Evaluation of hepatic clearance prediction using in vitro data: emphasis on fraction unbound in plasma and drug ionisation using a database of 107 drugs

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Design of Dual EP2/EP4 Antagonists through Scaffold Merging of Selective Inhibitors

Prostaglandin E2 (PGE2) plays a key role in various stages of cancer. PGE2 signals through the EP2 and the EP4 receptors, promoting tumorigenesis, metastasis, and/or immune suppression. Dual inhibition of both the EP2 and the EP4 receptors has the potential to counteract the effect of PGE2 and to result in antitumor efficacy. We herein disclose for the first time the structure of dual EP2/EP4 antagonists. By merging the scaffolds of EP2 selective and EP4 selective inhibitors, we generated a new chemical series of compounds blocking both receptors with comparable potency. In vitro and in vivo profiling suggests that the newly identified compounds are promising lead structures for further development into dual EP2/EP4 antagonists for use in cancer therapy.

The Comparison of Machine Learning and Mechanistic In Vitro-In Vivo Extrapolation Models for the Prediction of Human Intrinsic Clearance

Accurate prediction of human pharmacokinetics (PK) remains one of the key objectives of drug metabolism and PK (DMPK) scientists in drug discovery projects. This is typically performed by using in vitro-in vivo extrapolation (IVIVE) based on mechanistic PK models. In recent years, machine learning (ML), with its ability to harness patterns from previous outcomes to predict future events, has gained increased popularity in application to absorption, distribution, metabolism, and excretion (ADME) sciences. This study compares the performance of various ML and mechanistic models for the prediction of human IV clearance for a large (645) set of diverse compounds with literature human IV PK data, as well as measured relevant in vitro end points. ML models were built using multiple approaches for the descriptors: (1) calculated physical properties and structural descriptors based on chemical structure alone (classical QSAR/QSPR); (2) in vitro measured inputs only with no structure-based descriptors (ML IVIVE); and (3) in silico ML IVIVE using in silico model predictions for the in vitro inputs. For the mechanistic models, well-stirred and parallel-tube liver models were considered with and without the use of empirical scaling factors and with and without renal clearance. The best ML model for the prediction of in vivo human intrinsic clearance (CLint) was an in vitro ML IVIVE model using only six in vitro inputs with an average absolute fold error (AAFE) of 2.5. The best mechanistic model used the parallel-tube liver model, with empirical scaling factors resulting in an AAFE of 2.8. The corresponding mechanistic model with full in silico inputs achieved an AAFE of 3.3. These relative performances of the models were confirmed with the prediction of 16 Pfizer drug candidates that were not part of the original data set. Results show that ML IVIVE models are comparable to or superior to their best mechanistic counterparts. We also show that ML IVIVE models can be used to derive insights into factors for the improvement of mechanistic PK prediction.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Characterization of intravenous pharmacokinetics in Göttingen minipig and clearance prediction using established in vitro to in vivo extrapolation methodologies

1. The use of the Göttingen minipig as an animal model for drug safety testing and prediction of human pharmacokinetics (PK) continues to gain momentum in pharmaceutical research and development. The aim of this study was to evaluate in vitro to in vivo extrapolation (IVIVE) methodologies for prediction of hepatic, metabolic clearance (CL_hep,met) in Göttingen minipig, using a comprehensive set of compounds.2. In vivo clearance was determined in Göttingen minipig by intravenous cassette dosing and hepatocyte intrinsic clearance, plasma protein binding and non-specific incubation binding were determined in vitro. Prediction of CL_hep,met was performed by IVIVE using conventional and adapted formats of the well-stirred liver model.3. The best prediction of in vivo CL_hep,met from scaled in vitro kinetic data was achieved using an empirical correction factor based on a 'regression offset' of the IVIV relationship.4. In summary, these results expand the in vitro and in vivo PK knowledge in Göttingen minipig. We show regression corrected IVIVE provides superior prediction of in vivo CL_hep,met in minipig offering a practical, unified scaling approach to address systematic under-predictions. Finally, we propose a reference set for researchers to establish their own 'lab-specific' regression correction for IVIVE in minipig.

Midazolam as a Probe for Heterotropic Drug-Drug Interactions Mediated by CYP3A4

Human cytochrome P450 CYP3A4 is involved in the processing of more than 35% of current pharmaceuticals and therefore is responsible for multiple drug-drug interactions (DDI). In order to develop a method for the detection and prediction of the possible involvement of new drug candidates in CYP3A4-mediated DDI, we evaluated the application of midazolam (MDZ) as a probe substrate. MDZ is hydroxylated by CYP3A4 in two positions: 1-hydroxy MDZ formed at lower substrate concentrations, and up to 35% of 4-hydroxy MDZ at high concentrations. The ratio of the formation rates of these two products (the site of metabolism ratio, SOM) was used as a measure of allosteric heterotropic interactions caused by effector molecules using CYP3A4 incorporated in lipid nanodiscs. The extent of the changes in the SOM in the presence of effectors is determined by chemical structure and is concentration-dependent. MD simulations of CYP3A4 in the lipid bilayer suggest that experimental results can be explained by the movement of the F-F' loop and concomitant changes in the shape and volume of the substrate-binding pocket. As a result of PGS binding at the allosteric site, several residues directly contacting MDZ move away from the substrate molecule, enabling the repositioning of the latter for minor product formation.

