Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs

Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

New framework for a non-animal approach adequately assures the safety of cosmetic ingredients - A case study on caffeine

This case study on the model substance caffeine demonstrates the viability of a 10-step read-across (RAX) framework in practice. New approach methodologies (NAM), including RAX and physiologically-based kinetic (PBK) modelling were used to assess the consumer safety of caffeine. Appropriate animal systemic toxicity data were used from the most relevant RAX analogue while assuming that no suitable animal toxicity data were available for caffeine. Based on structural similarities, three primary metabolites of the target chemical caffeine (theophylline, theobromine and paraxanthine) were selected as its most relevant analogues, to estimate a point of departure in order to support a next generation risk assessment (NGRA). On the basis of the pivotal mode of action (MOA) of caffeine and other methylxanthines, theophylline appeared to be the most potent and suitable analogue. A worst-case aggregate exposure assessment determined consumer exposure to caffeine from different sources, such as cosmetics and food/drinks. Using a PBK model to estimate human blood concentrations following exposure to caffeine, an acceptable Margin of Internal Exposure (MOIE) of 27-fold was derived on the basis of a RAX using theophylline animal data, which suggests that the NGRA approach for caffeine is sufficiently conservative to protect human health.

Overcoming the shortcomings of the extended-clearance concept: a framework for developing a physiologically-based pharmacokinetic (PBPK) model to select drug candidates involving transporter-mediated clearance

Introduction:Human pharmacokinetic (PK) prediction can be a significant challenge to drug candidates undergoing transporter-mediated clearance, when only animal data and in vitro human parameters are available in the drug discovery stage.Areas covered:The extended clearance concept (ECC) that incorporates the processes of hepatic uptake, passive diffusion, metabolism and biliary secretion has been adapted to determine the rate-determining process of hepatic clearance and drug-drug interactions (DDIs). However, since the ECC is derived from the well-stirred model and does not consider the liver as a drug distribution organ to reflect the time-dependent variation of drug concentrations between the liver and plasma, it can be misused for compound selection in drug discovery.Expert opinion:The PBPK model consists of a set of differential equations of drug mass balance, and can overcome the shortcomings of the ECC in predicting human PK. The predictability, relevance and reliability of the model and the scaling factors for IVIVE must be validated using either the measured liver concentrations or DDI data with known transporter inhibitors, or both, in monkeys. A human PBPK model that incorporates in vitro human data and SFs obtained from the validated monkey PBPK model can be used for compound selection in the drug discovery phase.

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.

Pharmacokinetic, metabolic stability, plasma protein binding and CYP450s inhibition/induction assessment studies of N-(2-pyridylmethyl)-2-hydroxiymethyl-1-pyrrolidinyl-4-(3-chloro-4-methoxy-benzylamino)-5-pyrimidine-carboxamide as potential type 5 phosphodiesterase inhibitors

N-(2-pyridylmethyl)-2-hydroxiymethyl-1-pyrrolidinyl-4-(3-chloro-4-methoxy-benzylamino)-5-pyrimidine-carboxamide (NHPPC) is a new potential of type 5 phosphodiesterase (PDE5) inhibitors, synthesized from the avanafil analogue for the treatment of erectile dysfunction. The targets of this article were to assess plasma protein binding, liver microsomal metabolic stability, inhibition and induction on cytochrome P450 isozymes and the pharmacokinetics of NHPPC. Equilibrium dialysis technique was applied to determine Plasma protein binding (PPB) and NHPPC was evaluated in male Sprague-Dawley rats and Beagle dogs in vivo pharmacokinetic. The NHPPC was highly bound to plasma proteins in rats, dogs and human tested and the mean values for PPB rate were 96.2%, 99.6% and 99.4%, respectively. After in vitro liver microsomes incubated for 60 min, the percent remaining of NHPPC was 42.8%, 0.8% and 42.0% in rats, dogs and human, respectively. In vitro intrinsic clearance was found to be 0.0233, 0.1204 and 0.0214 mL/min/mg protein in rat, dog and human liver microsomes of NHPPC, respectively. NHPPC showed no significant inhibitory effects on major CYP450 enzymes, and had no significant induction potential on CYP1A2 and CYP3A4. Following oral administration in rats and dogs, t max was 6 and 0.5 h, respectively. The clearance for NHPPC was 1.19 and 1.46 L/h/kg in rats and dogs, respectively. And absolute bioavailability in rat and dog were approximately 34.5% and 53.1%, respectively. These results showed that NHPPC has a good development prospect.

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

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

Structural and chemical insights into the covalent-allosteric inhibition of the protein kinase Akt

Structure-based driven synthesis and biological evaluation provide innovative novel covalent-allosteric Akt inhibitors.

The Ser/Thr kinase Akt (Protein Kinase B/PKB) is a master switch in cellular signal transduction pathways. Its downstream signaling influences cell proliferation, cell growth, and apoptosis, rendering Akt a prominent drug target. The unique activation mechanism of Akt involves a change of the relative orientation of its N-terminal pleckstrin homology (PH) and the kinase domain and makes this kinase suitable for highly specific allosteric modulation. Here we present a unique set of crystal structures of covalent-allosteric interdomain inhibitors in complex with full-length Akt and report the structure-based design, synthesis, biological and pharmacological evaluation of a focused library of these innovative inhibitors.

