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

Characterization and Applications of Permeabilized Hepatocytes in Drug Discovery

Hepatocytes are one of the most physiologically relevant in vitro liver systems for human translation of clearance and drug-drug interactions (DDI). However, the cell membranes of hepatocytes can limit the entry of certain compounds into the cells for metabolism and DDI. Passive permeability through hepatocytes can be different in vitro and in vivo, which complicates the human translation. Permeabilized hepatocytes offer a useful tool to probe mechanistic understanding of permeability-limited metabolism and DDI. Incubation with saponin of 0.01% at 0.5 million cells/mL and 0.05% at 5 million cells/mL for 5 min at 37°C completely permeabilized the plasma membrane of hepatocytes, while leaving the membranes of subcellular organelles intact. Permeabilized hepatocytes maintained similar enzymatic activity as intact unpermeabilized hepatocytes and can be stored at -80°C for at least 7 months. This approach reduces costs by preserving leftover hepatocytes. The relatively low levels of saponin in permeabilized hepatocytes had no significant impact on the enzymatic activity. As the cytosolic contents leak out from permeabilized hepatocytes, cofactors need to be added to enable metabolic reactions. Cytosolic enzymes will no longer be present if the media are removed after cells are permeabilized. Hence permeabilized hepatocytes with and without media removal may potentially enable reaction phenotyping of cytosolic enzymes. Although permeabilized hepatocytes work similarly as human liver microsomes and S9 fractions experimentally requiring addition of cofactors, they behave more like hepatocytes maintaining enzymatic activities for over 4 h. Permeabilized hepatocytes are a great addition to the drug metabolism toolbox to provide mechanistic insights.

Exploring the Boundaries for In Vitro-In Vivo Extrapolation: Use of Isolated Rat Hepatocytes in Co-culture and Impact of Albumin Binding Properties in the Prediction of Clearance of Various Drug Types

Prediction of hepatic clearance of drugs (via uptake or metabolism) from in vitro systems continues to be problematic, particularly when plasma protein binding is high. The following work explores simultaneous assessment of both clearance processes, focusing on a commercial hepatocyte-fibroblast co-culture system (HμREL) over a 24-hour period using six probe drugs (ranging in metabolic and transporter clearance and low-to-high plasma protein binding). A rat hepatocyte co-culture assay was established using drug depletion (measuring both medium and total concentrations) and cell uptake kinetic analysis, both in the presence and absence of plasma protein (1% bovine serum albumin). Secretion of endogenous albumin was monitored as a marker of viability, and this reached 0.004% in incubations (at a rate similar to in vivo synthesis). Binding to stromal cells was substantial and required appropriate correction factors. Drug concentration-time courses were analyzed both by conventional methods and a mechanistic cell model prior to in vivo extrapolation. Clearance assayed by drug depletion in conventional suspended rat hepatocytes provided a benchmark to evaluate co-culture value. Addition of albumin appeared to improve predictions for some compounds (where fraction unbound in the medium is less than 0.1); however, for high-binding drugs, albumin significantly limited quantification and thus predictions. Overall, these results highlight ongoing challenges concerning in vitro hepatocyte system complexity and limitations of practical expediency. Considering this, more reliable measurement of hepatically cleared compounds seems possible through judicious use of available hepatocyte systems, including co-culture systems, as described herein; this would include those compounds with low metabolic turnover but high active uptake clearance. SIGNIFICANCE STATEMENT: Co-culture systems offer a more advanced tool than standard hepatocytes, with the ability to be cultured for longer periods of time, yet their potential as an in vitro tool has not been extensively assessed. We evaluate the strengths and limitations of the HμREL system using six drugs representing various metabolic and transporter-mediated clearance pathways with various degrees of albumin binding. Studies in the presence/absence of albumin allow in vitro-in vivo extrapolation and a framework to maximize their utility.

