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

In silico modeling and simulation of organ-on-a-chip systems to support data analysis and a priori experimental design

Organ-on-a-chip (OoC) systems are a promising new class of in vitro devices that can combine various tissues, cultured in different compartments, linked by media flow. The properties of these novel in vitro systems linked to increased physiological relevance of culture conditions may lead to more in vivo-relevant cell phenotypes, enabling better in vitro pharmacology and toxicology assessment. Improved cell activities combined with longer lasting cultures offer opportunities to improve the characterization of absorption, distribution, metabolism, and excretion (ADME) processes, potentially leading to more accurate prediction of human pharmacokinetics (PKs). The inclusion of barrier tissue elements and metabolically competent tissue types results in complex concentration-time profiles (in vitro PK) for test drugs and their metabolites that require appropriate mathematical modeling of in vitro data for parameter estimation. In particular, modeling is critical to estimate in vitro ADME parameters when multiple different tissues are combined in a single device. Therefore, sophisticated in silico data analysis and a priori experimental design are highly recommended for OoC experiments in a manner not needed with standard ADME screening. The design of the experiment should be optimized based on an investigation of the structural characteristics of the in vitro system, the ADME features of the test compound and any available knowledge of cell phenotypes. This tutorial aims to provide such a modeling framework to inform experimental design and refine parameter estimation in a Gut-Liver OoC (the most studied multi-organ systems to predict the oral drug PKs) to improve translatability of data generated in such complex cellular systems.

Exploration and application of a liver-on-a-chip device in combination with modelling and simulation for quantitative drug metabolism studies

Microphysiological systems (MPS) are complex and more physiologically realistic cellular in vitro tools that aim to provide more relevant human in vitro data for quantitative prediction of clinical pharmacokinetics while also reducing the need for animal testing. The PhysioMimix liver-on-a-chip integrates medium flow with hepatocyte culture and has the potential to be adopted for in vitro studies investigating the hepatic disposition characteristics of drug candidates. The current study focusses on liver-on-a-chip system exploration for multiple drug metabolism applications. Characterization of cytochrome P450 (CYP), UDP-glucuronosyl transferase (UGT) and aldehyde oxidase (AO) activities was performed using 15 drugs and in vitro to in vivo extrapolation (IVIVE) was assessed for 12 of them. Next, the utility of the liver-on-a-chip for estimation of the fraction metabolized (f_m) via specific biotransformation pathways of quinidine and diclofenac was established. Finally, the metabolite identification opportunities were also explored using efavirenz as an example drug with complex primary and secondary metabolism involving a combination of CYP, UGT and sulfotransferase enzymes. A key aspect of these investigations was the application of mathematical modelling for improved parameter calculation. Such approaches will be required for quantitative assessment of metabolism and/or transporter processes in systems where medium flow and system compartments result in non-homogeneous drug concentrations. In particular, modelling was used to explore the effect of evaporation from the medium and it was found that the intrinsic clearance (CL_int) might be underestimated by up to 40% for low clearance compounds if evaporation is not accounted for. Modelling of liver-on-a-chip in vitro data also enhanced the approach to f_m estimation allowing objective assessment of metabolism models of different complexity. The resultant diclofenac f_m,UGT of 0.64 was highly comparable with values reported previously in the literature. The current study demonstrates the integration of mathematical modelling with experimental liver-on-a-chip studies and illustrates how this approach supports generation of high quality of data from complex in vitro cellular systems.

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.

Mass Spectrometry of Human Transporters

Transporters are key to understanding how an individual will respond to a particular dose of a drug. Two patients with similar systemic concentrations may have quite different local concentrations of a drug at the required site. The transporter profile of any individual depends upon a variety of genetic and environmental factors, including genotype, age, and diet status. Robust models (virtual patients) are therefore required and these models are data hungry. Necessary data include quantitative transporter profiles at the relevant organ. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) is currently the most powerful method available for obtaining this information. Challenges include sourcing the tissue, isolating the hydrophobic membrane-embedded transporter proteins, preparing the samples for MS (including proteolytic digestion), choosing appropriate quantification methodology, and optimizing the LC-MS/MS conditions. Great progress has been made with all of these, especially within the last few years, and is discussed here.

