Prediction Of Human Hepatic Clearance Research Articles

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).

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. 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. 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. 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.

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

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

Empirical and theoretical approaches for the prediction of human hepatic clearance using chimeric mice with humanised liver: The use of physiologically based scaling, a novel solution for potential overprediction due to coexisting mouse metabolism

1. Chimeric mice are immunodeficient mice in which the majoity of the hepatic parenchymal cells are replaced with human hepatocyes. 2. Following intravenous administration of 24 model compounds to control and chimeric mice, human hepatic clearance (CLh) was predicted using the single-species allometric scaling (SSS) method. Predictability of the chimeric mice was better than that of the control mice. 3. Human CLh was predicted by the physiologically based scaling (PBS) method, wherein observed CLh in chimeric mice was first converted to intrinsic CLh (CLh,int). As the liver of chimeric mice contains remaining mouse hepatocytes, CLh,int was corrected by in vitro CLh ratios of mouse to human hepatocytes according to their hepatocyte replacement index. Further, predicted human CLh was calculated based on an assumption that CLh,int in chimeric mice normalised for their liver weight was equal to CLh,int per liver weight in humans. Consequently, better prediction performance was observed with the use of PBS method than the SSS method. 4. SSS method is an empirical method, and effects of coexisting mouse metabolism cannot be avoided. However, the PBS method with in vitro CLh correction might be a potential solution and may expand the application of chimeric mice in new drug development.

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.

Albumin-Mediated Uptake Improves Human Clearance Prediction for Hepatic Uptake Transporter Substrates Aiding a Mechanistic In Vitro-In Vivo Extrapolation (IVIVE) Strategy in Discovery Research.

This study focused on exploring various in vitro to in vivo extrapolation (IVIVE) approaches with the primary goal of improving human hepatic clearance (CL) prediction for OATP substrates. To that effect, the impact of albumin-mediated uptake in human hepatocytes was investigated. In vitro hepatic uptake assay using suspended human hepatocytes was performed with 16 selected OATP substrates to determine the uptake CL in the absence and presence of 4% BSA and unbound hepatocyte to media partition coefficient (Kpuu). Substantial enhancement of the unbound uptake CL (PSu,inf) was observed in the presence of 4% BSA, demonstrating "albumin-mediated" uptake. Prediction of human hepatic CL was performed using two non-traditional IVIVE approaches: initial uptake CL (PSu,inf) and intrinsic metabolic CL (CLint,met) corrected by Kpuu based on extended clearance concept. Compared to traditional IVIVE using CLint,met only, the two tested IVIVE approaches significantly improved the prediction of human hepatic CL. Particularly, direct extrapolation from PSu,inf (+BSA) showed the most robust correlation with in vivo human hepatic CL for all 16 compounds with bias of 1.9-2.0 for two lots of human hepatocytes, respectively. In addition, PSu,inf (+BSA) and Kpuu were also determined in suspended cynomolgus monkey hepatocytes. Prediction of monkey hepatic CL was improved by both approaches, although with more bias compared to human. These results suggested supplementing 4% BSA in human hepatocyte uptake assay provides a useful tool to characterize hepatic uptake CL for OATP substrates, enabling more accurate human CL prediction without any empirical scaling factor (ESF).

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.

Prediction of human hepatic clearance for cytochrome P450 substrates via a new culture method using the collagen vitrigel membrane chamber and PXB-cells

Prediction of human hepatic clearance for cytochrome P450 substrates via a new culture method using the collagen vitrigel membrane chamber and PXB-cells

Application of ICA-CMAC in the Prediction of Human Hepatic Clearance

In this paper, a novel improved Credit Assigned CMAC (ICA-CMAC) is designed based on the concept of credit to enhance the performance of the traditional CMAC. Then ICA-CMAC is used to predict the human hepatic clearance according to in-vitro data of drugs. The experiment results show that the prediction by ICA-CMAC is faster and more accurate and can be thought as a new and effective way for drug metabolism prediction.

Use of intrinsic clearance for prediction of human hepatic clearance

Importance of the field: The use of intrinsic metabolic stability/clearance and other in vitro pharmacokinetic data for the selection of drug candidates for clinical evaluation during discovery lead optimization has become one of the primary focuses of research organizations involved in new drug discovery. Using intrinsic clearance determined from human liver microsomal preparations and/or hepatocyte to predict human clearance has become more acceptable.Areas covered in this review: This review focuses on the current methods for determining intrinsic clearance and scaling to predict human hepatic clearance, and novel physiologically-based models for improvement of human hepatic clearance prediction. Published microsomal metabolic stability data and in-house hepatocyte clearance data were compared with published in vivo human hepatic clearance data. Various scaling models and the effect of protein binding were examined.What the reader will gain: Use of a novel microfluidic model and other physiologically-based models are presented. Microsomal metabolic clearance requires correction for protein binding and in vitro microsomal binding in order to better predict in vivo hepatic clearance of compounds that are mainly eliminated by hepatic metabolism.Take home message: Metabolic clearance obtained using hepatocytes may work well in combination with the well-stirred model. Novel models incorporating flow and protein binding in the system may be the most complete models for prediction of human in vivo metabolism.

