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

Which Unbound Fraction Should We Use in the Well-Stirred Model for More Accurately Predicting Hepatic Clearance of Drugs for Humans?

As the hepatic clearance (CLH) of drugs becomes independent of hepatic blood flow rate, CLH depends primarily on intrinsic clearance (CLint). Incubations of microsomes or hepatocytes are commonly used to generate CLint. Therefore, CLint estimates corrected for binding to the in vitro systems and scaled to whole liver, are applied to a well-stirred liver model to obtain CLH predictions for drugs. In other words, CLint is extrapolated with the ratio of unbound fraction between the plasma (fup) and incubation medium (fuinc). However, this binding correction resulted to an important underprediction bias of CLH. Therefore, the approach considering fup and fuinc needs to be better understood for more precisely scaling CLint. The objective of this study was to explain the underprediction bias of CLH based on physicochemical properties of drugs. Analysis-ready datasets have been collected so that evaluation of the data generates a mechanistic understanding of the impact of unbound fraction on the prediction of CLH of human for 128 drugs. Experimental values of fuinc for liver are quantifying solely the binding to lipids in microsomes or hepatocytes in the absence of plasma proteins in the incubations. However, the experimental values of fup for plasma can estimate the binding to lipids and plasma proteins. Therefore, drugs binding primarily to lipids in the liver and plasma showed a less pronounced underprediction bias of CLH by using the ratios of fup/fuinc in the well-stirred model. In contrast, drugs binding primarily to the plasma proteins in the liver and plasma showed a larger underprediction bias of CLH. Furthermore, for the ionized drugs, values of fup and fuinc are not covering the pH gradient effect between plasma and hepatocytes, which also impacted the CLH predictions. For these reasons, a mechanistic approach was proposed to replace the conventional fup value with an adjusted fup (fu-adjusted) that accounts for differences in proteins/lipids binding and pH gradient effect between the liver and plasma. Hence, replacing fup with fu-adjusted did provide a universal and mechanisms-based approach removing the underprediction bias for all datasets of drugs. Overall, this study indicates which drug properties generated the largest underprediction bias of CLH and suggests that the Poulin et al. method referring to fu-adjusted could be the most proper unbound fraction to reduce that bias with the well-stirred model.

An overview of interpretability of two models of unbound fraction that are used in combination with the well-stirred model for predicting hepatic clearance of drugs

Hypothetical and experimental models of unbound fraction have been proposed to facilitate predicting the hepatic clearance (CLH) of drugs from values of intrinsic clearance for the unbound drug (CLint-in vitro-unbound) and the well-stirred model (WSM). The hypothetical model (fu-adjusted) is adjusting the unbound fractions determined in plasma in vitro to estimate the maximum unbound fractions at the hepatocytes if each drug-protein complex in plasma becomes fully dissociated at the membrane by any albumin (ALB)-facilitated hepatic uptake mechanism. The model of fu-adjusted is also adjusting the unbound fraction for a pH gradient effect across the membrane. Alternatively, the new experimental model (fu-dynamic) measures the unbound fractions resulting to the dynamic dissociation kinetics from proteins in the presence of plasma and a liver enzyme in an in vitro assay. The objective of this study was to conduct an in-depth analysis of previous CLH predictions made with these unbound fractions in a companion manuscript. Furthermore, a new dataset on transporter substrates was also included in this study. Finally, the physiological basis of fu-adjusted has been redefined to extend its applicability with more drugs. In this case, there are lower concentrations of binding proteins in liver versus plasma that could also explain the higher unbound fractions for that organ. The outcomes associated to additional analyses pointed out that fu-adjusted, again, generally provided the most accurate predictions of CLH because fu-dynamic has generated superior biases of underpredictions or overpredictions. For slowly metabolized drugs bound to ALB, fu-dynamic was definitively less accurate than fu-adjusted. For other drug properties, fu-dynamic fared better but it was still not generally more accurate than fu-adjusted. Furthermore, experimental values of fu-dynamic were sometimes incoherent. For example, drugs bound to alpha-acid glycoprotein (AGP) did not follow the principle of fu-dynamic (i.e., values of fu-dynamic did not correlate with values of CLint-in vitro-unbound) by contrast to those drugs bound to ALB. Therefore, the current experimental setting for fu-dynamic might be unsuitable in some circumstances. Overall, this study confirmed that calculated values of fu-adjusted were as accurate as experimental values of fu-dynamic and can even be more accurate. A guidance on which unbound fraction to use in the WSM is also provided.

How predictive are isolated perfused liver data of in vivo hepatic clearance? A meta-analysis of isolated perfused rat liver data

Isolated perfused rat liver (IPRL) experiments have been used to answer clearance-related questions, including evaluating the impact of pathological and physiological processes on hepatic clearance (CLH). However, to date, IPRL data has not been evaluated for in vivo CLH prediction accuracy.In addition to a detailed overview of available IPRL literature, we present an in-depth analysis of the performance of IPRL in CLH prediction.While the entire dataset poorly predicted CLH (GAFE = 3.2; 64% within 3-fold), IPRL conducted under optimal experimental conditions, such as in the presence of plasma proteins and with a perfusion rate within 2-fold of physiological liver blood flow and corrected for unbound fraction in the presence of red blood cells, can accurately predict rat CLH (GAFE = 2.0; 78% within 3-fold). Careful consideration of experimental conditions is needed to allow proper data analysis.Further, isolated perfused liver experiments in other species, including human livers, may allow us to address the current in vitro-in vivo disconnects of hepatic metabolic clearance and improve our methodology for CLH predictions.