Misconceptions and issues regarding allometric scaling during the drug development process

INTRODUCTION

Allometry is the study of size and its consequences. The simple hypothesis of allometric scaling is that all physiological parameters are proportional to body size or body mass. This review examines the development of theory-based allometry or fixed exponents (0.75 and 1.0 for basal metabolic rate and volume, respectively) and the evidence for or against the theory. The main focus of this report is to show the readers that there is enough evidence from experimental data that negate the concept of theory-based allometry in biology, physiology, and pharmacokinetics. Areas covered: In this review, the history of the development of theoretical allometry and the strong evidence against theory-based allometry demonstrated by experimental data is provided. During drug development, allometry is applied to both inter-species (from animals to humans) and intra-species (adults to children) scaling. These two forms of allometric scaling in the context of theory-based allometry are discussed and provide insight on scientific progress that refute theory-based allometry. Expert opinion: Theory-based allometry is a mere theory and experimental data and real-life observations strongly negate the existence of such a theory. Pharmacostatistical and physiological models based on theory-based allometry can be misleading and incorrect because the theory-based allometric exponent 0.75 is not universal. The exponents of allometry are data dependent and are not fixed in the universe.

Development of a Physiologically Based Pharmacokinetic Model of Ethionamide in the Pediatric Population by Integrating Flavin-Containing Monooxygenase 3 Maturational Changes Over Time

Currently, ethionamide is the most frequently prescribed second-line antituberculosis drug in children. After extensive metabolism by flavin-containing monooxygenase (FMO) isoform 3 in the liver, the drug may exert cytotoxic effects. The comparison of children in different age groups revealed a significant age-related increase in ethionamide elimination in vivo. However, to date, the exact mechanism underlying this dynamic increase in ethionamide elimination has not been elucidated. We hypothesized that the age-dependent changes in ethionamide elimination were predominantly a result of the progressive increases in the expression and metabolic capacity of FMO3 during childhood. To test this hypothesis, a full physiologically based pharmacokinetic (PBPK) model of ethionamide was established and validated in adults through incorporation of comprehensive metabolism and transporter profiles, then expanded to the pediatric population through integration of FMO3 maturational changes over time. Thus, a good prediction PBPK model was validated successfully both in adults and children and applied to demonstrate the critical contribution of FMO3 in the mechanistic elimination pathway of ethionamide. In addition, a significant correlation between clearance and age was observed in children by accounting for ethionamide maturation, which could offer a mechanistic understanding of the age-associated changes in ethionamide elimination. In conclusion, this study underlines the benefits of in vitro-in vivo extrapolation and a quantitative PBPK approach for the investigation of transporter-enzyme interplay in ethionamide disposition and the demonstration of FMO3 ontogeny in children.

The Inhibition of Hepatic and Renal Glucuronidation of p-Nitrophenol and 4-Methylumbelliferone by Oil Palm Empty Fruit Bunch Lignin and Its Main Oxidation Compounds

Background:

In order to develop oil palm empty fruit bunch (EFB) lignin as a nutraceutical and health supplement, the investigation of its potential in interacting with other drugs via inhibition of drug-metabolizing enzymes (DMEs) would ensure product safety.

Objective:

The study was aimed to investigate the in vitro effect of oil palm EFB lignin and its main oxidation compounds on phase II DME UDP-glucuronosyltransferases (UGTs) in rat liver and kidney microsomes.

Materials and Methods:

The p-nitrophenol (p-NP) and 4-methylumbelliferone (4-MU) were employed as probe substrates in glucuronidation assays. The effect of soda oil palm EFB lignin on V_max, K_m, CL_int, K_i, and mode of inhibition of 4-MU glucuronidation in RLM was also determined.

Results:

The inhibitory potency of oil palm EFB lignin for both p-NP and 4-MU glucuronidation in rat liver microsome (RLM) and rat kidneys microsomes (RKM) was found to be in the rank order of soda > kraft > organosolv. However, the inhibitory potency of its main oxidation compounds were in the rank order of vanillin > syringaldehyde > p-hydroxybenzaldehyde. Soda oil palm EFB lignin exhibited mixed-type inhibition against 4-MU glucuronidation in RLM, showing the change in apparent V_max and with only a minor effect on K_m compared with control.

Conclusions:

The findings showed that effect of oil palm EFB lignin on both p-NP and 4-MU glucuronidation in RLM and RKM was enhanced by the presence of vanillin as well as flavonoids. Kinetic study showed that soda oil palm EFB lignin exhibited strong inhibition on UGT activity in RLM with mixed-type inhibition mode.

