Prediction of hepatic clearance using cryopreserved human hepatocytes: a comparison of serum and serum-free incubations

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE)

BACKGROUND AND OBJECTIVE

The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results.

METHODS

Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors.

RESULTS

The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC.

CONCLUSIONS

The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Does Addition of Protein to Hepatocyte or Microsomal In Vitro Incubations Provide a Useful Improvement in In Vitro-In Vivo Extrapolation Predictability?

Accurate prediction of in vivo hepatic clearance is an essential part of successful and efficient drug development; however, many investigators have recognized that there are significant limitations in the predictability of clearance with a tendency for underprediction for primarily metabolized drugs. Here, we examine the impact of adding serum or albumin into hepatocyte and microsomal incubations on the predictability of in vivo hepatic clearance. The addition of protein into hepatocyte incubations has been reported to improve the predictability for high clearance (extraction ratio) drugs and highly protein-bound drugs. Analyzing published data for 60 different drugs and 97 experimental comparisons (with 17 drugs being investigated from two to seven) we confirmed the marked underprediction of clearance. However, we could not validate any relevant improved predictability within twofold by the addition of serum to hepatocyte incubations or albumin to microsomal incubations. This was the case when investigating all measurements, or when subdividing analyses by extraction ratio, degree of protein binding, Biopharmaceutics Drug Disposition Classification System class, examining Extended Clearance Classification System class 1B drugs only, or drug charge. Manipulating characteristics of small data sets of like compounds and adding scaling factors can appear to yield good predictability, but the carryover of these methods to alternate drug classes and different laboratories is not evident. Improvement in predictability of poorly soluble compounds is greater than that for soluble compounds, but not to a meaningful extent. Overall, we cannot confirm that protein addition improves in vitro-in vivo extrapolation predictability to any clinically meaningful degree when considering all drugs and different subsets. SIGNIFICANCE STATEMENT: The addition of protein into microsomal or hepatocyte incubations has been widely proposed to improve hepatic clearance predictions. To date, studies examining this phenomenon have not included appropriate negative controls where predictability is achieved without protein addition and have been conducted with small data sets of similar compounds that don't apply to alternate drug classes. Here, an extensive analysis of published data for 60 drugs and 97 experimental comparisons couldn't validate any relevant clinically improved clearance predictability with protein addition.

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.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

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 (CL_{int,u in vitro}) beyond that conventionally calculated using fraction unbound and was correlated with the unbound fraction of drug in vitro and in plasma (fu_p) and absolute unbound intrinsic clearance in vivo (CL_{int,u in vivo}) in both rat and human hepatocytes. PMU appeared to be more important for highly bound (fu_p < 0.1) and high CL_{int,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 fu_p 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 CL_{int,u in vitro} and fu_p, PMU-enhanced predictions of CL_{int,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 CL_{int,u in vitro} is wide ranging and can be predicted based on fraction unbound in plasma and applied to CL_{int,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.

Comparative Assessment of Extrapolation Methods Based on the Conventional Free Drug Hypothesis and Plasma Protein-Mediated Hepatic Uptake Theory for the Hepatic Clearance Predictions of Two Drugs Extensively Bound to Both the Albumin And Alpha-1-Acid Glycoprotein

Bteich and coworkers recently demonstrated in a companion manuscript (J Pharm Sci 109: https://doi.org/10.1016/j.xphs.2020.07.003) that a protein-mediated hepatic uptake have occurred in an isolated perfused rat liver (IPRL) model for two drugs (Perampanel; PER and Fluoxetine; FLU) that bind extensively to the albumin (ALB) and alpha-1-acid glycoprotein (AGP). However, to our knowledge, there is no quantitative model available to predict the impact of a plasma protein-mediated hepatic uptake on the extent of hepatic clearance (CLh) for a drug binding extensively to these two proteins. Therefore, the main objective was to predict the corresponding CLh, which is an extension of the companion manuscript. The method consisted of extrapolating the intrinsic clearance from the unbound fraction measured in the perfusate or the unbound fraction extrapolated to the surface of the hepatocyte membrane by adapting an existing model of protein-mediated hepatic uptake (i.e., the fu_p-adjusted model) to include a binding ratio between the ALB and AGP. This new approach showed a relevant improvement compared to the free drug hypothesis particularly for FLU that showed the highest degree of ALB-mediated uptake. Overall, this study is a first step towards the development of predictive methods of CLh by considering the binding to ALB and AGP.

In vitro hepatic biotransformation of the algal toxin pectenotoxin-2

We have investigated the in vitro metabolism of pectenotoxin-2 (PTX-2) using primary hepatocytes from Wistar rats in suspension. Purified PTX-2 was rapidly metabolized. Two major and several minor oxidized PTX-2 metabolites were formed, none of which had retention times corresponding to PTX-1, -11, or −13. Hydrolysis products, such as PTX-2 seco acid, were not observed. Preliminary multi-stage LC-MS analyses indicated that the major hepatic PTX-2 metabolites resulted from the insertion of an oxygen atom at the positions C-19 to C-24, or at C-44. The rapid oxidative metabolism may explain the low oral toxicity of PTXs observed in vivo studies.