Application of empirical scalars to enable early prediction of human hepatic clearance using IVIVE in drug discovery: an evaluation of 173 drugs

The utilization of in vitro data to predict drug pharmacokinetics (PK) in vivo has been a consistent practice in early drug discovery for decades. However, its success is hampered by mispredictions attributed to uncharacterized biological phenomena/experimental artifacts. Predicted drug clearance (CL) from experimental data (i.e. hepatocyte intrinsic clearance: CLint, fraction unbound in plasma: fu,p) is often systematically underpredicted using the well-stirred model (WSM). The objective of this study was to evaluate using empirical scalars in the WSM to correct for CL mispredictions. Drugs (N=28) were used to generate numerical scalars on CLint (α), and fu,p (β) to minimize the error (AAFE) for CL predictions. These scalars were validated using an additional dataset (N=28 drugs) and applied to a non-redundant AstraZeneca (AZ) dataset available in the literature (N=117 drugs) for a total of 173 compounds. CL predictions using the WSM were improved for most compounds using an α value of 3.66 (~64%<2-fold) compared to no scaling (~46%<2-fold). Similarly, using a β value of 0.55 or combination of α and β scalars (values of 1.74 and 0.66, respectively) resulted in a similar improvement in predictions (~64%<2-fold and ~65%<2-fold, respectively). For highly bound compounds (fu,p{less than or equal to}0.01), AAFE was substantially reduced across all scaling methods. Using the β scalar alone or a combination of α and β appeared optimal; and produce larger magnitude corrections for highly-bound compounds. Some drugs are still disproportionally mispredicted, however the improvements in prediction error and simplicity of applying these scalars suggests its utility for early-stage CL predictions. Significance Statement In early drug discovery, prediction of human clearance using in vitro experimental data plays an essential role in triaging compounds prior to in vivo studies. These predictions have been systematically underestimated. Here we introduce empirical scalars calibrated on the extent of plasma protein binding that appear to improve clearance prediction across multiple datasets. This approach can be used in early phases of drug discovery prior to the availability of pre-clinical data for early quantitative predictions of human clearance.

Evaluation of the Success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) Modeling Predictions to Inform Early Drug Discovery

Minimizing in vitro and in vivo testing in early drug discovery with the use of physiologically based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the potential to reduce discovery cycle times and animal experimentation. However, the prediction success of such an approach has not been shown for a larger and diverse set of compounds representative of a lead optimization pipeline. In this study, the prediction success of the oral (PO) and intravenous (IV) pharmacokinetics (PK) parameters in rats was assessed using a “bottom-up” approach, combining in vitro and ML inputs with a PBPK model. More than 240 compounds for which all of the necessary inputs and PK data were available were used for this assessment. Different clearance scaling approaches were assessed, using hepatocyte intrinsic clearance and protein binding as inputs. In addition, a novel high-throughput PBPK (HT-PBPK) approach was evaluated to assess the scalability of PBPK predictions for a larger number of compounds in drug discovery. The results showed that bottom-up PBPK modeling was able to predict the rat IV and PO PK parameters for the majority of compounds within a 2- to 3-fold error range, using both direct scaling and dilution methods for clearance predictions. The use of only ML-predicted inputs from the structure did not perform well when using in vitro inputs, likely due to clearance miss predictions. The HT-PBPK approach produced comparable results to the full PBPK modeling approach but reduced the simulation time from hours to seconds. In conclusion, a bottom-up PBPK and HT-PBPK approach can successfully predict the PK parameters and guide early discovery by informing compound prioritization, provided that good in vitro assays are in place for key parameters such as clearance.

In Vitro - in Vivo Extrapolation of Hepatic Clearance in Preclinical Species

Accurate prediction of human clearance is of critical importance in drug discovery. In this study, in vitro - in vivo extrapolation (IVIVE) of hepatic clearance was established using large sets of compounds for four preclinical species (mouse, rat, dog, and non-human primate) to enable better understanding of clearance mechanisms and human translation. In vitro intrinsic clearances were obtained using pooled liver microsomes (LMs) or hepatocytes (HEPs) and scaled to hepatic clearance using the parallel-tube and well-stirred models. Subsequently, IVIVE scaling factors (SFs) were derived to best predict in vivo clearance. The SFs for extended clearance classification system (ECCS) class 2/4 compounds, involving metabolic clearance, were generally small (≤ 2.6) using both LMs and HEPs with parallel-tube model, with the exception of the rodents (~ 2.4-4.6), suggesting in vitro reagents represent in vivo reasonably well. SFs for ECCS class 1A and 1B are generally higher than class 2/4 across the species, likely due to the contribution of transporter-mediated clearance that is under-represented with in vitro reagents. The parallel-tube model offered lower variability in clearance predictions over the well-stirred model. For compounds that likely demonstrate passive permeability-limited clearance in vitro, rat LM predicted in vivo clearance more accurately than HEP. This comprehensive analysis demonstrated reliable IVIVE can be achieved using LMs and HEPs. Evaluation of clearance IVIVE in preclinical species helps to better understand clearance mechanisms, establish more reliable IVIVE in human, and enhance our confidence in human clearance and PK prediction, while considering species differences in drug metabolizing enzymes and transporters.

Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

Organic Anion-Transporting Polypeptide 1B1/1B3-Mediated Hepatic Uptake Determines the Pharmacokinetics of Large Lipophilic Acids: In Vitro-In Vivo Evaluation in Cynomolgus Monkey

It is generally presumed that uptake transport mechanisms are of limited significance in hepatic clearance for lipophilic or high passive-permeability drugs. In this study, we evaluated the mechanistic role of the hepato-selective organic anion-transporting polypeptides (OATPs) 1B1/1B3 in the pharmacokinetics of compounds representing large lipophilic acid space. Intravenous pharmacokinetics of 16 compounds with molecular mass ∼400-730 Da, logP ∼3.5-8, and acid pKa <6 were obtained in cynomolgus monkey after dosing without and with a single-dose rifampicin-OATP1B1/1B3 probe inhibitor. Rifampicin (30 mg/kg oral) significantly (P < 0.05) reduced monkey clearance and/or steady-state volume of distribution (VDss) for 15 of 16 acids evaluated. Additionally, clearance of danoprevir was reduced by about 35%, although statistical significance was not reached. A significant linear relationship was noted between the clearance ratio (i.e., ratio of control to treatment groups) and VDss ratio, suggesting hepatic uptake contributes to the systemic clearance and distribution simultaneously. In vitro transport studies using primary monkey and human hepatocytes showed uptake inhibition by rifampicin (100 µM) for compounds with logP ≤6.5 but not for the very lipophilic acids (logP > 6.5), which generally showed high nonspecific binding in hepatocyte incubations. In vitro uptake clearance and fraction transported by OATP1B1/1B3 (f_t,OATP1B) were found to be similar in monkey and human hepatocytes. Finally, for compounds with logP ≤6.5, good agreement was noted between in vitro f_t,OATP1B and clearance ratio (as well as VDss ratio) in cynomolgus monkey. In conclusion, this study provides mechanistic evidence for the pivotal role of OATP1B-mediated hepatic uptake in the pharmacokinetics across a wide, large lipophilic acid space. SIGNIFICANCE STATEMENT: This study provides mechanistic insight into the pharmacokinetics of a broad range of large lipophilic acids. Organic anion-transporting polypeptides 1B1/1B3-mediated hepatic uptake is of key importance in the pharmacokinetics and drug-drug interactions of almost all drugs and new molecular entities in this space. Diligent in vitro and in vivo transport characterization is needed to avoid the false negatives often noted because of general limitations in the in vitro assays while handling compounds with such physicochemical attributes.

Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways

Extensive studies have been conducted to predict in vivo metabolic clearance from in vitro human liver metabolism parameters (i.e., in vitro-in vivo extrapolation (IVIVE)) with little success. Here, deriving IVIVE from first principles, we show that the product of fraction unbound in the blood and the predicted in vivo intrinsic clearance determined from hepatocyte or microsomal incubations is the lower boundary condition for in vivo hepatic clearance and the prerequisite for IVIVE predictions to be valid, regardless of extraction ratio. For 60-80% of drugs evaluated here, this product is markedly less than the in vivo measured clearance, a result that violates the lower boundary of the predictive relationship. This can only be explained by (a) suboptimal in vitro metabolic stability assay conditions, (b) significant error in the assumption that in vitro intrinsic clearance determinations will predict in vivo intrinsic clearance simply by scaling-up the amount of enzyme (in vitro incubation to in vivo liver), and/or (c) the methods of determining fraction unbound are incorrect. We further suggest that widely employed organ blood flow values underpredict the effective blood flow within the organ by approximately 2.5-fold, thus impacting IVIVE of high clearance compounds. We propose future pathways that should be investigated in terms of the relationship to experimentally measured clearance values, rather than model-dependent intrinsic clearance. IVIVE outcome can be improved by estimating the ratio of unbound drug concentration in the liver tissue to the liver plasma, examining the assumption of the free drug theory (i.e., there are no transporter effects at the blood cell membrane) and the finding that the upper limit of organ clearance may be greater than blood flow entering the organ.

Relevance of In Vitro Metabolism Models to PET Radiotracer Development: Prediction of In Vivo Clearance in Rats from Microsomal Stability Data

The prediction of in vivo clearance from in vitro metabolism models such as liver microsomes is an established procedure in drug discovery. The potentials and limitations of this approach have been extensively evaluated in the pharmaceutical sector; however, this is not the case for the field of positron emission tomography (PET) radiotracer development. The application of PET radiotracers and classical drugs differs greatly with regard to the amount of substance administered. In typical PET imaging sessions, subnanomolar quantities of the radiotracer are injected, resulting in body concentrations that cannot be readily simulated in analytical assays. This raises concerns regarding the predictability of radiotracer clearance from in vitro data. We assessed the accuracy of clearance prediction for three prototypical PET radiotracers developed for imaging the A₁ adenosine receptor (A₁AR). Using the half-life (t_1/2) approach and physiologically based scaling, in vivo clearance in the rat model was predicted from microsomal stability data. Actual clearance could be accurately predicted with an average fold error (AFE) of 0.78 and a root mean square error (RMSE) of 1.6. The observed slight underprediction (1.3-fold) is in accordance with the prediction accuracy reported for classical drugs. This result indicates that the prediction of radiotracer clearance is possible despite concentration differences of more than three orders of magnitude between in vitro and in vivo conditions. Consequently, in vitro metabolism models represent a valuable tool for PET radiotracer development.

Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling

Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the prediction of human PKs prior to the first-in-human clinical trials. In vitro-in vivo extrapolation and allometric scaling are the choice of method for projection to human situations. Although these methods are useful tools for the estimation of PK parameters, it is a challenge to apply these methods since underlying biochemical, mathematical, physiological, and background knowledge of PKs are required. In addition, it is difficult to select an appropriate methodology depending on the data available. Therefore, this review covers the principles of PK parameters pertaining to the clearance, volume of distribution, elimination half-life, absorption rate constant, and prediction method from the original idea to recently developed models in order to introduce optimal models for the prediction of PK parameters.