The Disconnect in Intrinsic Clearance Determined in Human Hepatocytes and Liver Microsomes Results from Divergent Cytochrome P450 Activities

Candidate drugs may exhibit higher unbound intrinsic clearances (CLint,u) in human liver microsomes (HLMs) relative to human hepatocytes (HHs), posing a challenge as to which value is more predictive of in vivo clearance (CL). This work was aimed at better understanding the mechanism(s) underlying this 'HLM:HH disconnect' via examination of previous explanations, including passive permeability limited CL or cofactor exhaustion in hepatocytes. A series of structurally related, passively permeable (Papps > 5 × 10-6 cm/s), 5-azaquinazolines were studied in different liver fractions, and metabolic rates and routes were determined. A subset of these compounds demonstrated a significant HLM:HH (CLint,u ratio 2-26) disconnect. Compounds were metabolized via combinations of liver cytosol aldehyde oxidase (AO), microsomal cytochrome P450 (CYP) and flavin monooxygenase (FMO). For this series, the lack of concordance between CLint,u determined in HLM and HH contrasted with an excellent correlation of AO dependent CLint,u determined in human liver cytosol[Formula: see text], r2 = 0.95, P < 0.0001). The HLM:HH disconnect for both 5-azaquinazolines and midazolam was as a result of significantly higher CYP activity in HLM and lysed HH fortified with exogenous NADPH relative to intact HH. Moreover, for the 5-azaquinazolines, the maintenance of cytosolic AO and NADPH-dependent FMO activity in HH, relative to CYP, supports the conclusion that neither substrate permeability nor intracellular NADPH for hepatocytes were limiting CLint,u Further studies are required to identify the underlying cause of the lower CYP activities in HH relative to HLM and lysed hepatocytes in the presence of exogenous NADPH. SIGNIFICANCE STATEMENT: Candidate drugs may exhibit higher intrinsic clearance in human liver microsomes relative to human hepatocytes, posing a challenge as to which value is predictive of in vivo clearance. This work demonstrates that the difference in activity determined in liver fractions results from divergent cytochrome P450 but not aldehyde oxidase or flavin monooxygenase activity. This is inconsistent with explanations including substrate permeability limitations or cofactor exhaustion and should inform the focus of further studies to understand this cytochrome P450 specific disconnect phenomenon.

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.

Design considerations of benchtop fluid flow bioreactors for bio-engineered tissue equivalents in vitro

One of the major aims of bio-engineering tissue equivalents in vitro is to create physiologically relevant culture conditions to accurately recreate the cellular microenvironment. This often includes incorporation of factors such as the extracellular matrix, co-culture of multiple cell types and three-dimensional culture techniques. These advanced techniques can recapitulate some of the properties of tissue in vivo, however fluid flow is a key aspect that is often absent. Fluid flow can be introduced into cell and tissue culture using bioreactors, which are becoming increasingly common as we seek to produce increasingly accurate tissue models. Bespoke technology is continuously being developed to tailor systems for specific applications and to allow compatibility with a range of culture techniques. For effective perfusion of a tissue culture many parameters can be controlled, ranging from impacts of the fluid flow such as increased shear stress and mass transport, to potentially unwanted side effects such as temperature fluctuations. A thorough understanding of these properties and their implications on the culture model can aid with a more accurate interpretation of results. Improved and more complete characterisation of bioreactor properties will also lead to greater accuracy when reporting culture conditions in protocols, aiding experimental reproducibility, and allowing more precise comparison of results between different systems. In this review we provide an analysis of the different factors involved in the development of benchtop flow bioreactors and their potential biological impacts across a range of applications.

Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance

Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05–1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan.

Advancement of nanomedicines in chronic inflammatory disorders

Chronic diseases, as stated by the WHO, are a threat to human health which kill 3 out of every 5 people worldwide. Therapeutics for such illnesses can be developed using traditional medicine. However, it is not an easy path from natural products to Western pharmacological and pharmaceutical methods. For several decades, chronic inflammatory disorders, especially in Westernized countries, have increased incidence and prevalence. Several NSAIDs are used to decrease inflammation and pain; however, there are numerous negative consequences of these anti-inflammatory medications, whereas plant-based natural products have anti-inflammatory therapeutic benefits that have little or no adverse effects. Nanoparticles are a new type of drug delivery device that may be designed to provide excellent target selectivity for certain cells and tissues while also having a high drug loading capacity, resulting in better pharmacokinetics, pharmacodynamics (PKPD), and therapeutic bioavailability. The size and polarity of phytochemical compounds make it hard to pass the blood-brain barrier (BBB), blood-vessel endothelial lining, gastrointestinal tract and mucosa. In addition, the gastrointestinal system is enzymatically destroyed. Therefore, nanoparticles or nanocrystals might also be used for encapsulation or conjugation of these chemicals as a method to improve their organic effectiveness through their gastrointestinal stability, absorption rate and dispersion. The therapy of numerous inflammatory illnesses, including arthritis, gastritis, Nephritis, Hepatitis (Type A, B &C), ulcerative colitis, Alzheimer's disease, atherosclerosis, allergic responses (asthma, eczema) or autoimmune disorders, is characterised by nanoparticles. This review paper provides information on the numerous nanosystem described with their probable mechanism to treat chronic inflammatory diseases.