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu-dynamic) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

After 50 Years of Hepatic Clearance Models, Where Should We Go from Here? Improvements and Implications for Physiologically Based Pharmacokinetic Modeling

There is overwhelming preference for application of the unphysiologic, well-stirred model (WSM) over the parallel tube model (PTM) and dispersion model (DM) to predict hepatic drug clearance, CLH , despite that liver blood flow is dispersive and closer to the DM in nature. The reasoning is the ease in computation relating the hepatic intrinsic clearance ( CLint ), hepatic blood flow ( QH ), unbound fraction in blood ( fub ) and the transmembrane clearances ( CLin and CLef ) to CLH for the WSM. However, the WSM, being the least efficient liver model, predicts a lower EH that is associated with the in vitro CLint ( Vmax / Km ), therefore requiring scale-up to predict CLH in vivo. By contrast, the miniPTM, a three-subcompartment tank-in-series model of uniform enzymes, closely mimics the DM and yielded similar patterns for CLint versus EH , substrate concentration [S] , and KL / B , the tissue to outflow blood concentration ratio. We placed these liver models nested within physiologically based pharmacokinetic models to describe the kinetics of the flow-limited, phenolic substrate, harmol, using the WSM (single compartment) and the miniPTM and zonal liver models (ZLMs) of evenly and unevenly distributed glucuronidation and sulfation activities, respectively, to predict CLH For the same, given CLint ( Vmax and Km ), the WSM again furnished the lowest extraction ratio ( EH,WSM = 0.5) compared with the miniPTM and ZLM (>0.68). Values of EH,WSM were elevated to those for EH, PTM and EH, ZLM when the Vmax s for sulfation and glucuronidation were raised 5.7- to 1.15-fold. The miniPTM is easily manageable mathematically and should be the new normal for liver/physiologic modeling. SIGNIFICANCE STATEMENT: Selection of the proper liver clearance model impacts strongly on CLH predictions. The authors recommend use of the tank-in-series miniPTM (3 compartments mini-parallel tube model), which displays similar properties as the dispersion model (DM) in relating CLint and [ S ] to CLH as a stand-in for the DM, which best describes the liver microcirculation. The miniPTM is readily modified to accommodate enzyme and transporter zonation.

A Nonsystematic Review of the Features of Pharmacotherapy in the Elderly at the Stage of Taking Medications

The human body is subservient to the age-related changes that affect not only the outer appearance but also organs and tissues. They also concern the processes of pharmacokinetics and dynamics. This means that the absorption, distribution, and metabolism of drugs used by an elderly patient will be slowed down. Therefore, it becomes necessary to prescribe a special dosing regimen for older people. An actual problem is also that, with age, many patients require more drugs than young people. This increases the risk of side effects because many drugs are difficult to combine with each other. Pharmacy of our time is a science that is constantly developing and modernizing, which allows changing therapy for the better: prescribing drugs in smaller quantities, with a smaller range of adverse reactions and a better effect. The aim of the work is to analyze the impact and relationship of older age on the pharmacotherapy of patients, as well as the risks of drug-induced diseases. To carry out this work, such research methods as analysis, synthesis, comparative analysis, classification, analogy, abstraction, induction, and generalization were used. The features of the stages of pharmacokinetics and pharmacodynamics in the elderly were considered; we studied the data of clinical studies and literature in geriatrics; and the effects of a combination or increase in the dosage of drugs have been noted. After the collection of research data and the analysis, it turned out that it is real and necessary to avoid the negative consequences of pharmacotherapy in elderly and senile patients. Considering the natural age-related changes in the condition and functioning of organs and systems, constantly monitoring the effectiveness of drugs and undesirable reactions of the body to them, adjusting treatment protocols will have a favorable result and help optimize pharmacotherapy for the elderly and reduce the risk of side effects and diseases caused by medications.

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.

Evidence of the Need for Modified Well-stirred Model in In Vitro to In Vivo Extrapolation

In vitro to in vivo extrapolation (IVIVE), an approach for hepatic clearance (CL_H) prediction used worldwide, remains controversial due to systematic underprediction. Among the various probable factors, the original assumption of the hepatic mathematical model (i.e., the well-stirred model, WSM) may become problematic, leading to the underestimation of drug CL_H. Having a similar prerequisite that the well-stirred conditions are homogenous with perfectly mixed reactants, but using a different driving concentration, the modified well-stirred model (MWSM) stands apart from the WSM. However, we believe that both models should coexist so that the entire well-stirred scenario can be completely illustrated. Consequently, we collected published data from the literature and employed a logistic regression method to differentiate the optimal timing of use between WSM and MWSM in drug CL_H prediction. Generally, variances adopted in the regression, including partition coefficient (logP), fraction unbound (fu), volumes of distribution at steady-state (Vss), and mean residence time (MRT), corresponded to our assumption when protein-facilitated uptake was considered. Furthermore, a new empirical approach was introduced to allow practical use of the MWSM. The results showed that this model could provide a more precise prediction compared to previous empirical approaches. Therefore, these preliminary results not only delineated a more detailed structure and mechanism of MWSM but also highlighted its necessity and potential.