Prediction of Human Hepatic Clearance Using an In Vitro Plated Hepatocyte Clearance Model

Previously we have used human hepatocytes in suspension by measuring the parent loss for prediction of metabolic clearance according to a 1(st)-order kinetic model. In this study, we evaluated a novel integrative approach using plated human hepatocytes to include both uptake processes and metabolism in a single assay. Test articles were added in the medium, and the intrinsic clearance was determined based on the disappearance of the parent compound from the medium. Three different methods: direct, well-stirred, and parallel tube were tested for scaling purpose. With 30 randomly selected compounds with clinical clearance data, the scaled clearance showed reasonable linear correlation with r(2) values of 0.67, 0.72, and 0.70 for direct, well-stirred and parallel tube models, respectively. When human serum albumin (HSA) was added to the incubation medium a shift to lower in vitro clearance was observed for most of the compounds, suggesting that protein binding may have an effect on the metabolic clearance. In the presence of 4% of HSA, which is equivalent to the albumin concentration in the human plasma, the in vitro clearance data have the best prediction of human clearance when using the well-stirred method, followed by the parallel tube method and direct method. This study demonstrates the utility of using plated human hepatocyte as an integrated system for the prediction of human metabolic clearance. In addition, evaluation of the protein binding shift in the clearance showed that a significant number of compounds may not follow the equilibrium assumption according to the well-stirred model.

Methodological Uncertainty in Quantitative Prediction of Human Hepatic Clearance from In Vitro Experimental Systems

Mechanistic prediction of unbound drug clearance from human hepatic microsomes and hepatocytes correlates with in vivo clearance but is both systematically low (10 - 20 % of in vivo clearance) and highly variable, based on detailed assessments of published studies. Metabolic capacity (Vmax) of commercially available human hepatic microsomes and cryopreserved hepatocytes is log-normally distributed within wide (30 - 150-fold) ranges; Km is also log-normally distributed and effectively independent of Vmax, implying considerable variability in intrinsic clearance. Despite wide overlap, average capacity is 2 - 20-fold (dependent on P450 enzyme) greater in microsomes than hepatocytes, when both are normalised (scaled to whole liver). The in vitro ranges contrast with relatively narrow ranges of clearance among clinical studies. The high in vitro variation probably reflects unresolved phenotypical variability among liver donors and practicalities in processing of human liver into in vitro systems. A significant contribution from the latter is supported by evidence of low reproducibility (several fold) of activity in cryopreserved hepatocytes and microsomes prepared from the same cells, between separate occasions of thawing of cells from the same liver. The large uncertainty which exists in human hepatic in vitro systems appears to dominate the overall uncertainty of in vitro-in vivo extrapolation, including uncertainties within scaling, modelling and drug dependent effects. As such, any notion of quantitative prediction of clearance appears severely challenged.

PREDICTION OF IN VIVO HUMAN HEPATIC CLEARANCE IN DRUG DISCOVERY

We have investigated a quantitative prediction of in vivo human hepatic clearance from in vitro experiments. In vivo intrinsic clearance (CLint, in vivo) were compared with in vitro intrinsic clearance (CLint, in vitro) from in vitro metabolism data obtained by using liver microsomes focusing on P450 metabolism in rats, dogs and humans. The scaling factor (CLint, in vivo/CLint, in vitro) were different among the model compounds, while most of the animal scaling factors were within 2-fold of the values in humans. When human CLint, in vitro values were compared with the actual CLint, in vivo, correlations were not necessarily good. By contrast, using human CLint, in vitro corrected with the animal scaling factor yielded better predictions of CLint, in vivo that were mostly within 2-fold of actual values. Further, CLint, in vivo were compared with CLint, in vitro from in vitro metabolismd ata obtained by using rat fresh and human cryopreserved hepatocytes. Human CLint, in vitro corrected with the rat scaling factor yielded good predictions of CLint, in vivo that were mostly less than several-fold of actual values. This method thus provides a more reliable prediction of human hepatic clearance and will be useful in drug discovery.