Advances in HBV infection and replication systems in vitro

Background

Hepatitis B virus (HBV) is a DNA virus belonging to the Hepadnaviridae family that has limited tissue and species specificity. Due to the persistence of HBV covalently closed circular DNA (cccDNA) in host cells after HBV infection, current antiviral drugs cannot eradicate HBV. Therefore, the development of an active cell culture system supporting HBV infection has become the key to studying HBV and developing effective therapeutic drugs.

Main body

This review summarizes the significant research achievements in HBV cell culture systems in vitro, including embryonic hepatocytes and primary hepatocytes, which support the virus infection process most similar to that in the body and various liver tumor cells. The discovery of the bile-acid pump sodium-taurocholate co-transporting polypeptide (NTCP) as the receptor of HBV has advanced our understanding of HBV biology. Subsequently, various liver cancer cells overexpressing NTCP that support HBV infection have been established, opening a new door for studying HBV infection. The fact that induced pluripotent stem cells that differentiate into hepatocyte-like cells support HBV infection provides a novel idea for the establishment of an HBV cell culture system.

Conclusion

Because of the host and tissue specificity of HBV, a suitable in vitro HBV infection system is critical for the study of HBV pathogenesis. Nevertheless, recent advances regarding HBV infection in vitro offer hope for better studying the biological characteristics of HBV, the pathogenesis of hepatitis B, the screening of anti-HBV drugs and the mechanism of carcinogenesis.

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.

Modeling Pharmacokinetic Natural Product-Drug Interactions for Decision-Making: A NaPDI Center Recommended Approach

The popularity of botanical and other purported medicinal natural products (NPs) continues to grow, especially among patients with chronic illnesses and patients managed on complex prescription drug regimens. With few exceptions, the risk of a given NP to precipitate a clinically significant pharmacokinetic NP-drug interaction (NPDI) remains understudied or unknown. Application of static or dynamic mathematical models to predict and/or simulate NPDIs can provide critical information about the potential clinical significance of these complex interactions. However, methods used to conduct such predictions or simulations are highly variable. Additionally, published reports using mathematical models to interrogate NPDIs are not always sufficiently detailed to ensure reproducibility. Consequently, guidelines are needed to inform the conduct and reporting of these modeling efforts. This recommended approach from the Center of Excellence for Natural Product Drug Interaction Research describes a systematic method for using mathematical models to interpret the interaction risk of NPs as precipitants of potential clinically significant pharmacokinetic NPDIs. A framework for developing and applying pharmacokinetic NPDI models is presented with the aim of promoting accuracy, reproducibility, and generalizability in the literature. SIGNIFICANCE STATEMENT: Many natural products (NPs) contain phytoconstituents that can increase or decrease systemic or tissue exposure to, and potentially the efficacy of, a pharmaceutical drug; however, no regulatory agency guidelines exist to assist in predicting the risk of these complex interactions. This recommended approach from a multi-institutional consortium designated by National Institutes of Health as the Center of Excellence for Natural Product Drug Interaction Research provides a framework for modeling pharmacokinetic NP-drug interactions.

Impact of Plasma Protein Binding in Drug Clearance Prediction: A Data Base Analysis of Published Studies and Implications for In Vitro-In Vivo Extrapolation