SUMMARY

The inhibitory potential of oil palm EFB lignin extracts for p-NP and 4-MU glucuronidation in RLM and RKM can be listed in the following rank order: soda > kraft > organosolv

The inhibitory potential of oil palm EFB lignin main oxidation compounds for p-NP and 4-MU glucuronidation in RLM and RKM can be listed in the following rank order: vanillin > syringaldehyde > p-hydroxybenzaldehyde

Results suggested that the effect of oil palm EFB lignin on p-NP and 4-MU glucuronidation activity in both RLM and RKM was enhanced by the presence of vanillin as well as total flavonoid content

Results also suggested that oil palm EFB lignin may inhibit glucuronidation of substrate by UGT enzymes, especially UGT1A6, particularly in rat liver

Abbreviations used:p-NP: p-Nitrophenol, 4-MU: 4-Methylumbelliferone, EFB: Empty fruit bunch, DME: Drug-metabolizing enzymes, UGT: UDPglucuronosyltransferase, V_max: Maximal reaction velocity, K_m: Michaelis-Menten constant, CLint: Intrinsic clearance, K_i: Dissociation constant of an inhibitor enzyme complex, 4-MUG: 4-Methylumbelliferone glucuronide, DMSO: Dimethyl sulfoxide, IC50: Half maximal inhibitory concentration, p-NPG: p-Nitrophenol glucuronide, RKM: Rat kidneys microsomes, RLM: Rat liver microsome, UDPGA: UDPglucuronic acid, TCA: trichloroacetic acid, MPA: mycophenolic acid

Implementation of a novel ultra fast metabolic stability analysis method using exact mass TOF-MS

AIM

Increasing numbers of compounds requiring stability data means highly optimized methods capable of rapid turnaround are desirable during early discovery. Materials and methods/results: An advanced, generic analytical workflow for metabolic stability has been developed that utilizing ballistic gradient LC (sub 1 min run times), exact mass TOF-MS (Waters Xevo-G2-XS Q-TOF) and automated data processing (Waters UNIFI software) allowed for rapid integration and interpretation of all data produced, eliminating the need for method development and manual processing. We can analyze and process 96 compounds across two species in quadruplicate in a 24-h period with no method development.

CONCLUSION

An advanced bioanalytical workflow has increased our capacity threefold and reduced our instrument/processing needs threefold.

3D engineered In vitro hepatospheroids for studying drug toxicity and metabolism

Drug toxicity is one of the reasons for late stage drug attrition, because of hepatotoxicity. Various in vitro liver models like primary human hepatocytes, immortalized human hepatic cell lines, liver slices and microsomes have been used; but limited by viability, hepatic gene expression and function. The 3D-engineered construct of hepatocyte-like-cells (HLCs) differentiated from stem cells, may provide a limitless source of hepatocytes with improved reproducibility. Towards this end, we used hepatospheroids (diameter=50-80μm) differentiated from human-umbilical-cord-mesenchymal stem cells (hUC-MSCs) on 3D scaffold GEVAC (Gelatin-vinyl-acetate-copolymer) as in vitro model for studying drug metabolism/toxicity. Our data demonstrated that hUC-MSCs-derived-hepatospheroids cultured on GEVAC expressed significantly higher drug-metabolizing enzymes (CYPs) both at mRNA and activity level compared to 2D culture, using HR-LC/MS. We further showed that hepatospheroids convert phenacetin (by CYP1A2) and testosterone (by CYP3A4) to their human-specific metabolites acetaminophen and 6β-hydroxytestosterone with a predictive clearance rate of 0.011ml/h/10⁶ cells and 0.021ml/h/10⁶ cells respectively, according to first-order kinetics. Hepatotoxicity was confirmed by exposing hepatospheroids to ethanol and acetaminophen; ROS generation, cell viability, cytoskeleton structure, elevation of liver function enzymes, i.e. AST and ALT, was analyzed. To the best of our knowledge, this is the first report to use hUC-MSCs-derived-hepatospheroids on GEVAC as in vitro model for drug metabolism/toxicity study; which can replace the conventional 2D-models used in drug development.

Prediction of drug disposition in diabetic patients by means of a physiologically based pharmacokinetic model

BACKGROUND AND OBJECTIVE

Accumulating evidence has shown that diabetes mellitus may affect the pharmacokinetics of some drugs, leading to alteration of pharmacodynamics and/or toxic effects. The aim of this study was to develop a novel physiologically based pharmacokinetic (PBPK) model for predicting drug pharmacokinetics in patients with type 2 diabetes mellitus quantitatively.

METHODS

Contributions of diabetes-induced alteration of physiological parameters including gastric emptying rates, intestinal transit time, drug metabolism in liver and kidney functions were incorporated into the model. Plasma concentration-time profiles and pharmacokinetic parameters of seven drugs (antipyrine, nisoldipine, repaglinide, glibenclamide, glimepiride, chlorzoxazone, and metformin) in non-diabetic and diabetic patients were predicted using the developed model. The PBPK model coupled with a Monte-Carlo simulation was also used to predict the means and variability of pharmacokinetic parameters.