Simultaneous Assessment of Clearance, Metabolism, Induction, and Drug-Drug Interaction Potential Using a Long-Term In Vitro Liver Model for a Novel Hepatitis B Virus Inhibitor

Long-term in vitro liver models are now widely explored for human hepatic metabolic clearance prediction, enzyme phenotyping, cross-species metabolism, comparison of low clearance drugs, and induction studies. Here, we present studies using a long-term liver model, which show how metabolism and active transport, drug-drug interactions, and enzyme induction in healthy and diseased states, such as hepatitis B virus (HBV) infection, may be assessed in a single test system to enable effective data integration for physiologically based pharmacokinetic (PBPK) modeling. The approach is exemplified in the case of (3S)-4-[[(4R)-4-(2-Chloro-4-fluorophenyl)-5-methoxycarbonyl-2-thiazol-2-yl-1,4-dihydropyrimidin-6-yl]methyl]morpholine-3-carboxylic acid RO6889678, a novel inhibitor of HBV with a complex absorption, distribution, metabolism, and excretion (ADME) profile. RO6889678 showed an intracellular enrichment of 78-fold in hepatocytes, with an apparent intrinsic clearance of 5.2 µl/min per mg protein and uptake and biliary clearances of 2.6 and 1.6 µl/min per mg protein, respectively. When apparent intrinsic clearance was incorporated into a PBPK model, the simulated oral human profiles were in good agreement with observed data at low doses but were underestimated at high doses due to unexpected overproportional increases in exposure with dose. In addition, the induction potential of RO6889678 on cytochrome P450 (P450) enzymes and transporters at steady state was assessed and cotreatment with ritonavir revealed a complex drug-drug interaction with concurrent P450 inhibition and moderate UDP-glucuronosyltransferase induction. Furthermore, we report on the first evaluation of in vitro pharmacokinetics studies using HBV-infected HepatoPac cocultures. Thus, long-term liver models have great potential as translational research tools exploring pharmacokinetics of novel drugs in vitro in health and disease.

Integrated Gut and Liver Microphysiological Systems for Quantitative In Vitro Pharmacokinetic Studies

Investigation of the pharmacokinetics (PK) of a compound is of significant importance during the early stages of drug development, and therefore several in vitro systems are routinely employed for this purpose. However, the need for more physiologically realistic in vitro models has recently fueled the emerging field of tissue-engineered 3D cultures, also referred to as organs-on-chips, or microphysiological systems (MPSs). We have developed a novel fluidic platform that interconnects multiple MPSs, allowing PK studies in multi-organ in vitro systems along with the collection of high-content quantitative data. This platform was employed here to integrate a gut and a liver MPS together in continuous communication, and investigate simultaneously different PK processes taking place after oral drug administration in humans (e.g., intestinal permeability, hepatic metabolism). Measurement of tissue-specific phenotypic metrics indicated that gut and liver MPSs can be fluidically coupled with circulating common medium without compromising their functionality. The PK of diclofenac and hydrocortisone was investigated under different experimental perturbations, and results illustrate the robustness of this integrated system for quantitative PK studies. Mechanistic model-based analysis of the obtained data allowed the derivation of the intrinsic parameters (e.g., permeability, metabolic clearance) associated with the PK processes taking place in each MPS. Although these processes were not substantially affected by the gut-liver interaction, our results indicate that inter-MPS communication can have a modulating effect (hepatic metabolism upregulation). We envision that our integrative approach, which combines multi-cellular tissue models, multi-MPS platforms, and quantitative mechanistic modeling, will have broad applicability in pre-clinical drug development.

Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance

PURPOSE

Develop a minimal mechanistic model based on in vitro-in vivo extrapolation (IVIVE) principles to predict extent of passive tubular reabsorption. Assess the ability of the model developed to predict extent of passive tubular reabsorption (Freab) and renal excretion clearance (CLR) from in vitro permeability data and tubular physiological parameters.

METHODS

Model system parameters were informed by physiological data collated following extensive literature analysis. A database of clinical CLR was collated for 157 drugs. A subset of 45 drugs was selected for model validation; for those, Caco-2 permeability (Papp) data were measured under pH6.5-7.4 gradient conditions and used to predict Freab and subsequently CLR. An empirical calibration approach was proposed to account for the effect of inter-assay/laboratory variation in Papp on the IVIVE of Freab.

RESULTS

The 5-compartmental model accounted for regional differences in tubular surface area and flow rates and successfully predicted the extent of tubular reabsorption of 45 drugs for which filtration and reabsorption were contributing to renal excretion. Subsequently, predicted CLR was within 3-fold of the observed values for 87% of drugs in this dataset, with an overall gmfe of 1.96. Consideration of the empirical calibration method improved overall prediction of CLR (gmfe=1.73 for 34 drugs in the internal validation dataset), in particular for basic drugs and drugs with low extent of tubular reabsorption.

CONCLUSIONS

The novel 5-compartment model represents an important addition to the IVIVE toolbox for physiologically-based prediction of renal tubular reabsorption and CLR. Physiological basis of the model proposed allows its application in future mechanistic kidney models in preclinical species and human.

Quantitative Assessment of Population Variability in Hepatic Drug Metabolism Using a Perfused Three-Dimensional Human Liver Microphysiological System

In this work, we first describe the population variability in hepatic drug metabolism using cryopreserved hepatocytes from five different donors cultured in a perfused three-dimensional human liver microphysiological system, and then show how the resulting data can be integrated with a modeling and simulation framework to accomplish in vitro–in vivo translation. For each donor, metabolic depletion profiles of six compounds (phenacetin, diclofenac, lidocaine, ibuprofen, propranolol, and prednisolone) were measured, along with metabolite formation, mRNA levels of 90 metabolism-related genes, and markers of functional viability [lactate dehydrogenase (LDH) release, albumin, and urea production]. Drug depletion data were analyzed with mixed-effects modeling. Substantial interdonor variability was observed with respect to gene expression levels, drug metabolism, and other measured hepatocyte functions. Specifically, interdonor variability in intrinsic metabolic clearance ranged from 24.1% for phenacetin to 66.8% for propranolol (expressed as coefficient of variation). Albumin, urea, LDH, and cytochrome P450 mRNA levels were identified as significant predictors of in vitro metabolic clearance. Predicted clearance values from the liver microphysiological system were correlated with the observed in vivo values. A population physiologically based pharmacokinetic model was developed for lidocaine to illustrate the translation of the in vitro output to the observed pharmacokinetic variability in vivo. Stochastic simulations with this model successfully predicted the observed clinical concentration-time profiles and the associated population variability. This is the first study of population variability in drug metabolism in the context of a microphysiological system and has important implications for the use of these systems during the drug development process.

Challenges and Opportunities with Non-CYP Enzymes Aldehyde Oxidase, Carboxylesterase, and UDP-Glucuronosyltransferase: Focus on Reaction Phenotyping and Prediction of Human Clearance