Plasma protein-mediated uptake (PMU) and its effect on clearance (CL) prediction have been studied in various formats; however, a comprehensive analysis of the overall impact of PMU on CL parameters from hepatocyte assays (routinely used for IVIVE) has not previously been performed. The following work collated data reflecting the effect of PMU for 26 compounds with a wide variety of physicochemical, drug, and in vivo CL properties. PMU enhanced the unbound intrinsic clearance in vitro (CLint,u in vitro) beyond that conventionally calculated using fraction unbound and was correlated with the unbound fraction of drug in vitro and in plasma (fup) and absolute unbound intrinsic clearance in vivo (CLint,u in vivo) in both rat and human hepatocytes. PMU appeared to be more important for highly bound (fup < 0.1) and high CLint,u in vivo drugs. These trends were independent of species, assay conditions, ionization, and extended clearance classification system group, although the type of plasma protein used in in vitro assays may require further investigation. Such generalized trends (spanning fup 0.0008-0.99) may suggest a generic mechanism behind PMU; however, multiple drug-dependent mechanisms are also possible. Using the identified relationship between the impact of PMU on CLint,u in vitro and fup, PMU-enhanced predictions of CLint,u in vivo were calculated for both transporter substrates and metabolically cleared drugs. PMU was accurately predicted, and incorporation of predicted PMU improved the IVIVE of hepatic CL, with an average fold error of 1.17 and >50% of compounds predicted within a 2-fold error for both rat and human data sets (n ≥ 100). SIGNIFICANCE STATEMENT: Current strategies for prediction of hepatic clearance from in vitro data are recognized to be inaccurate, but they do not account for PMU. The impact of PMU on CLint,u in vitro is wide ranging and can be predicted based on fraction unbound in plasma and applied to CLint,u in vitro values obtained by standard procedures in the absence of plasma protein. Such PMU-enhanced predictions improved IVIVE, and future studies may easily incorporate this PMU relationship to provide more accurate IVIVE.

Prediction of Drug Clearance from Enzyme and Transporter Kinetics

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.

Primary Human Hepatocyte Spheroid Model as a 3D In Vitro Platform for Metabolism Studies

3D cultures of primary human hepatocytes (PHH) are emerging as a more in vivo-like culture system than previously available hepatic models. This work describes the characterisation of drug metabolism in 3D PHH spheroids. Spheroids were formed from three different donors of PHH and the expression and activities of important cytochrome P450 enzymes (CYP1A2, 2B6, 2C9, 2D6, and 3A4) were maintained for up to 21 days after seeding. The activity of CYP2B6 and 3A4 decreased, while the activity of CYP2C9 and 2D6 increased over time (P < 0.05). For six test compounds, that are metabolised by multiple enzymes, intrinsic clearance (CL_int) values were comparable to standard in vitro hepatic models and successfully predicted in vivo CL_int within 3-fold from observed values for low clearance compounds. Remarkably, the metabolic turnover of these low clearance compounds was reproducibly measured using only 1-3 spheroids, each composed of 2000 cells. Importantly, metabolites identified in the spheroid cultures reproduced the major metabolites observed in vivo, both primary and secondary metabolites were captured. In summary, the 3D PHH spheroid model shows promise to be used in drug discovery projects to study drug metabolism, including unknown mechanisms, over an extended period of time.

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.

Metabolism of the dual FLT-3/Aurora kinase inhibitor CCT241736 in preclinical and human in vitro models: Implication for the choice of toxicology species

CCT241736 is a dual fms-like tyrosine kinase 3 (FLT3)/Aurora kinase inhibitor in development for the treatment of acute myeloid leukaemia. The successful development of any new drug relies on adequate safety testing including preclinical toxicology studies. Selection of an appropriate preclinical species requires a thorough understanding of the compound's metabolic clearance and pathways, as well as other pharmacokinetic and pharmacodynamic considerations. In addition, elucidation of the metabolising enzymes in human facilitates improved clinical prediction based on population pharmacokinetics and can inform drug-drug interaction studies. Intrinsic clearance (CLint) determination and metabolite profiling of CCT241736 in human and four preclinical species (dog, minipig, rat and mouse) was undertaken in cryopreserved hepatocytes and liver microsomes. Recombinant human cytochrome P450 bactosomes (rCYP) were utilised to provide reaction phenotyping data and support prediction of metabolic pathways. CCT241736 exhibited low CLint in both hepatocytes and liver microsomes of human, dog, minipig and rat, but considerably higher CLint in mouse. CYP3A4 and CYP3A5 were identified as the major enzymes responsible for biotransformation of CCT241736 in human, exclusively forming five out of seven metabolites. Minipig showed greatest similarity to human with regard to both overall metabolic profile and abundance of specific metabolites relative to parent compound, and is therefore proposed as the most appropriate toxicological species. The greatest disparity was observed between human and dog. Based on metabolic profile, either mouse or rat is a suitable rodent species for toxicology studies.

Interlaboratory Variability in Human Hepatocyte Intrinsic Clearance Values and Trends with Physicochemical Properties

PURPOSE

To examine the interlaboratory variability in CL_int values generated with human hepatocytes and determine trends in variability and clearance prediction accuracy using physicochemical and pharmacokinetic parameters.