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PTX-2 is rapidly metabolized in rat hepatocytes.

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Two major and several minor oxidized PTX-2 metabolites were formed.

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The results may explain the low oral toxicity of PTXs observed in vivo studies.

The Presence of a Transporter-Induced Protein Binding Shift: A New Explanation for Protein-Facilitated Uptake and Improvement for In Vitro-In Vivo Extrapolation

Accurately predicting hepatic clearance is an integral part of the drug-development process, and yet current in vitro to in vivo (IVIVE) extrapolation methods yield poor predictions, particularly for highly protein-bound transporter substrates. Explanations for error include inaccuracies in protein-binding measurements and the lack of recognition of protein-facilitated uptake, where both unbound and bound drug may be cleared, violating the principles of the widely accepted free drug theory. A new explanation for protein-facilitated uptake is proposed here, called a transporter-induced protein binding shift High-affinity binding to cell-membrane proteins may change the equilibrium of the nonspecific binding between drugs and plasma proteins, leading to greater cellular uptake and clearance than currently predicted. The uptake of two lower protein-binding organic anion transporting polypeptide substrates (pravastatin and rosuvastatin) and two higher binding substrates (atorvastatin and pitavastatin) were measured in rat hepatocytes in incubations with protein-free buffer versus 100% plasma. Decreased unbound K _m values and increased intrinsic clearance values were seen in the plasma incubations for the highly bound compounds, supporting the new hypothesis and mitigating the IVIVE underprediction previously seen for highly bound transporter substrates.

In vivo hepatic clearance of lipophilic drugs predicted by in vitro uptake data into cryopreserved hepatocytes suspended in sera of rats, guinea pigs, monkeys and humans

Evaluation of uptake of lipophilic acid compounds into hepatocytes was an unresolved drug development issue because of their adsorption to cells and materials and low analytical sensitivity and accuracy in assessment of protein bindings. Uptake assays of compounds using hepatocytes suspended in serum were expected to solve these problems for prediction of in vivo hepatic clearance. Here, for compounds with high protein binding (>99%), diflunisal, montelukast, cerivastatin, telmisartan, fluvastatin and six new drug candidates, in vivo hepatic clearance predicted based on hepatic depletion and uptake (CL_{h, uptake, predicted}) data using hepatocytes in the absence and presence of sera was investigated. In vitro hepatic uptake results with hepatocytes suspended in serum improved prediction of human hepatic clearance values for highly lipophilic montelukast and telmisartan. In vivo CL_{h, uptake, predicted} values of six new highly lipophilic acid drug candidates (protein binding >99.97%) and diflunisal, montelukast and cerivastatin predicted based on hepatocytes suspended in serum were within threefold differences of their total clearance in vivo in rats, guinea pigs or monkeys, except for montelukast in monkeys (5.8-fold). These results suggest that the human hepatic uptake in hepatocytes suspended in serum is useful for prediction of CL_{h, uptake, predicted}, especially for highly lipophilic/protein binding acid compounds.

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.

Cellular Uptake Kinetics of Neutral and Charged Chemicals in in Vitro Assays Measured by Fluorescence Microscopy

Cellular uptake kinetics are key for understanding time-dependent chemical exposure in in vitro cell assays. Slow cellular uptake kinetics in relation to the total exposure time can considerably reduce the biologically effective dose. In this study, fluorescence microscopy combined with automated image analysis was applied for time-resolved quantification of cellular uptake of 10 neutral, anionic, cationic, and zwitterionic fluorophores in two reporter gene assays. The chemical fluorescence in the medium remained relatively constant during the 24-h assay duration, emphasizing that the proteins and lipids in the fetal bovine serum (FBS) supplemented to the assay medium represent a large reservoir of reversibly bound chemicals with the potential to compensate for chemical depletion by cell uptake, growth, and sorption to well materials. Hence FBS plays a role in stabilizing the cellular dose in a similar way as polymer-based passive dosing, here we term this process as serum-mediated passive dosing (SMPD). Neutral chemicals accumulated in the cells up to 12 times faster than charged chemicals. Increasing medium FBS concentrations accelerated uptake due to FBS-facilitated transport but led to lower cellular concentrations as a result of increased sorption to medium proteins and lipids. In vitro cell exposure results from the interaction of several extra- and intracellular processes, leading to variable and time-dependent exposure between different chemicals and assay setups. The medium FBS plays a crucial role for the thermodynamic equilibria as well as for the cellular uptake kinetics, hence influencing exposure. However, quantification of cellular exposure by an area under the curve (AUC) analysis illustrated that, for the evaluated bioassay setup, current in vitro exposure models that assume instantaneous equilibrium between medium and cells still reflect a realistic exposure because the AUC was typically reduced less than 20% compared to the cellular dose that would result from instantaneous equilibrium.