Meeting the Challenge of Predicting Hepatic Clearance of Compounds Slowly Metabolized by Cytochrome P450 Using a Novel Hepatocyte Model, HepatoPac

Generating accurate in vitro intrinsic clearance data is an important aspect of predicting in vivo human clearance. Primary hepatocytes in suspension are routinely used to predict in vivo clearance; however, incubation times have typically been limited to 4-6 hours, which is not long enough to accurately evaluate the metabolic stability of slowly metabolized compounds. HepatoPac is a micropatterened hepatocyte-fibroblast coculture system that can be used for continuous incubations of up to 7 days. This study evaluated the ability of human HepatoPac to predict the in vivo clearance (CL) of 17 commercially available compounds with low to intermediate clearance (<12 ml/min/kg). In vitro half-life for disappearance of each compound was converted to hepatic clearance using the well stirred model, with and without correction for plasma protein binding. Hepatic CL, using three individual donors, was accurately predicted for 11 of 17 compounds (59%; predicted clearance within 2-fold of observed human in vivo clearance values). The accuracy of prediction increased to 82% (14 of 17 compounds) with an acceptance criterion defined as within 3-fold. When considering only low clearance compounds (<5 ml/min per kg), which represented 10 of the 17 compounds, the accuracy of prediction was 70% within 2-fold and 100% within 3-fold. In addition, the turnover of three slowly metabolized compounds (alprazolam, meloxicam, and tolbutamide) in HepatoPac was directly compared with turnover in suspended hepatocytes. The turnover of alprazolam and tolbutamide was approximately 2-fold greater using HepatoPac compared with suspended hepatocytes, which was roughly in line with the extrapolated values (correcting for the longer incubation time and lower cell number with HepatoPac). HepatoPac, but not suspended hepatocytes, demonstrated significant turnover of meloxicam. These results demonstrate the utility of HepatoPac for prediction of in vivo hepatic clearance, particularly with low clearance compounds.

Quantitation of Lysosomal Trapping of Basic Lipophilic Compounds Using In Vitro Assays and In Silico Predictions Based on the Determination of the Full pH Profile of the Endo-/Lysosomal System in Rat Hepatocytes

Lysosomal sequestration may affect the pharmacokinetics, efficacy, and safety of new basic lipophilic drug candidates potentially impacting their intracellular concentrations and tissue distribution. It may also be involved in drug-drug interactions, drug resistance, and phospholipidosis. However, currently there are no assays to evaluate the lysosomotropic behavior of compounds in a setting fully meeting the needs of drug discovery. We have, therefore, integrated a set of methods to reliably rank order, quantify, and calculate the extent of lysosomal sequestration in rat hepatocytes. An indirect fluorescence-based assay monitors the displacement of the fluorescence probe LysoTracker Red by test compounds. Using a lysosomal-specific evaluation algorithm allows one to generate IC₅₀ values at lower than previously reported concentrations. The concentration range directly agrees with the concentration dependency of the lysosomal drug content itself directly quantified by liquid chromatography-tandem mass spectrometry and thus permits a quantitative link between the indirect and the direct trapping assay. Furthermore, we have determined the full pH profile and corresponding volume fractions of the endo-/lysosomal system in plated rat hepatocytes, enabling a more accurate in silico prediction of the extent of lysosomal trapping based only on pK _a values as input, allowing early predictions even prior to chemical synthesis. The concentration dependency-i.e., the saturability of the trapping-can then be determined by the IC₅₀ values generated in vitro. Thereby, a more quantitative assessment of the susceptibility of basic lipophilic compounds for lysosomal trapping is possible.

An examination of protein binding and protein-facilitated uptake relating to in vitro-in vivo extrapolation

As explained by the free drug theory, the unbound fraction of drug has long been thought to drive the efficacy of a molecule. Thus, the fraction unbound term, or f_u, appears in equations for fundamental pharmacokinetic parameters such as clearance, and is used when attempting in vitro to in vivo extrapolation (IVIVE). In recent years though, it has been noted that IVIVE does not always yield accurate predictions, and that some highly protein bound ligands have more efficient uptake than can be explained by their unbound fractions. This review explores the evolution of f_u terms included when implementing IVIVE, the concept of protein-facilitated uptake, and the mechanisms that have been proposed to account for facilitated uptake.

Discovery of an Orally Bioavailable Inhibitor of Defective in Cullin Neddylation 1 (DCN1)-Mediated Cullin Neddylation

We previously reported the discovery, validation, and structure-activity relationships of a series of piperidinyl ureas that potently inhibit the DCN1-UBE2M interaction. We demonstrated that compound 7 inhibits both the DCN1-UBE2M protein-protein interaction and DCN1-mediated cullin neddylation in biochemical assays and reduces levels of steady-state cullin neddylation in a squamous carcinoma cell line harboring DCN1 amplification. Although compound 7 exhibits good solubility and permeability, it is rapidly metabolized in microsomal models (CL_int = 170 mL/min/kg). This work lays out the discovery of an orally bioavailable analogue, NAcM-OPT (67). Compound 67 retains the favorable biochemical and cellular activity of compound 7 but is significantly more stable both in vitro and in vivo. Compound 67 is orally bioavailable, well tolerated in mice, and currently used to study the effects of acute pharmacologic inhibition of the DCN1-UBE2M interaction on the NEDD8/CUL pathway.