RESULTS

The predicted area under the plasma concentration-time curve (AUC) and maximum (peak) concentration (C max) were reasonably consistent (<2-fold errors) with the reported values. Sensitivity analysis showed that gut transit time, hepatic enzyme activity, and renal function affected the pharmacokinetic characteristics of these drugs. Shortened gut transit time only decreased the AUC of controlled-released drugs and drugs with low absorption rates. Impairment of renal function markedly altered pharmacokinetics of drugs mainly eliminated via the kidneys.

CONCLUSION

All of these results indicate that the developed PBPK model can quantitatively predict pharmacokinetic alterations induced by diabetes.

Propofol-induced rno-miR-665 targets BCL2L1 and influences apoptosis in rodent developing hippocampal astrocytes

Propofol exerts neurotoxic effects on the developing mammalian brains, but the underlying molecular mechanism remains unclear. MicroRNAs (miRNAs) are a class of small noncoding RNAs that modulate gene expression at the post-transcriptional level. However, in specific types of neurocytes, the detailed functions of miRNAs were not entirely understood. We investigated the potential role of miRNAs in astrocyte pathogenesis caused by propofol. We performed genome-wide microRNA expression profiling in immature cultured hippocampal astrocytes by microarray analysis and predicted their targets and functions using bioinformatics tools. The functional effects of one differentially expressed miRNA were examined experimentally in relation to astrocyte viability. The results showed that 13 miRNAs were significantly differentially expressed after both short-term exposure to high-concentration propofol (10 μg/ml for 1h) and long-term exposure to low-concentration propofol (0.9 μg/ml for 48 h), including rno-miR-665, differing significantly between the 2. Bioinformatics predicted putative binding sites for rno-miR-665 existing in the 3'-untranslated region of Bcl-2-like protein 1 BCL2L1 (Bcl-xl) mRNA. Moreover, such relationship was assessed by luciferase reporter assay, qRT-PCR and western blot. Rno-miR-665 which was significantly up-regulated by propofol can suppress BCL2L1 and elevate cleaved caspase-3 expression in immature astrocytes in vitro. Apoptosis of developing hippocampal astrocytes was thus significantly influenced by propofol or rno-miR-665, or both. Taken together, rno-miR-665 is involved in the neurotoxicity induced by propofol via a caspase-3 mediated mechanism by negatively regulating BCL2L1. It might act as an alternative therapeutic target for treatment of neurological disorders in peadiatric prolonged anesthesia or sedation with propofol clinically.

Quantifying and Communicating Uncertainty in Preclinical Human Dose-Prediction

Human dose-prediction is fundamental for ranking lead-optimization compounds in drug discovery and to inform design of early clinical trials. This tutorial describes how uncertainty in such predictions can be quantified and efficiently communicated to facilitate decision-making. Using three drug-discovery case studies, we show how several uncertain pieces of input information can be integrated into one single uncomplicated plot with key predictions, including their uncertainties, for many compounds or for many scenarios, or both.

Toward modular biological models: defining analog modules based on referent physiological mechanisms

Background

Currently, most biomedical models exist in isolation. It is often difficult to reuse or integrate models or their components, in part because they are not modular. Modular components allow the modeler to think more deeply about the role of the model and to more completely address a modeling project’s requirements. In particular, modularity facilitates component reuse and model integration for models with different use cases, including the ability to exchange modules during or between simulations. The heterogeneous nature of biology and vast range of wet-lab experimental platforms call for modular models designed to satisfy a variety of use cases. We argue that software analogs of biological mechanisms are reasonable candidates for modularization. Biomimetic software mechanisms comprised of physiomimetic mechanism modules offer benefits that are unique or especially important to multi-scale, biomedical modeling and simulation.

Results

We present a general, scientific method of modularizing mechanisms into reusable software components that we call physiomimetic mechanism modules (PMMs). PMMs utilize parametric containers that partition and expose state information into physiologically meaningful groupings. To demonstrate, we modularize four pharmacodynamic response mechanisms adapted from an in silico liver (ISL). We verified the modularization process by showing that drug clearance results from in silico experiments are identical before and after modularization. The modularized ISL achieves validation targets drawn from propranolol outflow profile data. In addition, an in silico hepatocyte culture (ISHC) is created. The ISHC uses the same PMMs and required no refactoring. The ISHC achieves validation targets drawn from propranolol intrinsic clearance data exhibiting considerable between-lab variability. The data used as validation targets for PMMs originate from both in vitro to in vivo experiments exhibiting large fold differences in time scale.

Conclusions

This report demonstrates the feasibility of PMMs and their usefulness across multiple model use cases. The pharmacodynamic response module developed here is robust to changes in model context and flexible in its ability to achieve validation targets in the face of considerable experimental uncertainty. Adopting the modularization methods presented here is expected to facilitate model reuse and integration, thereby accelerating the pace of biomedical research.

The application of allometric scaling principles to predict pharmacokinetic parameters across species

INTRODUCTION

Interspecies allometric scaling provides a simple and fast option to interpolate or extrapolate drug dose or pharmacokinetic parameters to a species of interest. Over the years, new scaling methods have been developed in order to improve the performance of these predictions. It is critical to choose appropriate allometric scaling approach(es) to analyze the available pharmacokinetic data.