Interconnected Microphysiological Systems for Quantitative Biology and Pharmacology Studies

Microphysiological systems (MPSs) are in vitro models that capture facets of in vivo organ function through use of specialized culture microenvironments, including 3D matrices and microperfusion. Here, we report an approach to co-culture multiple different MPSs linked together physiologically on re-useable, open-system microfluidic platforms that are compatible with the quantitative study of a range of compounds, including lipophilic drugs. We describe three different platform designs – “4-way”, “7-way”, and “10-way” – each accommodating a mixing chamber and up to 4, 7, or 10 MPSs. Platforms accommodate multiple different MPS flow configurations, each with internal re-circulation to enhance molecular exchange, and feature on-board pneumatically-driven pumps with independently programmable flow rates to provide precise control over both intra- and inter-MPS flow partitioning and drug distribution. We first developed a 4-MPS system, showing accurate prediction of secreted liver protein distribution and 2-week maintenance of phenotypic markers. We then developed 7-MPS and 10-MPS platforms, demonstrating reliable, robust operation and maintenance of MPS phenotypic function for 3 weeks (7-way) and 4 weeks (10-way) of continuous interaction, as well as PK analysis of diclofenac metabolism. This study illustrates several generalizable design and operational principles for implementing multi-MPS “physiome-on-a-chip” approaches in drug discovery.

Improving Prediction of Metabolic Clearance Using Quantitative Extrapolation of Results Obtained From Human Hepatic Micropatterned Cocultures Model and by Considering the Impact of Albumin Binding

The objective was to compare, with the same data set, the predictive performance of 3 in vitro assays of hepatic clearance (CL), namely, micropatterned cocultures (also referring to HepatoPac^®) and suspension as well as monolayer hepatocytes to define which assay is the most accurate. Furthermore, existing in vitro-to-in vivo extrapolation (IVIVE) methods were challenged to verify which method is the most predictive (i.e., direct scaling method without binding correction, conventional method based either on the unbound fraction in plasma (fu_p) according to the free-drug hypothesis, or based on an fu_p value adjusted for the albumin [ALB]-facilitated hepatic uptake phenomenon). Accordingly, the role of ALB binding was specifically challenged, and consequently, the ALB production was monitored in parallel to the metabolic stability. The ALB concentration data were used to compare the in vitro assays and to adjust the value of fu_p of each drug to mimic the ALB-facilitated hepatic uptake phenomenon. The results confirmed that the direct and conventional IVIVE methods generally overpredicted and underpredicted the CL in vivo in humans, respectively. However, the underprediction of the conventional IVIVE method based on fu_p was significantly reduced from data generated with the HepatoPac^® system compared with the 2 other in vitro assays, which is possibly because that system is producing ALB at a rate much closer to the in vivo condition in liver. Hence, these observations suggest that the presence of more ALB molecules per hepatocyte in that HepatoPac^® system may have facilitated the hepatic uptake of several bound drugs because their intrinsic CL was increased instead of being decreased by the ALB binding effect. Accordingly, the IVIVE method based on the fu_p value adjusted for the ALB-facilitated uptake phenomenon gave the lowest prediction bias from the statistical analyses. This study indicated that the HepatoPac^® system combined with the adjusted value of fu_p was the most reliable IVIVE method and revealed the importance of quantifying the in vitro-to-in vivo variation of ALB concentration to improve the CL predictions, which would help any future physiologically based pharmacokinetics modeling exercise.

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.

The Role of Extracellular Binding Proteins in the Cellular Uptake of Drugs: Impact on Quantitative In Vitro-to-In Vivo Extrapolations of Toxicity and Efficacy in Physiologically Based Pharmacokinetic-Pharmacodynamic Research

A critical component in the development of physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) models for estimating target organ dosimetry in pharmacology and toxicology studies is the understanding of the uptake kinetics and accumulation of drugs and chemicals at the cellular level. Therefore, predicting free drug concentrations in intracellular fluid will contribute to our understanding of concentrations at the site of action in cells in PBPK/PD research. Some investigators believe that uptake of drugs in cells is solely driven by the unbound fraction; conversely, others argue that the protein-bound fraction contributes a significant portion of the total amount delivered to cells. Accordingly, the current literature suggests the existence of a so-called albumin-mediated uptake mechanism(s) for the protein-bound fraction (i.e., extracellular protein-facilitated uptake mechanisms) at least in hepatocytes and cardiac myocytes; however, such mechanism(s) and cells from other organs deserve further exploration. Therefore, the main objective of this present study was to discuss further the implication of potential protein-facilitated uptake mechanism(s) on drug distribution in cells under in vivo conditions. The interplay between the protein-facilitated uptake mechanism(s) and the effects of a pH gradient, metabolism, transport, and permeation limitation potentially occurring in cells was also discussed, as this should violate the basic assumption on similar free drug concentration in cells and plasma. This was made because the published equations used to calculate drug concentrations in cells in a PBPK/PD model did not consider potential protein-facilitated uptake mechanism(s). Consequently, we corrected some published equations for calculating the free drug concentrations in cells compared with plasma in PBPK/PD modeling studies, and we proposed a refined strategy for potentially performing more accurate quantitative in vitro-to-in vivo extrapolations (IVIVEs) of toxicity (efficacy) at the cellular level from data generated in cell assays. Overall, this present study may help to optimize the human dose prediction in preclinical and clinical studies, while prescribing drugs with narrow therapeutic windows that are highly bound to extracellular proteins and/or highly ionized at the physiological pH. This may facilitate building a more accurate safety (efficacy) profile for such drugs.

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.

