In situ evaluation of the impact of metformin or verapamil coadministration with vildagliptin on its regional absorption from the rabbit's intestine.

This research aims to identify regional differences in vildagliptin absorption across the intestinal membrane. Furthermore, it was to investigate the effect of verapamil or metformin on vildagliptin absorptive clearance. The study utilized an in situ rabbit intestinal perfusion technique to determine vildagliptin oral absorption from duodenum, jejunum, ileum, and ascending colon. This was conducted both with and without perfusion of metformin or verapamil. The findings revealed that the vildagliptin absorptive clearance per unit length varied by site and was in the order as follows: ileum < jejunum < duodenum < ascending colon, implying that P-gp is significant in the reduction of vildagliptin absorption. Also, the arrangement cannot reverse intestinal P-gp, but the observations suggest that P-gp is significant in reducing vildagliptin absorption. Verapamil co-perfusion significantly increased the vildagliptin absorptive clearance by 2.4 and 3.2 fold through the jejunum and ileum, respectively. Metformin co-administration showed a non-significant decrease in vildagliptin absorptive clearance through all tested segments. Vildagliptin absorption was site-dependent and may be related to the intestinal P-glycoprotein content. This may aid in understanding the important elements that influence vildagliptin absorption, besides drug-drug interactions that can occur in type 2 diabetic patients taking vildagliptin in conjunction with other drugs that can modify the P-glycoprotein level.

Targeting host metabolism by inhibition of acetyl-Coenzyme A carboxylase reduces flavivirus infection in mouse models.

Flaviviruses are (re)-emerging RNA viruses strictly dependent on lipid metabolism for infection. In the search for host targeting antivirals, we explored the effect of pharmacological modulation of fatty acid metabolism during flavivirus infection. Considering the central role of acetyl-Coenzyme A carboxylase (ACC) on fatty acid metabolism, we analyzed the effect of three small-molecule ACC inhibitors (PF-05175157, PF-05206574, and PF-06256254) on the infection of medically relevant flaviviruses, namely West Nile virus (WNV), dengue virus, and Zika virus. Treatment with these compounds inhibited the multiplication of the three viruses in cultured cells. PF-05175157 induced a reduction of the viral load in serum and kidney in WNV-infected mice, unveiling its therapeutic potential for the treatment of chronic kidney disease associated with persistent WNV infection. This study constitutes a proof of concept of the reliability of ACC inhibitors to become viable antiviral candidates. These results support the repositioning of metabolic inhibitors as broad-spectrum antivirals.

Navigating Transporter Sciences in Pharmacokinetics Characterization Using the Extended Clearance Classification System.

Membrane transporters play an important role in the absorption, distribution, clearance, and elimination of drugs. Supported by the pharmacokinetics data in human, several transporters including organic anion transporting polypeptide (OATP)1B1, OATP1B3, organic anion transporter (OAT)1, OAT3, organic cation transporter (OCT)2, multidrug and toxin extrusion (MATE) proteins, P-glycoprotein and breast cancer resistance protein are suggested to be of clinical relevance. An early understanding of the transporter role in drug disposition and clearance allows reliable prediction/evaluation of pharmacokinetics and changes due to drug-drug interactions (DDIs) or genetic polymorphisms. We recently proposed an extended clearance classification system (ECCS) based on simple drug properties (i.e., ionization, permeability, and molecular weight) to predict the predominant clearance mechanism. According to this framework, systemic clearance of class 1B and 3B drugs is likely determined by the OATP-mediated hepatic uptake. Class 3A and 4 drugs, and certain class 3B drugs, are predominantly cleared by renal, wherein, OAT1, OAT3, OCT2, and MATE proteins could contribute to their active renal secretion. Intestinal efflux and uptake transporters largely influence the oral pharmacokinetics of class 3A, 3B, and 4 drugs. We discuss the paradigm of applying the ECCS framework in mapping the role of clinically relevant drug transporters in early discovery and development; thereby implementing the right strategy to allow optimization of drug exposure and evaluation of clinical risk due to DDIs and pharmacogenomics.

2-Aminopyridine-Based Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4) Inhibitors: Assessment of Mechanism-Based Safety.