Importance of the Unstirred Water Layer and Hepatocyte Membrane Integrity In Vitro for Quantification of Intrinsic Metabolic Clearance

Prediction of clearance-a vital component of drug discovery-remains in need of improvement and, in particular, requires more incisive assessment of mechanistic methodology in vitro, according to a number of recent reports. Although isolated hepatocytes have become an irreplaceable standard system for the measurement of intrinsic hepatic clearance mediated by active uptake transport and metabolism, the lack of prediction reliability appears to reflect a lack of methodological validation, especially for highly cleared drugs, as we have previously shown. Here, novel approaches were employed to explore fundamental experimental processes and associated potential limitations of in vitro predictions of clearance. Rat hepatocytes deemed nonviable by trypan blue staining showed undiminished metabolic activity for probe cytochrome P450 (P450) substrates midazolam and propranolol; supplementation with NADPH enhanced these activities. Extensive permeabilization of the plasma membrane using saponin showed either full or minimal P450 activity, depending on the presence or absence of 1 mM NADPH, respectively. The shaking of incubations facilitated P450 metabolic rates up to 5-fold greater than static incubation, depending on intrinsic clearance, indicating the critical influence of the unstirred water layer (UWL). Permeabilization allowed static incubation metabolic rates to approach those of shaking for intact cells, indicating an artificially induced breakdown of the UWL. Permeabilization combined with shaking allowed an increased metabolic rate for saquinavir, resolving the membrane permeability limitation for this drug. These findings advance the interpretation of the rate-limiting processes involved in intrinsic clearance measurements and could be critical for successful in vitro prediction.

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.

Prediction of cytochrome P450-mediated drug clearance in humans based on the measured activities of selected CYPs

Determining drug-metabolizing enzyme activities on an individual basis is an important component of personalized medicine, and cytochrome P450 enzymes (CYPs) play a principal role in hepatic drug metabolism. Herein, a simple method for predicting the major CYP-mediated drug clearance in vitro and in vivo is presented. Ten CYP-mediated drug metabolic activities in human liver microsomes (HLMs) from 105 normal liver samples were determined. The descriptive models for predicting the activities of these CYPs in HLMs were developed solely on the basis of the measured activities of a smaller number of more readily assayed CYPs. The descriptive models then were combined with the Conventional Bias Corrected in vitro–in vivo extrapolation method to extrapolate drug clearance in vivo. The V_max, K_m, and CL_int of six CYPs (CYP2A6, 2C8, 2D6, 2E1, and 3A4/5) could be predicted by measuring the activities of four CYPs (CYP1A2, 2B6, 2C9, and 2C19) in HLMs. Based on the predicted CL_int, the values of CYP2A6-, 2C8-, 2D6-, 2E1-, and 3A4/5-mediated drug clearance in vivo were extrapolated and found that the values for all five drugs were close to the observed clearance in vivo. The percentage of extrapolated values of clearance in vivo which fell within 2-fold of the observed clearance ranged from 75.2% to 98.1%. These findings suggest that measuring the activity of CYP1A2, 2B6, 2C9, and 2C19 allowed us to accurately predict CYP2A6-, 2C8-, 2D6-, 2E1-, and 3A4/5-mediated activities in vitro and in vivo and may possibly be helpful for the assessment of an individual’s drug metabolic profile.

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd.

Hepatic Clearance Predictions from In Vitro-In Vivo Extrapolation and the Biopharmaceutics Drug Disposition Classification System

Predicting in vivo pharmacokinetic parameters such as clearance from in vitro data is a crucial part of the drug-development process. There is a commonly cited trend that drugs that are highly protein-bound and are substrates for hepatic uptake transporters often yield the worst predictions. Given this information, 11 different data sets using human microsomes and hepatocytes were evaluated to search for trends in accuracy, extent of protein binding, and drug classification based on the Biopharmaceutics Drug Disposition Classification System (BDDCS), which makes predictions about transporter effects. As previously reported, both in vitro systems (microsomes and hepatocytes) gave a large number of inaccurate results, defined as predictions falling more than 2-fold outside of in vivo values. The weighted average of the percentage of inaccuracy was 66.5%. BDDCS class 2 drugs, which are subject to transporter effects in vivo unlike class 1 compounds, had a higher percentage of inaccurate predictions and often had slightly larger bias. However, since the weighted average of the percentage of inaccuracy was still high in both classes (81.9% for class 2 and 62.3% for class 1), it may be currently hard to use BDDCS class to predict potential accuracy. The results of this study emphasize the need for improved in vitro to in vivo extrapolation experimental methods, as using physiologically based scaling is still not accurate, and BDDCS cannot currently help predict accurate results.

Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models

OBJECTIVES

The aim of this study was (1) to determine how closely physiologically based pharmacokinetic (PBPK) models can predict oral bioavailability using a priori knowledge of drug-specific properties and (2) to examine the influence of the biopharmaceutics classification system class on the simulation success.

METHODS

Simcyp Simulator, GastroPlus^™ and GI-Sim were used. Compounds with published Biowaiver monographs (bisoprolol (BCS I), nifedipine (BCS II), cimetidine (BCS III), furosemide (BCS IV)) were selected to ensure availability of accurate and reproducible data for all required parameters. Simulation success was evaluated with the average fold error (AFE) and absolute average fold error (AAFE). Parameter sensitivity analysis (PSA) to selected parameters was performed.