In Silico Modeling for the Prediction of Dose and Pathway-Related Adverse Effects in Humans From In Vitro Repeated-Dose Studies

Long-term repeated-dose toxicity is mainly assessed in animals despite poor concordance of animal data with human toxicity. Nowadays advanced human in vitro systems, eg, metabolically competent HepaRG cells, are used for toxicity screening. Extrapolation of in vitro toxicity to in vivo effects is possible by reverse dosimetry using pharmacokinetic modeling. We assessed long-term repeated-dose toxicity of bosentan and valproic acid (VPA) in HepaRG cells under serum-free conditions. Upon 28-day exposure, the EC50 values for bosentan and VPA decreased by 21- and 33-fold, respectively. Using EC(10) as lowest threshold of toxicity in vitro, we estimated the oral equivalent doses for both test compounds using a simplified pharmacokinetic model for the extrapolation of in vitro toxicity to in vivo effect. The model predicts that bosentan is safe at the considered dose under the assumed conditions upon 4 weeks exposure. For VPA, hepatotoxicity is predicted for 4% and 47% of the virtual population at the maximum recommended daily dose after 3 and 4 weeks of exposure, respectively. We also investigated the changes in the central carbon metabolism of HepaRG cells exposed to orally bioavailable concentrations of both drugs. These concentrations are below the 28-day EC(10) and induce significant changes especially in glucose metabolism and urea production. These metabolic changes may have a pronounced impact in susceptible patients such as those with compromised liver function and urea cycle deficiency leading to idiosyncratic toxicity. We show that the combination of modeling based on in vitro repeated-dose data and metabolic changes allows the prediction of human relevant in vivo toxicity with mechanistic insights.

Dose metric considerations in in vitro assays to improve quantitative in vitro-in vivo dose extrapolations

Challenges to improve toxicological risk assessment to meet the demands of the EU chemical's legislation, REACH, and the EU 7th Amendment of the Cosmetics Directive have accelerated the development of non-animal based methods. Unfortunately, uncertainties remain surrounding the power of alternative methods such as in vitro assays to predict in vivo dose-response relationships, which impedes their use in regulatory toxicology. One issue reviewed here, is the lack of a well-defined dose metric for use in concentration-effect relationships obtained from in vitro cell assays. Traditionally, the nominal concentration has been used to define in vitro concentration-effect relationships. However, chemicals may differentially and non-specifically bind to medium constituents, well plate plastic and cells. They may also evaporate, degrade or be metabolized over the exposure period at different rates. Studies have shown that these processes may reduce the bioavailable and biologically effective dose of test chemicals in in vitro assays to levels far below their nominal concentration. This subsequently hampers the interpretation of in vitro data to predict and compare the true toxic potency of test chemicals. Therefore, this review discusses a number of dose metrics and their dependency on in vitro assay setup. Recommendations are given on when to consider alternative dose metrics instead of nominal concentrations, in order to reduce effect concentration variability between in vitro assays and between in vitro and in vivo assays in toxicology.

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.

Selection of suitable prodrug candidates for in vivo studies via in vitro studies; the correlation of prodrug stability in between cell culture homogenates and human tissue homogenates

PURPOSE

To determine the correlations/discrepancies of drug stabilities between in the homogenates of human culture cells and of human tissues.

METHODS

Amino acid/dipeptide monoester prodrugs of floxuridine were chosen as the model drugs. The stabilities (half-lives) of floxuridine prodrugs in human tissues (pancreas, liver, and small intestine) homogenates were obtained and compared with ones in cell culture homogenates (AcPC-1, Capan-2, and Caco-2 cells) as well as human liver microsomes. The correlations of prodrug stability in human small bowel tissue homogenate vs. Caco-2 cell homogenate, human liver tissue homogenate vs. human liver microsomes, and human pancreatic tissue homogenate vs. pancreatic cell, AsPC-1 and Capan-2, homogenates were examined.

RESULTS

The stabilities of floxuridine prodrugs in human small bowel homogenate exhibited the great correlation to ones in Caco-2 cell homogenate (slope = 1.0-1.3, r2 = 0.79-0.98). The stability of those prodrugs in human pancreas tissue homogenate also exhibited the good correlations to ones in AsPC-1 and Capan-2 cells homogenates (slope = 0.5-0.8, r2 = 0.58-0.79). However, the correlations of prodrug stabilities between in human liver tissue homogenates and in human liver microsomes were weaker than others (slope = 1.3-1.9, r2 = 0.07-0.24).

CONCLUSIONS

The correlations of drug stabilities in cultured cell homogenates and in human tissue homogenates were compared. Those results exhibited wide range of correlations between in cell homogenate and in human tissue homogenate (r2 = 0.07 - 0.98). Those in vitro studies in cell homogenates would be good tools to predict drug stabilities in vivo and to select drug candidates for further developments. In the series of experiments, 5'-O-D-valyl-floxuridine and 5'-O-L-phenylalanyl-L-tyrosyl-floxuridine would be selected as candidates of oral drug targeting delivery for cancer chemotherapy due to their relatively good stabilities compared to other tested prodrugs.