METHODS

Data for 50 compounds from 14 papers were compiled with physicochemical and pharmacokinetic parameter values taken from various sources.

RESULTS

Coefficients of variation were as high as 99.8% for individual compounds and variation was not dependent on the number of prediction values included in the analysis. When examining median values, it appeared that compounds with a lower number of rotatable bonds had more variability. When examining prediction uniformity, those compounds with uniform in vivo underpredictions had higher CL_{int, in vivo} values, while those with non-uniform predictions typically had lower CL_{int, in vivo} values. Of the compounds with uniform predictions, only a small number were uniformly predicted accurately. Based on this limited dataset, less lipophilic, lower intrinsic clearance, and lower protein binding compounds yield more accurate clearance predictions.

CONCLUSIONS

Caution should be taken when compiling in vitro CL_int values from different laboratories as variations in experimental procedures (such as extent of shaking during incubation) may yield different predictions for the same compound. The majority of compounds with uniform in vitro values had predictions that were inaccurate, emphasizing the need for a better mechanistic understanding of IVIVE. The non-uniform predictions, often with low turnover compounds, reaffirmed the experimental challenges for drugs in this clearance range. Separating new chemical entities by lipophilicity, intrinsic clearance, and protein binding may help instill more confidence in IVIVE predictions.

Use of Segregated Hepatocyte Scaling Factors and Cross-Species Relationships to Resolve Clearance Dependence in the Prediction of Human Hepatic Clearance

Human and rat hepatocytes have a strong tendency to underpredict hepatic intrinsic clearance (CLint) and the extent of underprediction increases with increasing observed CLint In this study, application of the log average rat hepatocyte-rat in vivo empirical scaling factor (ESF) of 4.2 to human hepatocyte prediction successfully removed bias but did not improve precision. An analogous method using individual drug rat ESFs only achieved marginal improvement in accuracy but not precision. A novel approach to resolve clearance-dependent prediction, involving rat ESFs calculated for particular (order of magnitude) ranges of observed CLint (log average range, 0.12-2.1) improved human prediction precision but only modestly reduced bias. However, rat in vivo CLint was several-fold greater than human in vivo CLint and this was reflected in greater rat hepatocyte and microsome CLint, suggesting that rat metabolic enzymes are more efficient than their human counterparts, by several-fold. By applying the segregated rat ESFs followed by the human/rat CLint ratio, which was consistent regardless of CLint (log average 3.5), both accuracy and precision were improved, providing both a means of mitigating clearance dependence and reaffirming the potential role of rat hepatocytes for prediction of human metabolic CLint These cross-species observations indicate that underprediction from human in vitro systems may be predominantly consequential of an intrinsic property of the in vitro system rather than individual drug properties.

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.

The Extended Clearance Concept Following Oral and Intravenous Dosing: Theory and Critical Analyses

PURPOSE

To derive the theoretical basis for the extended clearance model of organ elimination following both oral and IV dosing, and critically analyze the approaches previously taken.

METHODS

We derived from first principles the theoretical basis for the extended clearance concept of organ elimination following both oral and IV dosing and critically analyzed previous approaches.

RESULTS

We point out a number of critical characteristics that have either been misinterpreted or not clearly presented in previously published treatments. First, the extended clearance concept is derived based on the well-stirred model. It is not appropriate to use alternative models of hepatic clearance. In analyzing equations, clearance terms are all intrinsic clearances, not total drug clearances. Flow and protein binding parameters should reflect blood measurements, not plasma values. In calculating the AUCR-factor following oral dosing, the AUC terms do not include flow parameters. We propose that calculations of AUCR may be a more useful approach to evaluate drug-drug and pharmacogenomic interactions than evaluating rate-determining steps. Through analyses of cerivastatin and fluvastatin interactions with cyclosporine we emphasize the need to characterize volume of distribution changes resulting from transporter inhibition/induction that can affect rate constants in PBPK models. Finally, we note that for oral doses, prediction of systemic and intrahepatic drug-drug interactions do not require knowledge of fu,H or Kp,uu for substrates/victims.

CONCLUSIONS

The extended clearance concept is a powerful tool to evaluate drug-drug interactions, pharmacogenomic and disease state variance but evaluating the AUCR-factor may provide a more valuable approach than characterizing rate-determining steps.