AREAS COVERED

This review provides updated information on the latest allometric scaling methods developed for the most frequently interpolated or extrapolated pharmacokinetic parameters. The different degrees of success and advantages/disadvantages of different methods are compared and contrasted. The pitfalls that affect the accuracy of prediction and the solutions to avoid the risk of prediction errors are discussed. The application of allometric scaling in veterinary medicine is presented.

EXPERT OPINION

Although interspecies allometric scaling needs further refinements and has limitations, it is still a potential tool and rational option for the estimate of pharmacokinetic parameters in species for which there are no data available or to better interpret preclinical efficacy and safety trials. Allometric scaling can offer insight into possible mechanisms of species-dependent drug disposition.

A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development

Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drug-disposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, half-life, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data.

Scaling and systems biology for integrating multiple organs-on-a-chip

Coupled systems of in vitro microfabricated organs-on-a-chip containing small populations of human cells are being developed to address the formidable pharmacological and physiological gaps between monolayer cell cultures, animal models, and humans that severely limit the speed and efficiency of drug development. These gaps present challenges not only in tissue and microfluidic engineering, but also in systems biology: how does one model, test, and learn about the communication and control of biological systems with individual organs-on-chips that are one-thousandth or one-millionth of the size of adult organs, or even smaller, i.e., organs for a milliHuman (mHu) or microHuman (μHu)? Allometric scaling that describes inter-species variation of organ size and properties provides some guidance, but given the desire to utilize these systems to extend and validate human pharmacokinetic and pharmacodynamic (PK/PD) models in support of drug discovery and development, it is more appropriate to scale each organ functionally to ensure that it makes the suitable physiological contribution to the coupled system. The desire to recapitulate the complex organ-organ interactions that result from factors in the blood and lymph places a severe constraint on the total circulating fluid (~5 mL for a mHu and ~5 μL for a μHu) and hence on the pumps, valves, and analytical instruments required to maintain and study these systems. Scaling arguments also provide guidance on the design of a universal cell-culture medium, typically without red blood cells. This review presents several examples of scaling arguments and discusses steps that should ensure the success of this endeavour.

Development of a hybrid physiologically based pharmacokinetic model with drug-specific scaling factors in rat to improve prediction of human pharmacokinetics

Accurate prediction of pharmacokinetics (PK) in humans has been a vital part of drug discovery. The aims of this study are to verify the usefulness of scaling factors for clearance (CL) and apparent volume of distribution at the steady state (Vss ) estimated from the difference between observed and predicted PK profiles in rats for human PK prediction, and to develop a novel hybrid physiologically based pharmacokinetic (PBPK) model with the two scaling factors. The human prediction accuracies for CL with in vitro-in vivo extrapolation and Vss with a tissue composition model were improved by using rat-scaling factors. This improvement was explainable by data that the scaling factors for CL and Vss in rats were correlated with those in humans. The predictability of plasma concentration-time profiles by the hybrid PBPK model incorporating two scaling factors was compared mainly with that by the conventional PBPK model. The hybrid PBPK model yielded higher prediction accuracy for plasma concentrations than the conventional method. Furthermore, we proposed a tiered approach using the three prediction methods, including the hybrid Dedrick approach, that were previously reported (Sayama H, Komura H, Kogayu M. 2013. Drug Metab Dispos 41:498-507), taking the available information in the individual stages of drug discovery and development into consideration.

Comprehensive assessment of human pharmacokinetic prediction based on in vivo animal pharmacokinetic data, part 1: volume of distribution at steady state

The authors present a comprehensive analysis on the estimation of volume of distribution at steady state (VD(ss) ) in human based on rat, dog, and monkey data on nearly 400 compounds for which there are also associated human data. This data set, to the authors- knowledge, is the largest publicly available, has been carefully compiled from literature reports, and was expanded with some in-house determinations such as plasma protein binding data. This work offers a good statistical basis for the evaluation of applicable prediction methods, their accuracy, and some methods-dependent diagnostic tools. The authors also grouped the compounds according to their charge classes and show the applicability of each method considered to each class, offering further insight into the probability of a successful prediction. Furthermore, they found that the use of fraction unbound in plasma, to obtain unbound volume of distribution, is generally detrimental to accuracy of several methods, and they discuss possible reasons. Overall, the approach using dog and monkey data in the íie-Tozer equation offers the highest probability of success, with an intrinsic diagnostic tool based on aberrant values (<0 or >1) for the calculated fraction unbound in tissue. Alternatively, methods based on dog data (single-species scaling) and rat and dog data (íie-Tozer equation with 2 species or multiple regression methods) may be considered reasonable approaches while not requiring data in nonhuman primates.

Human microdose evaluation of the novel EP1 receptor antagonist GSK269984A

AIM

The primary objective was to evaluate the pharmacokinetics (PK) of the novel EP(1) antagonist GSK269984A in human volunteers after a single oral and intravenous (i.v.) microdose (100 µg).