Serum-free culture of primary human hepatocytes in a miniaturized hollow-fibre membrane bioreactor for pharmacological in vitro studies

Primary human hepatocytes represent an important cell source for in vitro investigation of hepatic drug metabolism and disposition. In this study, a multi-compartment capillary membrane-based bioreactor technology for three-dimensional (3D) perfusion culture was further developed and miniaturized to a volume of less than 0.5 ml to reduce demand for cells. The miniaturized bioreactor was composed of two capillary layers, each made of alternately arranged oxygen and medium capillaries serving as a 3D culture for the cells. Metabolic activity and stability of primary human hepatocytes was studied in this bioreactor in the presence of 2.5% fetal calf serum (FCS) under serum-free conditions over a culture period of 10 days. The miniaturized bioreactor showed functions comparable to previously reported data for larger variants. Glucose and lactate metabolism, urea production, albumin synthesis and release of intracellular enzymes (AST, ALT, GLDH) showed no significant differences between serum-free and serum-supplemented bioreactors. Activities of human-relevant cytochrome P450 (CYP) isoenzymes (CYP1A2, CYP3A4/5, CYP2C9, CYP2D6, CYP2B6) analyzed by determination of product formation rates from selective probe substrates were also comparable in both groups. Gene expression analysis showed moderately higher expression in the majority of CYP enzymes, transport proteins and enzymes of Phase II metabolism in the serum-free bioreactors compared to those maintained with FCS. In conclusion, the miniaturized bioreactor maintained stable function over the investigated period and thus provides a suitable system for pharmacological studies on primary human hepatocytes under defined serum-free conditions.

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

Underprediction of in vivo intrinsic clearance (CL(int)) of unbound drug from human hepatic in vitro systems using physiological extrapolation methodology is accepted as a common outcome. Poulin et al. (2012. J Pharm Sci 101:838-851) recently proposed an approach involving determination of effective fraction unbound in plasma (fu(p)) based on albumin-facilitated hepatic uptake of acidic/neutral drugs which improved prediction accuracy and precision for 25 drugs highly bound to plasma proteins. This approach includes correction of unbound drug according to the ionisation fraction either side of the plasma membrane based on pH difference. Here, we assessed the proposed method using a larger database of predictions of CL(int) for 107 drugs involving hepatocytes (89 drugs) and microsomes (64 drugs). The proposed method was similarly effective in minimising average prediction bias (to within twofold), unlike the conventional fu(p) correction method. However, precision was similar between methods and there was no evidence in the larger database that prediction bias was associated with fu(p). Prediction bias for hepatocytes was clearance dependent by either method, indicating important sources of bias from in vitro methodology. Therefore, to progress beyond empirical correction of bias, there is further need of mechanistic elucidation to improve prediction methodology.

In vitro-in vivo extrapolation of clearance: modeling hepatic metabolic clearance of highly bound drugs and comparative assessment with existing calculation methods

In vitro-in vivo extrapolation (IVIVE) is an important method for estimating the hepatic metabolic clearance (CL) of drugs. This study highlights a problematic area observed when using microsomal data to predict in vivo CL of drugs that are highly bound to plasma proteins, and further explores mechanisms for human CL predictions by associating additional processes to IVIVE disconnect. Therefore, this study attempts to develop a novel IVIVE calculation method, which consists of adjusting the binding terms in a well-stirred liver model. A comparative assessment between the IVIVE method proposed here and previously published methods of Obach (1999. Drug Metab Dispos 27:1350-1359) and Berezhkovskiy (2010. J Pharm Sci 100:1167-1783) was also performed. The assessment was confined by the availability of measured in vitro and in vivo data in humans for 25 drugs highly bound to plasma proteins, for which it can be assumed that metabolism is the major route of elimination. Here, we argue that a difference in drug ionization and binding proteins such as albumin (AL) and alpha-1-acid glycoprotein (AAG) in plasma and liver also needs to be considered in IVIVE based on mechanistic studies. Therefore, converting unbound fraction in plasma to liver essentially increased the predicted CL values, which resulted in much more accurate estimates of in vivo CL as compared with the other IVIVE methods tested. The impact on CL estimate was more apparent for drugs binding to AL than to AAG. This is a mechanistic rational for explaining a considerable proportion of the divergence between previously estimated and observed CL values. Human CL was predicted within 1.5-fold, twofold, and threefold of the observed CL for 84%, 96%, and 100% of the compounds, respectively. Overall, this study demonstrates a significant improvement in the mechanism-based prediction of metabolic CL for these 25 highly bound drugs from in vitro data determined with microsomes, which should facilitate the application of physiologically based pharmacokinetic (PBPK) models in drug discovery and development.