Studies have linked the serine-threonine kinase MAP4K4 to the regulation of a number of biological processes and/or diseases, including diabetes, cancer, inflammation, and angiogenesis. With a majority of the members of our lead series (e.g., 1) suffering from time-dependent inhibition (TDI) of CYP3A4, we sought design avenues that would eliminate this risk. One such approach arose from the observation that carboxylic acid-based intermediates employed in our discovery efforts retained high MAP4K4 inhibitory potency and were devoid of the TDI risk. The medicinal chemistry effort that led to the discovery of this central nervous system-impaired inhibitor together with its preclinical safety profile is described.

A Study on Pharmacokinetics of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects.

Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging.

Molecular properties associated with transporter-mediated drug disposition.

Membrane transporters play a key role in the absorption, distribution, clearance, elimination, and transport of drugs. Understanding the drug properties and structure activity relationships (SAR) for affinity to membrane transporters is critical to optimize clearance and pharmacokinetics during drug design. To facilitate the early identification of clearance mechanism, a framework named the extended clearance classification system (ECCS) was recently introduced. Using in vitro and physicochemical properties that are readily available in early drug discovery, ECCS has been successfully applied to identify major clearance mechanism and to implicate the role of membrane transporters in determining pharmacokinetics. While the crystal structures for most of the drug transporters are currently not available, ligand-based modeling approaches that use information obtained from the structure and molecular properties of the ligands have been applied to associate the drug-related properties and transporter-mediated disposition. The approach allows prospective prediction of transporter both substrate and/or inhibitor affinity and build quantitative structure-activity relationship (QSAR) to enable early optimization of pharmacokinetics, tissue distribution and drug-drug interaction risk. Drug design applications can be further improved through uncovering transporter protein crystal structure and generation of quality data to refine and develop viable predictive models.

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

PURPOSE: To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions. METHODS: A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability. RESULTS: Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters. CONCLUSIONS: ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

Transporter-Enzyme Interplay: Deconvoluting Effects of Hepatic Transporters and Enzymes on Drug Disposition Using Static and Dynamic Mechanistic Models.

A large body of evidence suggests hepatic uptake transporters, organic anion-transporting polypeptides (OATPs), are of high clinical relevance in determining the pharmacokinetics of substrate drugs, based on which recent regulatory guidances to industry recommend appropriate assessment of investigational drugs for the potential drug interactions. We recently proposed an extended clearance classification system (ECCS) framework in which the systemic clearance of class 1B and 3B drugs is likely determined by hepatic uptake. The ECCS framework therefore predicts the possibility of drug-drug interactions (DDIs) involving OATPs and the effects of genetic variants of SLCO1B1 early in the discovery and facilitates decision making in the candidate selection and progression. Although OATP-mediated uptake is often the rate-determining process in the hepatic clearance of substrate drugs, metabolic and/or biliary components also contribute to the overall hepatic disposition and, more importantly, to liver exposure. Clinical evidence suggests that alteration in biliary efflux transport or metabolic enzymes associated with genetic polymorphism leads to change in the pharmacodynamic response of statins, for which the pharmacological target resides in the liver. Perpetrator drugs may show inhibitory and/or induction effects on transporters and enzymes simultaneously. It is therefore important to adopt models that frame these multiple processes in a mechanistic sense for quantitative DDI predictions and to deconvolute the effects of individual processes on the plasma and hepatic exposure. In vitro data-informed mechanistic static and physiologically based pharmacokinetic models are proven useful in rationalizing and predicting transporter-mediated DDIs and the complex DDIs involving transporter-enzyme interplay.

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS).