METHOD

GSK269984A was administered to two groups of healthy human volunteers as a single oral (n= 5) or i.v. (n= 5) microdose (100 µg). Blood samples were collected for up to 24 h and the parent drug concentrations were measured in separated plasma using a validated high pressure liquid chromatography-tandem mass spectrometry method following solid phase extraction.

RESULTS

Following the i.v. microdose, the geometric mean values for clearance (CL), steady-state volume of distribution (V(ss) ) and terminal elimination half-life (t(1/2) ) of GSK269984A were 9.8 l h(-1) , 62.8 l and 8.2 h. C(max) and AUC(0,∞) were 3.2 ng ml(-1) and 10.2 ng ml(-1)  h, respectively; the corresponding oral parameters were 1.8 ng ml(-1) and 9.8 ng ml(-1)  h, respectively. Absolute oral bioavailability was estimated to be 95%. These data were inconsistent with predictions of human PK based on allometric scaling of in vivo PK data from three pre-clinical species (rat, dog and monkey).

CONCLUSION

For drug development programmes characterized by inconsistencies between pre-clinical in vitro metabolic and in vivo PK data, and where uncertainty exists with respect to allometric predictions of the human PK profile, these data support the early application of a human microdose study to facilitate the selection of compounds for further clinical development.

Applications of human pharmacokinetic prediction in first-in-human dose estimation

Quantitative estimations of first-in-human (FIH) doses are critical for phase I clinical trials in drug development. Human pharmacokinetic (PK) prediction methods have been developed to project the human clearance (CL) and bioavailability with reasonable accuracy, which facilitates estimation of a safe yet efficacious FIH dose. However, the FIH dose estimation is still very challenging and complex. The aim of this article is to review the common approaches for FIH dose estimation with an emphasis on PK-guided estimation. We discuss 5 methods for FIH dose estimation, 17 approaches for the prediction of human CL, 6 methods for the prediction of bioavailability, and 3 tools for the prediction of PK profiles. This review may serve as a practical protocol for PK- or pharmacokinetic/pharmacodynamic-guided estimation of the FIH dose.

Design, synthesis and biological activity of original pyrazolo-pyrido-diazepine, -pyrazine and -oxazine dione derivatives as novel dual Nox4/Nox1 inhibitors

Pyrazolo-pyrido-diazepine, -pyrazine and -oxazine dione derivatives are new chemical entities with good and attractive druglikeness properties. A series of pyrazolo-pyrido-diazepine dione analogs demonstrated to be particularly amenable to lead optimization through a couple of cycles in order to improve specificity for isoforms Nox4 and Nox1 and had excellent pharmacokinetic parameters by oral route. Several molecules such as compound 7c proved to be highly potent in in vitro assays on human lung fibroblasts differentiation as well as in curative murine models of bleomycin-induced pulmonary fibrosis with superior efficiency over Pirfenidone. Pyrazolo-pyrido-diazepine dione derivatives targeting Nox4 and Nox1 isoforms appear highly promising therapeutics for the treatment of idiopathic pulmonary fibrosis.

A semiphysiologically based pharmacokinetic modeling approach to predict the dose-exposure relationship of an antiparasitic prodrug/active metabolite pair

Dose selection during antiparasitic drug development in animal models and humans traditionally has relied on correlations between plasma concentrations obtained at or below maximally tolerated doses that are efficacious. The objective of this study was to improve the understanding of the relationship between dose and plasma/tissue exposure of the model antiparasitic agent, pafuramidine, using a semiphysiologically based pharmacokinetic (semi-PBPK) modeling approach. Preclinical and clinical data generated during the development of pafuramidine, a prodrug of the active metabolite, furamidine, were used. A whole-body semi-PBPK model for rats was developed based on a whole-liver PBPK model using rat isolated perfused liver data. A whole-body semi-PBPK model for humans was developed on the basis of the whole-body rat model. Scaling factors were calculated using metabolic and transport clearance data generated from rat and human sandwich-cultured hepatocytes. Both whole-body models described pafuramidine and furamidine disposition in plasma and predicted furamidine tissue (liver and kidney) exposure and excretion profiles (biliary and renal). The whole-body models predicted that the intestine contributes significantly (30-40%) to presystemic furamidine formation in both rats and humans. The predicted terminal elimination half-life of furamidine in plasma was 3- to 4-fold longer than that of pafuramidine in rats (170 versus 47 h) and humans (64 versus 19 h). The dose-plasma/tissue exposure relationship for the prodrug/active metabolite pair was determined using the whole-body models. The human model proposed a dose regimen of pafuramidine (40 mg once daily) based on a predefined efficacy-safety index. A similar approach could be used to guide dose-ranging studies in humans for next-in-class compounds.