Pharmacodynamic model of sodium-glucose transporter 2 (SGLT2) inhibition: implications for quantitative translational pharmacology

Sodium-glucose co-transporter-2 (SGLT2) inhibitors are an emerging class of agents for use in the treatment of type 2 diabetes mellitus (T2DM). Inhibition of SGLT2 leads to improved glycemic control through increased urinary glucose excretion (UGE). In this study, a biologically based pharmacokinetic/pharmacodynamic (PK/PD) model of SGLT2 inhibitor-mediated UGE was developed. The derived model was used to characterize the acute PK/PD relationship of the SGLT2 inhibitor, dapagliflozin, in rats. The quantitative translational pharmacology of dapagliflozin was examined through both prospective simulation and direct modeling of mean literature data obtained for dapagliflozin in healthy subjects. Prospective simulations provided time courses of UGE that were of consistent shape to clinical observations, but were modestly biased toward under prediction. Direct modeling provided an improved characterization of the data and precise parameter estimates which were reasonably consistent with those predicted from preclinical data. Overall, these results indicate that the acute clinical pharmacology of SGLT2 inhibitors in healthy subjects can be reasonably well predicted from preclinical data through rational accounting of species differences in pharmacokinetics, physiology, and SGLT2 pharmacology. Because these data can be generated at the earliest stages of drug discovery, the proposed model is useful in the design and development of novel SGLT2 inhibitors. In addition, this model is expected to serve as a useful foundation for future efforts to understand and predict the effects of SGLT2 inhibition under chronic administration and in other patient populations.

Physiologically based predictions of the impact of inhibition of intestinal and hepatic metabolism on human pharmacokinetics of CYP3A substrates

The first objective of the present study was to predict the pharmacokinetics of selected CYP3A substrates administered at a single oral dose to human. The second objective was to predict pharmacokinetics of the selected drugs in presence of inhibitors of the intestinal and/or hepatic CYP3A activity. We developed a whole-body physiologically based pharmacokinetics (WB-PBPK) model accounting for presystemic elimination of midazolam (MDZ), alprazolam (APZ), triazolam (TRZ), and simvastatin (SMV). The model also accounted for concomitant administration of the above-mentioned drugs with CYP3A inhibitors, namely ketoconazole (KTZ), itraconazole (ITZ), diltiazem (DTZ), saquinavir (SQV), and a furanocoumarin contained in grape-fruit juice (GFJ), namely 6',7'-dihydroxybergamottin (DHB). Model predictions were compared to published clinical data. An uncertainty analysis was performed to account for the variability and uncertainty of model parameters when predicting the model outcomes. We also briefly report on the results of our efforts to develop a global sensitivity analysis and its application to the current WB-PBPK model. Considering the current criterion for a successful prediction, judged satisfied once the clinical data are captured within the 5th and 95th percentiles of the predicted concentration-time profiles, a successful prediction has been obtained for a single oral administration of MDZ and SMV. For APZ and TRZ, however, a slight deviation toward the 95th percentile was observed especially for C(max) but, overall, the in vivo profiles were well captured by the PBPK model. Moreover, the impact of DHB-mediated inhibition on the extent of intestinal pre-systemic elimination of MDZ and SMV has been accurately predicted by the proposed PBPK model. For concomitant administrations of MDZ and ITZ, APZ and KTZ, as well as SMV and DTZ, the in vivo concentration-time profiles were accurately captured by the model. A slight deviation was observed for SMV when coadministered with ITZ, whereas more important deviations have been obtained between the model predictions and in vivo concentration-time profiles of MDZ coadministered with SQV. The same observation was made for TRZ when administered with KTZ. Most of the pharmacokinetic parameters predicted by the PBPK model were successfully predicted within a two-fold error range either in the absence or presence of metabolism-based inhibition. Overall, the present study demonstrated the ability of the PBPK model to predict DDI of CYP3A substrates with promising accuracy.

Prediction of human pharmacokinetics—evaluation of methods for prediction of hepatic metabolic clearance

Methods for prediction of hepatic clearance (CLH) in man have been evaluated. A physiologically-based in-vitro to in-vivo (PB-IVIV) method with human unbound fraction in blood (fu,bl) and hepatocyte intrinsic clearance (CLint)-data has a good rationale and appears to give the best predictions (maximum ∼2-fold errors; &lt; 25% errors for half of CL-predictions; appropriate ranking). Inclusion of an empirical scaling factor is, however, needed, and reasons include the use of cryopreserved hepatocytes with low activity, and inappropriate CLint- and fu,bl-estimation methods. Thus, an improvement of this methodology is possible and required. Neglect of fu,bl or incorporation of incubation binding does not seem appropriate. When microsome CLint-data are used with this approach, the CLH is underpredicted by 5- to 9-fold on average, and a 106-fold underprediction (attrition potential) has been observed. The poor performance could probably be related to permeation, binding and low metabolic activity. Inclusion of scaling factors and neglect of fu,bl for basic and neutral compounds improve microsome predictions. The performance is, however, still not satisfactory. Allometry incorrectly assumes that the determinants for CLH relate to body weight and overpredicts human liver blood flow rate. Consequently, allometric methods have poor predictability. Simple allometry has an average overprediction potential, &gt; 2-fold errors for ∼1/3 of predictions, and 140-fold underprediction to 5800-fold overprediction (potential safety risk) range. In-silico methodologies are available, but these need further development. Acceptable prediction errors for compounds with low and high CLH should be ∼50 and ∼10%, respectively. In conclusion, it is recommended that PB-IVIV with human hepatocyte CLint and fu,bl is applied and improved, limits for acceptable errors are decreased, and that animal CLH-studies and allometry are avoided.