Early prediction of clearance mechanisms allows for the rapid progression of drug discovery and development programs, and facilitates risk assessment of the pharmacokinetic variability associated with drug interactions and pharmacogenomics. Here we propose a scientific framework--Extended Clearance Classification System (ECCS)--which can be used to predict the predominant clearance mechanism (rate-determining process) based on physicochemical properties and passive membrane permeability. Compounds are classified as: Class 1A--metabolism as primary systemic clearance mechanism (high permeability acids/zwitterions with molecular weight (MW) ≤400 Da), Class 1B--transporter-mediated hepatic uptake as primary systemic clearance mechanism (high permeability acids/zwitterions with MW >400 Da), Class 2--metabolism as primary clearance mechanism (high permeability bases/neutrals), Class 3A--renal clearance (low permeability acids/zwitterions with MW ≤400 Da), Class 3B--transporter mediated hepatic uptake or renal clearance (low permeability acids/zwitterions with MW >400 Da), and Class 4--renal clearance (low permeability bases/neutrals). The performance of the ECCS framework was validated using 307 compounds with single clearance mechanism contributing to ≥70% of systemic clearance. The apparent permeability across clonal cell line of Madin - Darby canine kidney cells, selected for low endogenous efflux transporter expression, with a cut-off of 5 × 10(-6) cm/s was used for permeability classification, and the ionization (at pH7) was assigned based on calculated pKa. The proposed scheme correctly predicted the rate-determining clearance mechanism to be either metabolism, hepatic uptake or renal for ~92% of total compounds. We discuss the general characteristics of each ECCS class, as well as compare and contrast the framework with the biopharmaceutics classification system (BCS) and the biopharmaceutics drug disposition classification system (BDDCS). Collectively, the ECCS framework is valuable in early prediction of clearance mechanism and can aid in choosing the right preclinical tool kit and strategy for optimizing drug exposure and evaluating clinical risk of pharmacokinetic variability caused by drug interactions and pharmacogenomics.

Strategies for skeletal muscle targeting in drug discovery.

The targeting of drugs to skeletal muscle is an emerging area of research. Driven by the need for new therapies to treat a range of muscle-associated diseases, these strategies aim to provide improved drug exposure at the site of action in skeletal muscle with reduced concentration in other tissues where unwanted side effects could occur. By interacting with muscle-specific cell surface recognition elements, both tissue localization and selective uptake into skeletal muscle cells can be achieved. The design of molecules that are substrates for muscle uptake transporters can provide concentration in m uscle tissue. For example, drug conjugates with carnitine can provide improved muscle uptake via OCTN2 transport. Binding to muscle surface recognition elements followed by endocytosis can allow even large molecules such as antibodies to enter muscle cells. Monoclonal antibody 3E10 demonstrated selective uptake into skeletal muscle in vivo. Hybrid adeno-associated viral vectors have recently shown promise for high skeletal muscle selectivity in gene transfer applications. Delivery technology methods, including electroporation of DNA plasmids, have also been investigated for selective muscle uptake. This review discusses challenges and opportunities for skeletal muscle targeting, highlighting specific examples and areas in need of additional research.

Intestinal targeting of drugs: rational design approaches and challenges.

Targeting drugs to the gastrointestinal tract has been and continues to be an active area of research. Gut-targeting is an effective means of increasing the local concentration of active substance at the desired site of action while minimizing concentrations elsewhere in the body that could lead to unwanted side-effects. Several approaches to intestinal targeting exist. Physicochemical property manipulation can drive molecules to large, polar, low absorption space or alternatively to lipophilic, high clearance space in order to minimize systemic exposure. Design of compounds that are substrates for transporters within the gastrointestinal tract, either uptake or efflux, or at the hepato-biliary interface, may help to increase intestinal concentration. Prodrug strategies have been shown to be effective particularly for colon targeting, and several different technology formulation approaches are currently being researched. This review provides examples of various approaches to intestinal targeting, and discusses challenges and areas in need of future scientific advances.

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

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

Mechanistic modeling to predict the transporter- and enzyme-mediated drug-drug interactions of repaglinide.

PURPOSE: Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide. METHODS: In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-ß-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data. RESULTS: In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-ß-glucuronide. CONCLUSIONS: This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

Model-based approaches to predict drug-drug interactions associated with hepatic uptake transporters: preclinical, clinical and beyond.