Interspecies scaling and prediction of human clearance: comparison of small- and macro-molecule drugs

Human clearance prediction for small- and macro-molecule drugs was evaluated and compared using various scaling methods and statistical analysis. Human clearance is generally well predicted using single or multiple species simple allometry for macro- and small-molecule drugs excreted renally. The prediction error is higher for hepatically eliminated small-molecules using single or multiple species simple allometry scaling, and it appears that the prediction error is mainly associated with drugs with low hepatic extraction ratio (Eh). The error in human clearance prediction for hepatically eliminated small-molecules was reduced using scaling methods with a correction of maximum life span (MLP) or brain weight (BRW). Human clearance of both small- and macro-molecule drugs is well predicted using the monkey liver blood flow method. Predictions using liver blood flow from other species did not work as well, especially for the small-molecule drugs.

Prediction of human oral plasma concentration-time profiles using preclinical data: comparative evaluation of prediction approaches in early pharmaceutical discovery

BACKGROUND AND OBJECTIVES

Empirically based methods remain one of our tools in human pharmacokinetic predictions. The Dedrick approach and the steady-state plasma drug concentration (C(ss))-mean residence time (MRT) approach are based on the assumption that concentration-time profiles are similar among species, including man, and that curves derived from a variety of animal species can be superimposed after mathematical transformation. In the Dedrick approach the transformation is based on the slope and intercept of the allometric relationship. The C(ss)-MRT approach is based on the implementation of measured animal and predicted human MRT and dose/volume of distribution at steady state (V(ss)). The aims of the present study were to compare the predictive performance of concentration-time profiles obtained by these approaches, to evaluate the prediction of individual pharmacokinetic parameters by these approaches and to further refine these approaches incorporating the experience from our previous work.

METHODS

A retrospective analysis using 35 proprietary compounds developed at Johnson & Johnson Pharmaceutical Research and Development was conducted to compare the accuracies of the Dedrick and C(ss)-MRT approaches for predicting oral concentration-time profiles and pharmacokinetic parameters in man. In the first step, input for the transformation was based on simple allometry. Then we assessed whether both methods could be fine-tuned by systematically incorporating correction factors (maximum life span potential, brain weight and plasma protein binding), depending on the interspecies relationship. In addition, for the C(ss)-MRT approach, we used formulas based on multivariate regression analysis as input for the transformation.

RESULTS

Inclusion of correction factors significantly improved the profile predictability for the Dedrick and C(ss)-MRT approaches. This was mainly linked to an improved prediction of terminal elimination half-life (t(½)), MRT and the ratio between the maximum plasma concentration and the concentration at the last observed time point (C(max)/C(last)). No significant differences were observed between the Dedrick approach with correction factors, the C(ss)-MRT approach with correction factors and the C(ss)-MRT approach, based on the regression equations.

CONCLUSIONS

Based on the dataset evaluated in this study, we demonstrated that human plasma concentration-time profiles and pharmacokinetic parameters could be predicted with the Dedrick and C(ss)-MRT approaches and that if correction factors were implemented, the predictions improved significantly. With the requirement of only a limited preclinical in vivo pharmacokinetic dataset, these empirical methods could offer potential in the early stages of drug discovery.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance

The objective of this study was to evaluate the performance of various allometric and in vitro-in vivo extrapolation (IVIVE) methodologies with and without plasma protein binding corrections for the prediction of human intravenous (i.v.) clearance (CL). The objective was also to evaluate the IVIVE prediction methods with animal data. Methodologies were selected from the literature. Pharmaceutical Research and Manufacturers of America member companies contributed blinded datasets from preclinical and clinical studies for 108 compounds, among which 19 drugs had i.v. clinical pharmacokinetics data and were used in the analysis. In vivo and in vitro preclinical data were used to predict CL by 29 different methods. For many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. In addition, 66 methods of predicting oral (p.o.) area under the curve (AUCp.o. ) were evaluated for 107 compounds using rational combinations of i.v. CL and bioavailability (F), and direct scaling of observed p.o. CL from preclinical species. Various statistical and outlier techniques were employed to assess the predictability of each method. Across methods, the maximum success rate in predicting human CL for the 19 drugs was 100%, 94%, and 78% of the compounds with predictions falling within 10-fold, threefold, and twofold error, respectively, of the observed CL. In general, in vivo methods performed slightly better than IVIVE methods (at least in terms of measures of correlation and global concordance), with the fu intercept method and two-species-based allometry (rat-dog) being the best performing methods. IVIVE methods using microsomes (incorporating both plasma and microsomal binding) and hepatocytes (not incorporating binding) resulted in 75% and 78%, respectively, of the predictions falling within twofold error. IVIVE methods using other combinations of binding assumptions were much less accurate. The results for prediction of AUCp.o. were consistent with i.v. CL. However, the greatest challenge to successful prediction of human p.o. CL is the estimate of F in human. Overall, the results of this initiative confirmed predictive performance of common methodologies used to predict human CL.