The species differences of intestinal drug absorption and first-pass metabolism between cynomolgus monkeys and humans

In order to elucidate the causes of the species differences in the oral bioavailability (BA) between cynomolgus monkeys and humans, the contributions of first-pass metabolism and intestinal absorption were investigated. Typical substrates of cytochrome P450 enzymes, UDP-glucuronosyltransferase enzymes and efflux transporters were selected, and the BA, the hepatic availability (Fh) and the fraction dose absorbed from gastro-intestinal tract (Fa*Fg) were calculated from pharmacokinetic analysis after oral and intravenous administration in cynomolgus monkeys. In addition, in vitro metabolism was investigated using liver and intestinal microsomes to evaluate the relationship between in vivo and in vitro results. The BA of cynomolgus monkeys was low compared with that in humans with most of the drugs tested, and not only Fh but also Fa*Fg contributed significantly to the low BA in cynomolgus monkeys. When Fh was evaluated in in vitro experiments, it correlated well with the in vivo Fh. However, although the metabolic activities of CYP3A4 substrates were high in cynomolgus monkey intestinal microsomes, those of the other substrates were low or not detected. These findings suggested that the species differences and low BA in cynomolgus monkeys could be mostly attributed not only to hepatic first-pass metabolism but also to the intestinal absorption process.

Prediction of hepatic clearance in human from in vitro data for successful drug development

The in vivo metabolic clearance in human has been successfully predicted by using in vitro data of metabolic stability in cryopreserved preparations of human hepatocytes. In the predictions by human hepatocytes, the systematic underpredictions of in vivo clearance have been commonly observed among different datasets. The regression-based scaling factor for the in vitro-to-in vivo extrapolation has mitigated discrepancy between in vitro prediction and in vivo observation. In addition to the elimination by metabolic degradation, the important roles of transporter-mediated hepatic uptake and canalicular excretion have been increasingly recognized as a rate-determining step in the hepatic clearance. It has been, therefore, proposed that the in vitro assessment should allow the evaluation of clearances for both transporter(s)-mediated uptake/excretion and metabolic degradation. This review first outlines the limited ability of subcellular fractions such as liver microsomes to predict hepatic clearance in vivo. It highlights the advantages of cryopreserved human hepatocytes as one of the versatile in vitro systems for the prediction of in vivo metabolic clearance in human at the early development stage. The following section discusses the mechanisms underlying the systematic underprediction of in vivo intrinsic clearance by hepatocytes. It leads to the proposal for the assessment of hepatic uptake clearance as one of the kinetically important determinants for accurate predictions of hepatic clearance in human. The judicious combination of advanced technologies and understandings for the drug disposition allows us to rationally optimize new chemical entities to the drug candidate with higher probability of success during the clinical development.

The metabolism of the 5HT3antagonists ondansetron, alosetron and GR87442 I: A comparison ofin vitroandin vivometabolism andin vitroenzyme kinetics in rat, dog and human hepatocytes, microsomes and recombinant human enzymes

The metabolism of the structurally related 5HT3 antagonists ondansetron, alosetron and GR87442 in the rat, dog and human was determined in hepatocytes, liver microsomes and human recombinant microsomes. The profiles of phase I metabolites were similar in human hepatocytes and microsomes. The metabolites of all three compounds produced in rat, dog and human microsomes and hepatocytes were similar to those seen in vivo, with the major routes of metabolism being N-dealkylation and/or hydroxylation. There was more extensive metabolic processing in hepatocytes than in microsomes; however, sequential metabolism was less extensive in vitro compared with in vivo. The pharmacokinetics of the three 5HT3 antagonists investigated were dominated by CYP3A4 (and/or 2C9) compared with CYP1A2 in man, possibly determined by enzyme capacity rather than relative enzyme affinity. These data support the use of rat, dog and human hepatocytes for the prediction of in vivo metabolites of ondansetron, alosetron and GR87442.

Xenobiotic intrinsic clearance in freshly isolated hepatocytes from rainbow trout (Oncorhynchus mykiss): determination of trout hepatocellularity, optimization of cell concentrations and comparison of serum and serum-free incubations

Metabolism plays an important role in bioaccumulation of xenobiotics in fish. In vitro determination of xenobiotic intrinsic clearance (CLint) in trout hepatocytes and subsequent extrapolation to in vivo hepatic clearance (CLH) using the "well-stirred" liver model greatly improved our current practice of bioaccumulation assessment [Han, X., Nabb, D.L., Mingoia, R.T., Yang, C.H., 2007. Determination of xenobiotic intrinsic clearance in freshly isolated hepatocytes from rainbow trout (Oncorhynchus mykiss) and rat and its application in bioaccumulation assessment. Environ. Sci. Technol. 41, 3269-3276]. In an effort to further optimize this approach, we experimentally obtained the value of trout hepatocellularity (HT), a key scaling factor in the "well-stirred" liver model. HT was determined to be (540+/-12)x10(6)cells/g liver for male trout. We also investigated the potential effect of different cell concentrations on the determination of CL(int) values of molinate, 4,4-bis(dimethylamino)benzophenone, 4-nonylphenol, 2,4-di-tert-butylphenol, and benzo(a)pyrene. Linear relationships were established between clearance rates and cell concentrations at 1x10(6), 2x10(6), 5x10(6), and 10x10(6)cells/mL. This suggests that under our experimental conditions, CLint determination was independent of hepatocyte concentrations. In order to better understand the "in vitro binding" effect in in vitro-to-in vivo scaling, we obtained CLint values for the above-mentioned compounds in trout hepatocytes that were suspended in trout serum. Incubations in serum, in general, resulted relatively larger prediction of CLH values. Our findings suggest that in bioaccumulation assessment, the traditional medium incubation method offers a conservative estimate on fish metabolism of xenobiotics and the serum incubation approach could be used for certain classes of compounds that are of challenge for in silico prediction of their plasma and in vitro binding properties.