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.

Free Drug Theory - No Longer Just a Hypothesis?

The Free Drug Hypothesis is a well-established concept within the scientific lexicon pervading many areas of Drug Discovery and Development, and yet it is poorly defined by virtue of many variations appearing in the literature. Clearly, unbound drug is in dynamic equilibrium with respect to absorption, distribution, metabolism, elimination, and indeed, interaction with the desired pharmacological target. Binding interactions be they specific (e.g. high affinity) or nonspecific (e.g. lower affinity/higher capacity) are governed by the same fundamental physicochemical tenets including Hill-Langmuir Isotherms, the Law of Mass Action and Drug Receptor Theory. With this in mind, it is time to recognise a more coherent version and consider it the Free Drug Theory and a hypothesis no longer. Today, we have the experimental and modelling capabilities, pharmacological knowledge, and an improved understanding of unbound drug distribution (e.g. Kp_uu) to raise the bar on our understanding and analysis of experimental data. The burden of proof should be to rule out mechanistic possibilities and/or experimental error before jumping to the conclusion that any observations contradict these fundamentals.

The structural basis for high affinity binding of α1-acid glycoprotein to the potent antitumor compound UCN-01

The α1-acid glycoprotein (AGP) is an abundant blood plasma protein with important immunomodulatory functions coupled to endogenous and exogenous ligand-binding properties. Its affinity for many drug-like structures, however, means AGP can have a significant effect on the pharmokinetics and pharmacodynamics of numerous small molecule therapeutics. Staurosporine, and its hydroxylated forms UCN-01 and UCN-02, are kinase inhibitors that have been investigated at length as antitumour compounds. Despite their potency, these compounds display poor pharmokinetics due to binding to both AGP variants, AGP1 and AGP2. The recent renewed interest in UCN-01 as a cytostatic protective agent prompted us to solve the structure of the AGP2–UCN-01 complex by X-ray crystallography, revealing for the first time the precise binding mode of UCN-01. The solution NMR suggests AGP2 undergoes a significant conformational change upon ligand binding, but also that it uses a common set of sidechains with which it captures key groups of UCN-01 and other small molecule ligands. We anticipate that this structure and the supporting NMR data will facilitate rational redesign of small molecules that could evade AGP and therefore improve tissue distribution.

Into the Labyrinth of the Lipocalin α1-Acid Glycoprotein

α₁-acid glycoprotein (AGP), also known as Orosomucoid (ORM), belongs to the Lipocalin protein family and it is well-known for being a positive acute-phase protein. AGP is mostly found in plasma, with the liver as main contributor, but it is also expressed in other tissues such as the brain or the adipose tissue. Despite the vast literature on AGP, the physiological functions of the protein remain to be elucidated. A large number of activities mostly related to protection and immune system modulation have been described. Recently created AGP-knockout models have suggested novel physiological roles of AGP, including regulation of metabolism. AGP has an outstanding ability to efficiently bind endogenous and exogenous small molecules that together with the complex and variable glycosylation patterns, determine AGP functions. This review summarizes and discusses the recent findings on AGP structure (including glycans), ligand-binding ability, regulation, and physiological functions of AGP. Moreover, this review explores possible molecular and functional connections between AGP and other members of the Lipocalin protein family.

A New Guidance for the Prediction of Hepatic Clearance in the Early Drug Discovery and Development from the in Vitro-to-in Vivo Extrapolation Method and an Approach for Exploring Whether an Albumin-Mediated Hepatic Uptake Phenomenon Could be Present Under in Vivo Conditions

The in vitro-to-in vivo extrapolation (IVIVE) methods for predicting the hepatic clearance (CL) of drugs based on microsomal or hepatocyte data have certainly advanced; however, there is still place for improving the extrapolations from in vitro assays containing no plasma proteins. Accordingly, there is a discussion on whether the free drug hypothesis or an albumin (ALB)-mediated hepatic uptake phenomenon is the best scaling method. Therefore, the objectives of this study were to guide the prediction of CL and to diagnose which scaling method between the free drug hypothesis and ALB-mediated uptake could be more accurate; this, irrespective of the mechanism(s) governing CL if the drugs can get to the hepatocyte membrane. The analysis of several datasets demonstrated that almost all values of CL in vivo fall within the two calculated values of CL use as boundaries from: 1) the free drug hypothesis, and 2) ALB-mediated uptake. The average value from these two CL boundaries predicted the CL in vivo with an incredible accuracy. Validating these boundaries in preclinical species prior going to human as well as considering the fractional binding in plasma increased the accuracy. Overall, this study is another step towards guiding the CL prediction in drug discovery and development.