KEY FINDINGS

Plasma concentration-time profiles after intravenous administration were forecast within an AAFE < 3. The addition of absorption processes resulted in more variability in the prediction of the plasma profiles, irrespective of biopharmaceutics classification system (BCS) class. The reliability of literature permeability data was identified as a key issue in the accuracy of predicting oral drug absorption.

CONCLUSION

For the four drugs studied, it appears that the forecasting accuracy of the PBPK models is related to the BCS class (BCS I > BCS II, BCS III > BCS IV). These results will need to be verified with additional drugs.

Development of a Novel Simplified PBPK Absorption Model to Explain the Higher Relative Bioavailability of the OROS® Formulation of Oxybutynin

A new minimal Segmented Transit and Absorption model (mSAT) model has been recently proposed and combined with intrinsic intestinal effective permeability (P _eff,int ) to predict the regional gastrointestinal (GI) absorption (f _abs ) of several drugs. Herein, this model was extended and applied for the prediction of oral bioavailability and pharmacokinetics of oxybutynin and its enantiomers to provide a mechanistic explanation of the higher relative bioavailability observed for oxybutynin's modified-release OROS® formulation compared to its immediate-release (IR) counterpart. The expansion of the model involved the incorporation of mechanistic equations for the prediction of release, transit, dissolution, permeation and first-pass metabolism. The predicted pharmacokinetics of oxybutynin enantiomers after oral administration for both the IR and OROS® formulations were in close agreement with the observed data. The predicted absolute bioavailability for the IR formulation was within 5% of the observed value, and the model adequately predicted the higher relative bioavailability observed for the OROS® formulation vs. the IR counterpart. From the model predictions, it can be noticed that the higher bioavailability observed for the OROS® formulation was mainly attributable to differences in the intestinal availability (F _G ) rather than due to a higher colonic f _abs , thus confirming previous hypotheses. The predicted f _abs was almost 70% lower for the OROS® formulation compared to the IR formulation, whereas the F _G was almost eightfold higher than in the IR formulation. These results provide further support to the hypothesis of an increased F _G as the main factor responsible for the higher bioavailability of oxybutynin's OROS® formulation vs. the IR.

Interspecies scaling of excretory amounts using allometry - retrospective analysis with rifapentine, aztreonam, carumonam, pefloxacin, miloxacin, trovafloxacin, doripenem, imipenem, cefozopran, ceftazidime, linezolid for urinary excretion and rifapentine, cabotegravir, and dolutegravir for fecal excretion

1. Interspecies allometry scaling for prediction of human excretory amounts in urine or feces was performed for numerous antibacterials. Antibacterials used for urinary scaling were: rifapentine, pefloxacin, trovafloxacin (Gr1/low; <10%); miloxacin, linezolid, PNU-142300 (Gr2/medium; 10-40%); aztreonam, carumonam, cefozopran, doripenem, imipenem, and ceftazidime (Gr3/high; >50%). Rifapentine, cabotegravir, and dolutegravir was used for fecal scaling (high; >50%). 2. The employment of allometry equation: Y = aW(b) enabled scaling of urine/fecal amounts from animal species. Corresponding predicted amounts were converted into % recovery by considering the respective human dose. Comparison of predicted/observed values enabled fold difference and error calculations (mean absolute error [MAE] and root mean square error [RMSE]). Comparisons were made for urinary/fecal data; and qualitative assessment was made amongst Gr1/Gr2/Gr3 for urine. 3. Average correlation coefficient for the allometry scaling was >0.995. Excretory amount predictions were largely within 0.75- to 1.5-fold differences. Average MAE and RMSE were within ±22% and 23%, respectively. Although robust predictions were achieved for higher urinary/fecal excretion (>50%), interspecies scaling was applicable for low/medium excretory drugs. 4. Based on the data, interspecies scaling of urine or fecal excretory amounts may be potentially used as a tool to understand the significance of either urinary or fecal routes of elimination in humans in early development.

Upcyte Human Hepatocytes: a Potent In Vitro Tool for the Prediction of Hepatic Clearance of Metabolically Stable Compounds

In vitro models based on primary human hepatocytes (PHH) have been advanced for clearance (CL) prediction of metabolically stable compounds, representing state-of-the-art assay systems for drug discovery and development. Yet, limited cell availability and large interindividual variability of metabolic profiles remain shortcomings of PHH. Upcyte human hepatocytes (UHH) represent a novel hepatic cell system derived from PHH, exhibiting proliferative capacity for approximately 35 population doublings. UHH from three donors were evaluated during culture for up to 18 days, investigating relative mRNA expression and in situ enzyme activity of cytochrome P450s (P450s), UDP-glucuronosyltransferases, and sulfotransferases. Furthermore, UHH were used for predicting hepatic CL of 21 marketed low to intermediate CL drugs. In a typical experiment, expansion from 3.9 × 10(6) up to 8.5 × 10(7) cells was achieved during subculture. When maintained at confluence, transcripts of major P450s were expressed at donor-specific levels with sustained activities for the majority of isoforms, showing generally low CYP1A2 and high CYP2B6 activity levels. For donor 151-03, CL prediction based on depletion experiments resulted in an average fold error of 2.0, and 80% of compounds being predicted within twofold to in vivo CL for a subset of 10 low CL drugs. UHH showed sustained and consistent activity of drug-metabolizing enzymes (DME), resulting in highly reproducible CL prediction performance. In conclusion, UHH show promising potential as alternative to PHH for standardized in vitro applications in discovery research based on their stable, hepatocyte-like DME phenotype and virtually unlimited cell availability.