Comparative evaluation of US Food and Drug Administration and pharmacologically guided approaches to determine the maximum recommended starting dose for first-in-human clinical trials in adult healthy men

The authors compared US Food and Drug Administration (FDA) and 9 pharmacologically guided approaches (PGAs; simple allometry, maximum life span potential [MLP], brain weight, rule of exponent [ROE], two 2-sp methods and 3 one-sp methods) to determine the maximum recommended starting dose (MRSD) for first-in-human clinical trials in adult healthy men using 10 drugs. The ROE method as suggested by Mahmood and Balian1 gave the best prediction accuracy for a pharmacokinetic (PK) parameter. Values derived from clearance were consistently better than volume of distribution (Vd)-based methods and had lower root mean square error (RMSE) values. A pictorial method evaluation chart was developed based on fold errors for simultaneous evaluation of various methods. The one-sp method (rat) and the US FDA methods gave the highest prediction accuracy and low RMSE values, and the 2-sp methods gave the least prediction accuracy with high RMSE values. The ROE method gave more consistent predictions for PK parameters than other allometric methods. Despite this, the MRSD predictions were not better than US FDA methods, probably indicating that across-species variation in clearance may be higher than variation in no observed adverse effect level (NOAEL) and that PGA methods may not be consistently better than the NOAEL based methods.

First in class, potent, and orally bioavailable NADPH oxidase isoform 4 (Nox4) inhibitors for the treatment of idiopathic pulmonary fibrosis

We describe the design, synthesis, and optimization of first-in-class series of inhibitors of NADPH oxidase isoform 4 (Nox4), an enzyme implicated in several pathologies, in particular idiopathic pulmonary fibrosis, a life-threatening and orphan disease. Initially, several moderately potent pyrazolopyridine dione derivatives were found during a high-throughput screening campaign. SAR investigation around the pyrazolopyridine dione core led to the discovery of several double-digit nanomolar inhibitors in cell free assays of reactive oxygen species (ROS) production, showing high potency on Nox4 and Nox1. The compounds have little affinity for Nox2 isoform and are selective for Nox4/1 isoforms. The specificity of these compounds was confirmed in an extensive in vitro pharmacological profile, as well as in a counterscreening assay for potential ROS scavenging. Concomitant benefits are good oral bioavailability and high plasma concentrations in vivo, allowing further clinical trials for the potential treatment of fibrotic diseases, cancers, and cardiovascular and metabolic diseases.

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.

Pharmacokinetic allometric scaling of antibodies: application to the first-in-human dose estimation

The objectives of this study are: (i) to evaluate the predictive performance of interspecies scaling for antibodies to predict clearance, volume of distribution at steady state, and half-life in humans from animal data and (ii) to estimate first-in-human dose based on the predicted human clearance. Four methods were used to predict clearance in humans: (1) clearance versus body weight (simple allometry), (2) the product of clearance and maximum life-span potential (MLP) versus body weight, (3) the product of clearance and brain weight versus body weight, and (4) the application of a fixed exponent of 0.75. Based on the predicted human clearance, six methods were used to estimate the first-in-human dose. The predicted pharmacokinetic parameters and the estimated first-in-human dose of antibodies were compared with the observed human values. The results of the study indicated that the clearance of antibodies can be predicted with reasonable accuracy in humans and a good estimate of first human dose can be obtained from the predicted human clearance.

Interspecies allometric scaling

Lack of approved pharmaceutical agents and very limited pharmacokinetic data in the scientific literature for exotic, wildlife, and zoo species are a major issue for veterinarians treating these species. There are fewer than 15 compounds approved in the United States for zoo and wildlife species compared to nearly 300 drugs licensed for cattle. Zoo veterinarians are therefore required to extrapolate the use of approved agents (veterinary or human) to nonapproved species, often with little or no scientific basis to support drug or dose schedule selection. In general, species differences in drug absorption, metabolism, distribution, and excretion have been well documented for domestic species. However, there has been limited research to provide similar data for nondomestic species. Consequently, with the possible exception of pet bird species, there is little published information on the pharmacokinetic parameters of drugs in nondomestic species. Additionally, because of the commercial value of many zoo species, the traditional method of "trial and error" for drug and dose selection and related compliance issues is often inappropriate. There is an understandable concern, whereby the zoo veterinarian does not wish to be the first to administer an agent or formulation in an untested species. "One medicine" is a central concept in treating zoo species, in that vertebrate species are generally more similar than dissimilar. However, drug absorption can vary within as well as between species. Considering the anatomical differences between true monogastrics (canine and feline species), hind-gut fermentors (rodents, rabbits, horses, and elephants), fore-gut fermentors (Colobus monkeys and kangaroos), and ruminants (cattle, goats, sheep, and antelope), the potential for differences in pharmacokinetic profiles are marked. Moreover, there are potential differences between organisms in a single class. An example is the ability of several snake species to up- and down-regulate their digestive systems. This renders the time course of oral drug absorption dependent on both body temperature and time after feeding. Plasma protein binding may vary considerably between species and may also be temperature dependent. This is very significant when treating poikilothermic (reptiles, amphibians, and fish) species and when conducting pharmacokinetic studies with highly protein-bound drugs. The large body sizes of some zoo species create additional considerations for treatment with drugs and can place significant limitations on delivery of an effective drug dose.