Accurate prediction of Kp,uu,brain based on experimental measurement of Kp,brain and computed physicochemical properties of candidate compounds in CNS drug discovery

A mathematical equation model was developed by building the relationship between the fu,b/fu,p ratio and the computed physicochemical properties of candidate compounds, thereby predicting Kp,uu,brain based on a single experimentally measured Kp,brain value. A total of 256 compounds and 36 marketed published drugs including acidic, basic, neutral, zwitterionic, CNS-penetrant, and non-CNS penetrant compounds with diverse structures and physicochemical properties were involved in this study. A strong correlation was demonstrated between the fu,b/fu,p ratio and physicochemical parameters (CLogP and ionized fraction). The model showed good performance in both internal and external validations. The percentages of compounds with Kp,uu,brain predictions within 2-fold variability were 80.0 %-83.3 %, and more than 90 % were within a 3-fold variability. Meanwhile, "black box" QSAR models constructed by machine learning approaches for predicting fu,b/fu,p ratio based on the chemical descriptors are also presented, and the ANN model displayed the highest accuracy with an RMSE value of 0.27 and 86.7 % of the test set drugs fell within a 2-fold window of linear regression. These models demonstrated strong predictive power and could be helpful tools for evaluating the Kp,uu,brain by a single measurement parameter of Kp,brain during lead optimization for CNS penetration evaluation and ranking CNS drug candidate molecules in the early stages of CNS drug discovery.

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

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

Metabolism Characterization and Chemical and Plasma Stability of Casearin B and Caseargrewiin F

Oral preparations of Casearia sylvestris (guacatonga) are used as antacid, analgesic, anti-inflammatory, and antiulcerogenic medicines. The clerodane diterpenes casearin B and caseargrewiin F are major active compounds in vitro and in vivo. The oral bioavailability and metabolism of casearin B and caseargrewiin F were not previously investigated. We aimed to assess the stability of casearin B and caseargrewiin F in physiological conditions and their metabolism in human liver microsomes. The compounds were identified by UHPLC-QTOF-MS/MS and quantified by validated LC-MS methods. The stability of casearin B and caseargrewiin F in physiological conditions was assessed in vitro. Both diterpenes showed a fast degradation (p < 0.05) in simulated gastric fluid. Their metabolism was not mediated by cytochrome P-450 enzymes, but the depletion was inhibited by the esterase inhibitor NaF. Both diterpenes and their dialdehydes showed a octanol/water partition coefficient in the range of 3.6 to 4.0, suggesting high permeability. Metabolism kinetic data were fitted to the Michaelis-Menten profile with KM values of 61.4 and 66.4 µM and Vmax values of 327 and 648 nmol/min/mg of protein for casearin B and caseargrewiin F, respectively. Metabolism parameters in human liver microsomes were extrapolated to predict human hepatic clearance, and suggest that caseargrewiin F and casearin B have a high hepatic extraction ratio. In conclusion, our data suggest that caseargrewiin F and casearin B present low oral bioavailability due to extensive gastric degradation and high hepatic extraction.

Significance of Basal Membrane Permeability of Epithelial Cells in Predicting Intestinal Drug Absorption

Drug absorption from the gastrointestinal tract is often restricted by efflux transport by P-glycoprotein (P-gp) and metabolism by CYP3A4. Both localize in the epithelial cells, and thus, their activities are directly affected by the intracellular drug concentration, which should be regulated by the ratio of permeability between apical (A) and basal (B) membranes. In this study, using Caco-2 cells with forced expression of CYP3A4, we assessed the transcellular permeation of A-to-B and B-to-A directions and the efflux from the preloaded cells to both sides of 12 representative P-gp or CYP3A4 substrate drugs and obtained the parameters for permeabilities, transport, metabolism, and unbound fraction in the enterocytes (f_ent) using simultaneous and dynamic model analysis. The membrane permeability ratios for B to A (R_BA) and f_ent varied by 8.8-fold and by more than 3000-fold, respectively, among the drugs. The R_BA values for digoxin, repaglinide, fexofenadine, and atorvastatin were greater than 1.0 (3.44, 2.39, 2.27, and 1.90, respectively) in the presence of a P-gp inhibitor, thus suggesting the potential involvement of transporters in the B membrane. The Michaelis constant for quinidine for P-gp transport was 0.077 µM for the intracellular unbound concentration. These parameters were used to predict overall intestinal availability (F_AF_G) by applying an intestinal pharmacokinetic model, advanced translocation model (ATOM), in which permeability of A and B membranes accounted separately. The model predicted changes in the absorption location for P-gp substrates according to its inhibition, and F_AF_G values of 10 of 12 drugs, including quinidine at varying doses, were explained appropriately. SIGNIFICANCE STATEMENT: Pharmacokinetics has improved predictability by identifying the molecular entities of metabolism and transport and by using mathematical models to appropriately describe drug concentrations at the locations where they act. However, analyses of intestinal absorption so far have not been able to accurately consider the concentrations in the epithelial cells where P-glycoprotein and CYP3A4 exert effects. In this study, the limitation was removed by measuring the apical and basal membrane permeability separately and then analyzing these values using new appropriate models.