Analysis of the impact of controlled release formulations on oral drug absorption, gut wall metabolism and relative bioavailability of CYP3A substrates using a physiologically-based pharmacokinetic model

Controlled release (CR) formulations are usually designed to achieve similar exposure (AUC) levels as the marketed immediate release (IR) formulation. However, the AUC is often lower following CR compared to IR formulations. There are a few exceptions when the CR formulations have shown higher AUC. This study investigated the impact of CR formulations on oral drug absorption and CYP3A4-mediated gut wall metabolism. A review of the current literature on relative bioavailability (Frel) between CR and IR formulations of CYP3A substrates was conducted. This was followed by a systematic analysis to assess the impact of the release characteristics and the drug-specific factors (including metabolism and permeability) on oral bioavailability employing a physiologically-based pharmacokinetic (PBPK) modelling and simulation approach. From the literature review, only three CYP3A4 substrates showed higher Frel when formulated as CR. Several scenarios were investigated using the PBPK approach; in most of them, the oral absorption of CR formulations was lower as compared to the IR formulations. However, for highly permeable compounds that were CYP3A4 substrates the reduction in absorption was compensated by an increase in the fraction that escapes from first pass metabolism in the gut wall (FG), where the magnitude was dependent on CYP3A4 affinity. The systematic simulations of various interplays between different parameters demonstrated that BCS class 1 highly-cleared CYP3A4 substrates can display up to 220% higher relative bioavailability when formulated as CR compared to IR, in agreement with the observed data collected from the literature. The results and methodology of this study can be employed during the formulation development process in order to optimize drug absorption, especially for CYP3A4 substrates.

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.

Meeting the challenge of predicting hepatic clearance of compounds slowly metabolized by cytochrome P450 using a novel hepatocyte model, HepatoPac

Generating accurate in vitro intrinsic clearance data is an important aspect of predicting in vivo human clearance. Primary hepatocytes in suspension are routinely used to predict in vivo clearance; however, incubation times have typically been limited to 4-6 hours, which is not long enough to accurately evaluate the metabolic stability of slowly metabolized compounds. HepatoPac is a micropatterened hepatocyte-fibroblast coculture system that can be used for continuous incubations of up to 7 days. This study evaluated the ability of human HepatoPac to predict the in vivo clearance (CL) of 17 commercially available compounds with low to intermediate clearance (<12 ml/min per kg). In vitro half-life for disappearance of each compound was converted to hepatic clearance using the well stirred model, with and without correction for plasma protein binding. Hepatic CL, using three individual donors, was accurately predicted for 10 of 17 compounds (59%; predicted clearance within 2-fold of observed human in vivo clearance values). The accuracy of prediction increased to 76% (13 of 17 compounds) with an acceptance criterion defined as within 3-fold. When considering only low clearance compounds (<5 ml/min per kg), which represented 10 of the 17 compounds, the accuracy of prediction was 60% within 2-fold and 90% within 3-fold. In addition, the turnover of three slowly metabolized compounds (alprazolam, meloxicam, and tolbutamide) in HepatoPac was directly compared with turnover in suspended hepatocytes. The turnover of alprazolam and tolbutamide was approximately 2-fold greater using HepatoPac compared with suspended hepatocytes, which was roughly in line with the extrapolated values (correcting for the longer incubation time and lower cell number with HepatoPac). HepatoPac, but not suspended hepatocytes, demonstrated significant turnover of meloxicam. These results demonstrate the utility of HepatoPac for prediction of in vivo hepatic clearance, particularly with low clearance compounds.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME

This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

An integrated pharmacokinetic and pharmacodynamic study of a new drug of abuse, methylone, a synthetic cathinone sold as "bath salts"

INTRODUCTION

Methylone (3,4-methylenedioxymethcathinone) is a new psychoactive substance and an active ingredient of "legal highs" or "bath salts". We studied the pharmacokinetics and locomotor activity of methylone in rats at doses equivalent to those used in humans.

MATERIAL AND METHODS

Methylone was administered to male Sprague-Dawley rats intravenously (10mg/kg) and orally (15 and 30 mg/kg). Plasma concentrations and metabolites were characterized by LC/MS and LC-MS/MS fragmentation patterns. Locomotor activity was monitored for 180-240 min.

RESULTS

Oral administration of methylone induced a dose-dependent increase in locomotor activity in rats. The plasma concentrations after i.v. administration were described by a two-compartment model with distribution and terminal elimination phases of α=1.95 h(-1) and β=0.72 h(-1). For oral administration, peak methylone concentrations were achieved between 0.5 and 1h and fitted to a flip-flop model. Absolute bioavailability was about 80% and the percentage of methylone protein binding was of 30%. A relationship between methylone brain levels and free plasma concentration yielded a ratio of 1.42 ± 0.06, indicating access to the central nervous system. We have identified four Phase I metabolites after oral administration. The major metabolic routes are N-demethylation, aliphatic hydroxylation and O-methylation of a demethylenate intermediate.

DISCUSSION

Pharmacokinetic and pharmacodynamic analysis of methylone showed a correlation between plasma concentrations and enhancement of the locomotor activity. A contribution of metabolites in the activity of methylone after oral administration is suggested. Present results will be helpful to understand the time course of the effects of this drug of abuse in humans.