Prediction of pharmacokinetic drug-drug interactions using human hepatocyte suspension in plasma and cytochrome P450 phenotypic data. II. In vitro-in vivo correlation with ketoconazole

Traditional cytochrome P450 (P450) based drug-drug interaction (DDI) predictions are based on the ratio of an inhibitor's physiological concentration [I] and its inhibition constant K(i). Determining [I] at the enzymatic site, although critical for predicting clinical DDIs, remains a technical challenge. In our previous study, a novel approach using cryopreserved human hepatocytes suspended in human plasma was investigated to mimic the in vivo concentration of ketoconazole at the enzymatic site (Lu et al., 2007), effectively eliminating the estimation of the elusive [I] value. P450 inhibition in this system appears to model that in vivo. Using the ketoconazole inhibition information in a human hepatocyte-plasma suspension together with quantitative P450 phenotypic information, we successfully predicted the pharmacokinetic DDIs for a small set of drugs, such as theophylline, tolbutamide, omeprazole, desipramine, midazolam, loratadine, cyclosporine, and alprazolam, as well as an investigational compound. For the applicability of this model on a wider scale the in vitro-in vivo correlation data set needed to be expanded. However, for most drugs in the literature there is not enough quantitative information on the involvement of individual P450s to predict DDIs retrospectively. To facilitate that, in this study we determined quantitative P450 phenotyping for seven marketed drugs: budesonide, buprenorphine, loratadine, sirolimus, tacrolimus, docetaxel, and methylprednisolone. Augmentation of the new data set with the one generated previously produced broader a database that provided further support for the wider applicability of this approach using ketoconazole as a potent CYP3A inhibitor. This application is predicted to be equally effective with other P450 inhibitors that are not substrates of efflux pumps.

The metabolism of the 5HT3 antagonists, ondansetron, alosetron and GR87442 II: investigation into the in vitro methods used to predict the in vivo hepatic clearance of ondansetron, alosetron and GR87442 in the rat, dog and human

The in vitro clearances of the 5HT3 antagonists, ondansetron, alosetron and GR87442 were investigated. Intrinsic clearances using either metabolite formation or substrate depletion methods were equivalent (R2 = 0.95). Hepatocytes from preclinical species were superior to microsomes for the prediction of hepatic clearance (CL(H)), whereas the predictions from human microsomes and hepatocytes were similar. Using a non-restrictive model, seven of the nine CL(H) predictions using hepatocytes were within 2-fold of the in vivo CL(H) values. If the unbound fraction was included, the clearance of the compounds was generally under-predicted by both in vitro models. However, for the most metabolically stable compound, GR87442, the non-restrictive model over-predicted CLp. This and the possibility of extrahepatic metabolism indicate that the restrictive model is more appropriate for prediction of CL(H). The rank order of metabolic stability correlated with that in vivo. All three compounds were more metabolically stable in human than in the preclinical animal species examined.

Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies

This review brings you up-to-date with the hepatocyte research on: 1) in vitro-in vivo correlations of metabolism and clearance; 2) CYP enzyme induction, regulation, and cross-talk using human hepatocytes and hepatocyte-like cell lines; 3) the function and regulation of hepatic transporters and models used to elucidate their role in drug clearance; 4) mechanisms and examples of idiosyncratic and intrinsic hepatotoxicity; and 5) alternative cell systems to primary human hepatocytes. We also report pharmaceutical perspectives of these topics and compare methods and interpretations for the drug development process.

Evaluation of a basic physiologically based pharmacokinetic model for simulating the first-time-in-animal study

The objective of this study was to evaluate a physiologically based pharmacokinetic (PBPK) approach for predicting the plasma concentration-time curves expected after intravenous administration of candidate drugs to rodents. The predictions were based on a small number of properties that were either calculated based on the structure of the candidate drug (octanol:water partition coefficient, ionization constant(s)) or obtained from the typical high-throughput screens implemented in the early drug discovery phases (fraction unbound in plasma and hepatic intrinsic clearance). The model was tested comparing the predicted and the observed pharmacokinetics of 45 molecules. This dataset included six known drugs and 39 drug candidates from different discovery programs, so that the performance of the model could be evaluated in a real discovery case scenario. The plasma concentration-time curves were predicted with good accuracy, the pharmacokinetic parameters being on average two- to three-fold of actual values. Multivariate analysis was used for identifying the candidate properties which were likely associated to biased predictions. The application of this approach was found useful for the prioritization of the in vivo pharmacokinetics screens and the design of the first-time-in-animal studies.