Over the years, significant progress has been made in reducing metabolic instability due to cytochrome P450-mediated oxidation. High-throughput metabolic stability screening has enabled the advancement of compounds with little to no oxidative metabolism. Furthermore, high lipophilicity and low aqueous solubility of presently pursued chemotypes reduces the probability of renal excretion. As such, these low microsomal turnover compounds are often substrates for non-CYP-mediated metabolism. UGTs, esterases, and aldehyde oxidase are major enzymes involved in catalyzing such metabolism. Hepatocytes provide an excellent tool to identify such pathways including elucidation of major metabolites. To predict human PK parameters for P450-mediated metabolism, in vitro-in vivo extrapolation using hepatic microsomes, hepatocytes, and intestinal microsomes has been actively investigated. However, such methods have not been sufficiently evaluated for non-P450 enzymes. In addition to the involvement of the liver, extrahepatic enzymes (intestine, kidney, lung) are also likely to contribute to these pathways. While there has been considerable progress in predicting metabolic pathways and clearance primarily mediated by the liver, progress in characterizing extrahepatic metabolism and prediction of clearance has been slow. Well-characterized in vitro systems or in vivo animal models to assess drug-drug interaction potential and intersubject variability due to polymorphism are not available. Here we focus on the utility of appropriate in vitro studies to characterize non-CYP-mediated metabolism and to understand the enzymes involved followed by pharmacokinetic studies in the appropriately characterized surrogate species. The review will highlight progress made in establishing in vitro-in vivo correlation, predicting human clearance and avoiding costly clinical failures when non-CYP-mediated metabolic pathways are predominant.

Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part I: In Vitro Systems and Physiological Data

The programme for the 2015 AAPS Annual Meeting and Exhibition (Orlando, FL; 25-29 October 2015) included a sunrise session presenting an overview of the state-of-the-art tools for in vitro-in vivo extrapolation (IVIVE) and mechanistic prediction of renal drug disposition. These concepts are based on approaches developed for prediction of hepatic clearance, with consideration of scaling factors physiologically relevant to kidney and the unique and complex structural organisation of this organ. Physiologically relevant kidney models require a number of parameters for mechanistic description of processes, supported by quantitative information on renal physiology (system parameters) and in vitro/in silico drug-related data. This review expands upon the themes raised during the session and highlights the importance of high quality in vitro drug data generated in appropriate experimental setup and robust system-related information for successful IVIVE of renal drug disposition. The different in vitro systems available for studying renal drug metabolism and transport are summarised and recent developments involving state-of-the-art technologies highlighted. Current gaps and uncertainties associated with system parameters related to human kidney for the development of physiologically based pharmacokinetic (PBPK) model and quantitative prediction of renal drug disposition, excretion, and/or metabolism are identified.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.

Meta-analysis of expression of hepatic organic anion-transporting polypeptide (OATP) transporters in cellular systems relative to human liver tissue

Organic anion-transporting polypeptide (OATP)1B1, OATP1B3, and OATP2B1 transporters play an important role in hepatic drug disposition. Recently, an increasing number of studies have reported proteomic expression data for OATP transporters. However, systematic analysis and understanding of the actual differences in OATP expression between liver tissue and commonly used cellular systems is lacking. In the current study, meta-analysis was performed to assess the protein expression of OATP transporters reported in hepatocytes relative to liver tissue and to identify any potential correlations in transporter expression levels in the same individual. OATP1B1 was identified as the most abundant uptake transporter at 5.9 ± 8.3, 5.8 ± 3.3, and 4.2 ± 1.7 fmol/μg protein in liver tissue, sandwich-cultured human hepatocytes (SCHH), and cryopreserved suspended hepatocytes, respectively. The rank order in average expression in liver tissue and cellular systems was OATP1B1 > OATP1B3 ≈ OATP2B1. Abundance levels of the OATP transporters investigated were not significantly different between liver and cellular systems, with the exception of OATP2B1 expression in SCHH relative to liver tissue. Analysis of OATP1B1, OATP1B3, and OATP2B1 liver expression data in the same individuals (n = 86) identified weak (OATP1B1-OATP2B1) to moderately (OATP1B3-OATP2B1) significant correlations. A significant weak correlation was noted between OATP1B1 abundance and age of human donors, whereas expression of the OATPs investigated was independent of sex. Implications of the current analysis on the in vitro-in vivo extrapolation of transporter-mediated drug disposition using physiologically based pharmacokinetic models are discussed.