Pharmacokinetics, pharmacodynamics and physiologically-based pharmacokinetic modelling of monoclonal antibodies

Development of monoclonal antibodies (mAbs) and their functional derivatives represents a growing segment of the development pipeline in the pharmaceutical industry. More than 25 mAbs and derivatives have been approved for a variety of therapeutic applications. In addition, around 500 mAbs and derivatives are currently in different stages of development. mAbs are considered to be large molecule therapeutics (in general, they are 2-3 orders of magnitude larger than small chemical molecule therapeutics), but they are not just big chemicals. These compounds demonstrate much more complex pharmacokinetic and pharmacodynamic behaviour than small molecules. Because of their large size and relatively poor membrane permeability and instability in the conditions of the gastrointestinal tract, parenteral administration is the most usual route of administration. The rate and extent of mAb distribution is very slow and depends on extravasation in tissue, distribution within the particular tissue, and degradation. Elimination primarily happens via catabolism to peptides and amino acids. Although not definitive, work has been published to define the human tissues mainly involved in the elimination of mAbs, and it seems that many cells throughout the body are involved. mAbs can be targeted against many soluble or membrane-bound targets, thus these compounds may act by a variety of mechanisms to achieve their pharmacological effect. mAbs targeting soluble antigen generally exhibit linear elimination, whereas those targeting membrane-bound antigen often exhibit non-linear elimination, mainly due to target-mediated drug disposition (TMDD). The high-affinity interaction of mAbs and their derivatives with the pharmacological target can often result in non-linear pharmacokinetics. Because of species differences (particularly due to differences in target affinity and abundance) in the pharmacokinetics and pharmacodynamics of mAbs, pharmacokinetic/pharmacodynamic modelling of mAbs has been used routinely to expedite the development of mAbs and their derivatives and has been utilized to help in the selection of appropriate dose regimens. Although modelling approaches have helped to explain variability in both pharmacokinetic and pharmacodynamic properties of these drugs, there is a clear need for more complex models to improve understanding of pharmacokinetic processes and pharmacodynamic interactions of mAbs with the immune system. There are different approaches applied to physiologically based pharmacokinetic (PBPK) modelling of mAbs and important differences between the models developed. Some key additional features that need to be accounted for in PBPK models of mAbs are neonatal Fc receptor (FcRn; an important salvage mechanism for antibodies) binding, TMDD and lymph flow. Several models have been described incorporating some or all of these features and the use of PBPK models are expected to expand over the next few years.

Lysosomal sequestration (trapping) of lipophilic amine (cationic amphiphilic) drugs in immortalized human hepatocytes (Fa2N-4 cells)

Lipophilic (logP > 1) and amphiphilic drugs (also known as cationic amphiphilic drugs) with ionizable amines (pKa > 6) can accumulate in lysosomes, a process known as lysosomal trapping. This process contributes to presystemic extraction by lysosome-rich organs (such as liver and lung), which, together with the binding of lipophilic amines to phospholipids, contributes to the large volume of distribution characteristic of numerous cardiovascular and central nervous system drugs. Accumulation of lipophilic amines in lysosomes has been implicated as a cause of phospholipidosis. Furthermore, elevated levels of lipophilic amines in lysosomes can lead to high organ-to-blood ratios of drugs that can be mistaken for active drug transport. In the present study, we describe an in vitro fluorescence-based method (using the lysosome-specific probe LysoTracker Red) to identify lysosomotropic agents in immortalized hepatocytes (Fa2N-4 cells). A diverse set of compounds with various physicochemical properties were tested, such as acids, bases, and zwitterions. In addition, the partitioning of the nonlysosomotropic atorvastatin (an anion) and the lysosomotropics propranolol and imipramine (cations) were quantified in Fa2N-4 cells in the presence or absence of various lysosomotropic or nonlysosomotropic agents and inhibitors of lysosomal sequestration (NH4Cl, nigericin, and monensin). Cellular partitioning of propranolol and imipramine was markedly reduced (by at least 40%) by NH4Cl, nigericin, or monensin. Lysosomotropic drugs also inhibited the partitioning of propranolol by at least 50%, with imipramine partitioning affected to a lesser degree. This study demonstrates the usefulness of immortalized hepatocytes (Fa2N-4 cells) for determining the lysosomal sequestration of lipophilic amines.

Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs

The purpose of this study was to perform a comparative analysis of various in vitro--in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs on the basis of intrinsic CL data determined in microsomes. Five IVIVE methods were evaluated: the "conventional and conventional bias-corrected methods" using the unbound fraction in plasma (fu(p) ), the "Berezhkovskiy method" in which the fu(p) is adjusted for drug ionization, the "Poulin et al. method" using the unbound fraction in liver (fu(liver) ), and the "direct scaling method," which does not consider any binding corrections. We investigated the effects of the following scenarios on the prediction of CL: the use of preclinical or human datasets, the extent of plasma protein binding, the magnitude of CL in vivo, and the extent of drug disposition based on biopharmaceutics drug disposition classification system (BDDCS) categorization. A large and diverse dataset of 139 compounds was collected, including those from the literature and in house from Genentech. The results of this study confirm that the Poulin et al. method is robust and showed the greatest accuracy as compared with the other IVIVE methods in the majority of prediction scenarios studied here. The difference across the prediction methods is most pronounced for (a) albumin-bound drugs, (b) highly bound drugs, and (c) low CL drugs. Predictions of CL showed relevant interspecies differences for BDDCS class 2 compounds; the direct scaling method showed the greatest predictivity for these compounds, particularly for a reduced dataset in rat that have unexpectedly high CL in vivo. This result is a reflection of the direct scaling method's natural tendency to overpredict the true metabolic CL. Overall, this study should facilitate the use of IVIVE correlation methods in physiologically based pharmacokinetics (PBPK) model.