INTRODUCTION: Membrane transporters have been recognized to play a key role in determining the absorption, distribution and elimination processes of drugs. The organic anion-transporting polypeptide (OATP)1B1 and OATP1B3 isoforms are selectively expressed in the human liver and are known to cause significant drug-drug interactions (DDIs), as observed with an increasing number of drugs. It is evident that DDIs involving hepatic transporters are capable of altering systemic, as well as tissue-specific, exposure of drug substrates resulting in marked differences in drug safety and/or efficacy. It is therefore essential to quantitatively predict such interactions early in the drug development to mitigate clinical risks. AREAS COVERED: The role of hepatic uptake transporters in drug disposition and clinical DDIs has been reviewed with an emphasis on the current state of the models applicable for quantitative predictions. The readers will also gain insight into the in vitro experimental tools available to characterize transport kinetics, while appreciating the knowledge gaps in the in vitro-in vivo extrapolation (IVIVE), which warrant further investigation. EXPERT OPINION: Static and dynamic models can be convincingly applied to quantitatively predict drug interactions, early in drug discovery, to mitigate clinical risks as well as to avoid unnecessary clinical studies. Compared to basic models, which focus on individual processes, mechanistic models provide the ability to assess DDI potential for compounds with systemic disposition determined by both transporters and metabolic enzymes. However, complexities in the experimental tools and an apparent disconnect in the IVIVE of transport kinetics have limited the physiologically based pharmacokinetic modeling strategies. Emerging data on the expression of transporter proteins and tissue drug concentrations are expected to help bridge these gaps. In addition, detailed characterization of substrate kinetics can facilitate building comprehensive mechanistic models.

Renal transporters in drug disposition, drug-drug interactions, and nephrotoxicity.

This unit describes in detail the in vitro methods for measuring the interaction of new chemical entities (NCEs) with human renal transporters (hOAT1, hOAT2, and hOCT2) as both a substrate and inhibitor. Renal transporter substrate assays help in the identification of renal secretion mechanisms and assessment of the potential renal drug-drug interactions (DDIs) for NCE as a target, as well as to predict its renal clearance in humans. Human renal transporter (hOAT1, hOAT2, and hOCT2) inhibition assays characterize the inhibition potency of NCE and predict the potential for renal DDIs as a perpetrator with xenobiotics and drugs that are mainly renally cleared. In addition, such inhibition assays enable a better assessment of the potential for renal transporter-mediated nephrotoxicity and pathology. Therefore, renal transporter substrate and inhibition assays are pivotal in drug discovery and development for renally cleared drugs and those that are co-administered with marketed compounds mainly eliminated via the kidney.

Physicochemical property space of hepatobiliary transport and computational models for predicting rat biliary excretion.

Biliary excretion (BE) is a major elimination pathway, and its prediction is particularly important for optimization of systemic and/or target-site exposure of new molecular entities. The objective is to characterize the physicochemical space associated with hepatobiliary transport and rat BE and to develop in silico models. BE of 123 in-house compounds was obtained using the bile-duct cannulated rat model. Human and rat hepatic uptake transporters (hOATP1B1, hOATP1B3, hOATP2B1, and rOatp1b2) substrates (n = 183) were identified using transfected cells. Furthermore, the datasets were extended by adding BE of 163 compounds and 97 organic anion transporting polypeptide (OATP) substrates from the literature. Approximately 60% of compounds showing percentage of BE (%BE) ≥ 10 are anions, with mean BE of anions (36%) more than 3-fold higher than that of nonacids (11%). Compounds with %BE ≥ 10 are found to have high molecular mass, large polar surface area, more rotatable bonds, and high H-bond count, whereas the lipophilicity and passive membrane permeability are lower compared with compounds with %BE < 10. According to statistical analysis and principal component analysis, hOATPs and rOatp1b2 substrates showed physicochemical characteristics that were similar to those of the %BE ≥ 10 dataset. We further build categorical in silico models to predict rat BE, and the models (gradient boosting machine and scoring function) developed showed 80% predictability in identifying the rat BE bins (%BE ≥ 10 or < 10). In conclusion, the significant overlap of the property space of OATP substrates and rat BE suggests a predominant role of sinusoidal uptake transporters in biliary elimination. Categorical in silico models to predict rat BE were developed, and successful predictions were achieved.

pH-Dependent solubility and permeability criteria for provisional biopharmaceutics classification (BCS and BDDCS) in early drug discovery.

The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin-Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥ 5 × 10(-6) cm/s, the accuracy of predicting Fa of ≥ 0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 µg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified pH-dependent permeability and solubility criteria that can be used to assign provisional biopharmaceutics class at early stage of the drug discovery process. Additionally, such a classification system will enable discovery scientists to assess the potential limiting factors to oral absorption, as well as help predict the drug disposition mechanisms and potential drug-drug interactions.

In vitro evaluation of hepatic transporter-mediated clinical drug-drug interactions: hepatocyte model optimization and retrospective investigation.

