response and drug-drug interactions (DDIs). The impact of transporter mediated hepatic clearance is illustrated with case examples, from the literature and also from the Pfizer portfolio. The currently available in vitro techniques to study the hepatic transporter proteins involved in the hepatobiliary clearance of drugs are reviewed herein along with recent advances in using these in vitro data to predict the human clearance of compounds recognized by hepatic uptake transporters.

Physiologically-based pharmacokinetics in drug development and regulatory science

The application of physiologically-based pharmacokinetic (PBPK) modeling is coming of age in drug development and regulation, reflecting significant advances over the past 10 years in the predictability of key pharmacokinetic (PK) parameters from human in vitro data and in the availability of dedicated software platforms and associated databases. Specific advances and contemporary challenges with respect to predicting the processes of drug clearance, distribution, and absorption are reviewed, together with the ability to anticipate the quantitative extent of PK-based drug-drug interactions and the impact of age, genetics, disease, and formulation. The value of this capability in selecting and designing appropriate clinical studies, its implications for resource-sparing techniques, and a more holistic view of the application of PK across the preclinical/clinical divide are considered. Finally, some attention is given to the positioning of PBPK within the drug development and approval paradigm and its future application in truly personalized medicine.

A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs

This article outlines general strategies for the management and evaluation of pharmacokinetic drug-drug interactions (DDIs) resulting from perturbation of clearance of investigational anticancer drug candidates by concomitantly administered agents in a drug development setting, with a focus on drug candidates that cannot be evaluated in first-in-human studies in healthy subjects. A risk level classification is proposed, based on quantitative integration of knowledge derived from preclinical drug-metabolism studies evaluating the projected percentage contribution [f(i)(%)] of individual molecular determinants (e.g. cytochrome P450 isoenzymes) to the overall human clearance of the investigational agent. The following classification is proposed with respect to susceptibility to DDIs with metabolic inhibitors: a projected maximum DDI expected to result in a ≤1.33-fold increase in exposure, representing a low level of risk; a projected maximum DDI expected to result in a >1.33-fold but <2-fold increase in exposure, representing a moderate level of risk; and a projected maximum DDI expected to result in a ≥2-fold increase in exposure, representing a potentially high level of risk. For DDIs with metabolic inducers, the following operational classification is proposed, based on the sum of the percentage contributions of enzymes that are inducible via a common mechanism to the overall clearance of the investigational drug: <<25%, representing a low level of risk; <50%, representing a moderate level of risk; and ≥50%, representing a potentially high level of risk. To ensure patient safety and to minimize bias in determination of the recommended phase II dose (RP2D), it is recommended that strong and moderate inhibitors and inducers of the major contributing enzyme are excluded in phase I dose-escalation studies of high-risk compounds, whereas exclusion of strong inhibitors and inducers of the contributing enzyme(s) is recommended as being sufficient for moderate-risk compounds. For drugs that will be investigated in diseases such as glioblastoma, where there may be relatively frequent use of enzyme-inducing antiepileptic agents (EIAEDs), a separate dose-escalation study in this subpopulation is recommended to define the RP2D. For compounds in the high-risk category, if genetic deficiencies in the activity of the major drug-metabolizing enzyme are known, it is recommended that poor metabolizers be studied separately to define the RP2D for this subpopulation. Whereas concomitant medication exclusion criteria that are utilized in the phase I dose-escalation studies will probably also need to be maintained for high-risk compounds in phase II studies unless the results of a clinical DDI study indicate the absence of a clinically relevant interaction, these exclusion criteria can potentially be relaxed beyond phase I for moderate-risk compounds, if supported by the nature of clinical toxicities and the understanding of the therapeutic index in phase I. Adequately designed clinical DDI studies will not only inform potential relaxation of concomitant medication exclusion criteria in later-phase studies but, importantly, will also inform the development of pharmacokinetically derived dose-modification guidelines for use in clinical practice when coupled with adequate safety monitoring, as illustrated in the prescribing guidance for many recently approved oncology therapeutics.

Lack of a primary physicochemical determinant in the direct transport of drugs to the brain after nasal administration in rats: potential involvement of transporters in the pathway

The objectives of this study were to evaluate the relative contribution of the direct pathway in overall brain transport for 17 model drugs with different physicochemical properties after nasal administrations and to identify factors that govern the fraction of the dose transported to the brain via the direct pathway (F(a, direct)). When the model drugs were nasally administered to rats, 5 of the 17 model drugs were delivered to a significant extent to the brain via the direct pathway. Multiple linear regression analyses showed that the correlation between various physicochemical properties and F(a, direct) was not statistically significant, indicative of a lack of primary physicochemical determinants in the direct transport pathway. Transporters such as rOAT3 and rOCT2 were expressed at significant levels in rat olfactory epithelia, and uptakes of standard substrates were significantly decreased in HEK293 cells expressing rOAT3 and rOCT2 in the presence of the five model drugs that were delivered to appreciable extents to the brain via the direct pathway. Therefore, these observations indicate that carrier-mediated transport may play a role in the brain delivery of drugs from the nose via the direct transport pathway.

Membrane transporters in drug development

Membrane transporters can be major determinants of the pharmacokinetic, safety and efficacy profiles of drugs. This presents several key questions for drug development, including which transporters are clinically important in drug absorption and disposition, and which in vitro methods are suitable for studying drug interactions with these transporters. In addition, what criteria should trigger follow-up clinical studies, and which clinical studies should be conducted if needed. In this article, we provide the recommendations of the International Transporter Consortium on these issues, and present decision trees that are intended to help guide clinical studies on the currently recognized most important drug transporter interactions. The recommendations are generally intended to support clinical development and filing of a new drug application. Overall, it is advised that the timing of transporter investigations should be driven by efficacy, safety and clinical trial enrolment questions (for example, exclusion and inclusion criteria), as well as a need for further understanding of the absorption, distribution, metabolism and excretion properties of the drug molecule, and information required for drug labelling.