To assess the feasibility of using sandwich-cultured human hepatocytes (SCHHs) as a model to characterize transport kinetics for in vivo pharmacokinetic prediction, the expression of organic anion-transporting polypeptide (OATP) proteins in SCHHs, along with biliary efflux transporters, was confirmed quantitatively by liquid chromatography-tandem mass spectrometry. Rifamycin SV (Rif SV), which was shown to completely block the function of OATP transporters, was selected as an inhibitor to assess the initial rates of active uptake. The optimized SCHH model was applied in a retrospective investigation of compounds with known clinically significant OATP-mediated uptake and was applied further to explore drug-drug interactions (DDIs). Greater than 50% inhibition of active uptake by Rif SV was found to be associated with clinically significant OATP-mediated DDIs. We propose that the in vitro active uptake value therefore could serve as a cutoff for class 3 and 4 compounds of the Biopharmaceutics Drug Disposition Classification System, which could be integrated into the International Transporter Consortium decision tree recommendations to trigger clinical evaluations for potential DDI risks. Furthermore, the kinetics of in vitro hepatobiliary transport obtained from SCHHs, along with protein expression scaling factors, offer an opportunity to predict complex in vivo processes using mathematical models, such as physiologically based pharmacokinetics models.

Differential modulation of cytochrome P450 activity and the effect of 1-aminobenzotriazole on hepatic transport in sandwich-cultured human hepatocytes.

Sandwich-cultured human hepatocytes (SCHH) have been widely used for in vitro assessments of biliary clearance. However, the modulation of metabolism enzymes has not been fully evaluated in this system. The present study was therefore undertaken to determine the activity of cytochrome P450 (P450) 1A2, 2C8, 2C9, 2C19, 2D6, and 3A and to evaluate the impact of 1-aminobenzotriazole (ABT) on hepatic uptake and biliary excretion in SCHH. The SCHH maintained integrity and viability as determined by lactate dehydrogenase release and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium assays conducted over the culture period. Although all assessed P450 activity decreased in day 2 SCHH, the extent of the decrease and the subsequent rebound in activity varied across the different isoforms. Day 5 CYP1A2 activity was approximately 2.5-fold higher than day 1 activity, whereas the CYP3A and CYP2C9 activities were 90 and 60% of the day 1 levels, respectively. In contrast, the initial CYP2C8, CYP2C19, and CYP2D6 activity losses did not rebound over the 5-day culture period. Furthermore, ABT was not found to have an effect, whether directly or indirectly as a P450 inactivator, with respect to the hepatic transport of rosuvastatin, atrovastatin, and midazolam in SCHH. Taken together, these results suggest that the SCHH model is a reliable tool to characterize hepatic uptake and biliary excretion. Due to the differential modulation of P450 activity, SCHH may not be considered a suitable tool for metabolic stability assessments with compounds predominantly cleared by certain P450 enzymes.

Development of a new permeability assay using low-efflux MDCKII cells.

Permeability is an important property of drug candidates. The Madin-Darby canine kidney cell line (MDCK) permeability assay is widely used and the primary concern of using MDCK cells is the presence of endogenous transporters of nonhuman origin. The canine P-glycoprotein (Pgp) can interfere with permeability and transporter studies, leading to less reliable data. A new cell line, MDCKII-LE (low efflux), has been developed by selecting a subpopulation of low-efflux cells from MDCKII-WT using an iterative fluorescence-activated cell sorting technique with calcein-AM as a Pgp and efflux substrate. MDCKII-LE cells are a subpopulation of MDCKII cells with over 200-fold lower canine Pgp mRNA level and fivefold lower protein level than MDCKII-WT. MDCKII-LE cells showed less functional efflux activity than MDCKII-WT based on efflux ratios. Notably, MDCKII-MDR1 showed about 1.5-fold decreased expression of endogenous canine Pgp, suggesting that using the net flux ratio might not completely cancel out the background endogenous transporter activities. MDCKII-LE cells offer clear advantages over the MDCKII-WT by providing less efflux transporter background signals and minimizing interference from canine Pgp. The MDCKII-LE apparent permeability values well differentiates compounds from high to medium/low human intestinal absorption and can be used for Biopharmaceutical Classification System. The MDCKII-LE permeability assay (4-in-1 cassette dosing) is high throughput with good precision, reproducibility, robustness, and cost-effective.