Data on ADME parameters of bisphenol A and its metabolites for use in physiologically based pharmacokinetic modelling

The paper presents the collection of physicochemical parameters of bisphenol A (BPA) and its sulfate (BPAS) and glucuronide (BPAG) conjugates, accompanied by data characterizing their absorption, distribution, metabolism and excretion (ADME) behavior following oral administration of BPA. The data were collected from open literature sources and publicly available databases. Additionally, data calculated by using the MarvinSketch 18.30.0 software or predicted by relevant QSAR models built in Simcyp® Simulator were also used. All data were analysed and are fit for purpose if necessary to ensure a reliable prediction of pharmacokinetics of BPA and its conjugates. The data selection process and reasoning for fitting is provided to allow critical assessment and to ensure data transparency. Finally, the sensitivity analysis was performed to assess the influence of the selected parameters on the PBPK model predictions.

Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models

Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fu_mic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r²=0.86) or mouse (r²=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r² of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fu_mic using four different in silico models for a set of 53-60 compounds. The correlation (r²) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r²=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r²<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.

How Science Is Driving Regulatory Guidances

This chapter provides regulatory perspectives on how to translate in vitro drug metabolism findings into in vivo drug-drug interaction (DDI) predictions and how this affects the decision of conducting in vivo DDI evaluation. The chapter delineates rationale and analyses that have supported the recommendations in the U.S. Food and Drug Administration (FDA) DDI guidances in terms of in vitro-in vivo extrapolation of cytochrome P450 (CYP) inhibition-mediated DDI potential for investigational new drugs and their metabolites as substrates or inhibitors. The chapter also describes the framework and considerations to assess UDP-glucuronosyltransferase (UGT) inhibition-mediated DDI potential for drugs as substrates or inhibitors. The limitations of decision criteria and further improvements needed are also discussed. Case examples are provided throughout the chapter to illustrate how decision criteria have been utilized to evaluate in vivo DDI potential from in vitro data.

Exploration of inhibition potential of isoniazid and its metabolites towards CYP2E1 in human liver microsomes through LC-MS/MS analysis

Isoniazid (INH) is the first-line anti-tubercular drug that is used both for the prophylaxis as well as the treatment of tuberculosis (TB). The patients with TB are more vulnerable to secondary infections and other health complications, hence, they are usually administered a cocktail of drugs. This increases the likelihood of drug-drug interactions (DDIs). INH is clinically proven to interact with drugs like phenytoin, carbamazepine, diazepam, triazolam, acetaminophen, etc. Most of such clinical observations have been supported by in vitro inhibition studies involving INH and cytochrome P450 (CYP) enzymes. A few published in vitro studies have explored the CYP2E1 inhibition potential of INH to explain its interactions with acetaminophen and other CY2E1 substrates, such as chlorzoxazone, but none of them were able to demonstrate any significant inhibition of the enzyme by the drug. It was reported that metabolites of INH, such as acetylhydrazine and hydrazine, were bioactivated by CYP2E1, highlighting that perhaps the drug metabolites were responsible for the mechanism based inhibition (MBI) of the enzyme. Therefore, the purpose of this investigation was to explore CYP2E1 enzyme inhibition potential of INH and its four major metabolites, viz., acetylisoniazid, isonicotinic acid, acetylhydrazine and hydrazine, using human liver microsomes (HLM). Additionally, we determined the fraction unbound in microsomal incubation (fu_mic) for all the five compounds using equilibrium dialysis assay. We observed that INH and its metabolites had lower propensity for microsomal binding, and the metabolites also lacked the potential to inhibit CYP2E1 enzyme, either by direct inhibition or through MBI. This suggests involvement of some other mechanism to explain interactions of INH with CY2E1 substrates, signifying need of further exploration.

Consideration of the Unbound Drug Concentration in Enzyme Kinetics

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system(s) under investigation. As a consequence, the apparent kinetic parameters, such as K_m or K_i, that are derived can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components which can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

Evidence-based strategies for the characterisation of human drug and chemical glucuronidation in vitro and UDP-glucuronosyltransferase reaction phenotyping

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily contribute to the elimination of drugs from almost all therapeutic classes. Awareness of the importance of glucuronidation as a drug clearance mechanism along with increased knowledge of the enzymology of drug and chemical metabolism has stimulated interest in the development and application of approaches for the characterisation of human drug glucuronidation in vitro, in particular reaction phenotyping (the fractional contribution of the individual UGT enzymes responsible for the glucuronidation of a given drug), assessment of metabolic stability, and UGT enzyme inhibition by drugs and other xenobiotics. In turn, this has permitted the implementation of in vitro - in vivo extrapolation approaches for the prediction of drug metabolic clearance, intestinal availability, and drug-drug interaction liability, all of which are of considerable importance in pre-clinical drug development. Indeed, regulatory agencies (FDA and EMA) require UGT reaction phenotyping for new chemical entities if glucuronidation accounts for ≥25% of total metabolism. In vitro studies are most commonly performed with recombinant UGT enzymes and human liver microsomes (HLM) as the enzyme sources. Despite the widespread use of in vitro approaches for the characterisation of drug and chemical glucuronidation by HLM and recombinant enzymes, evidence-based guidelines relating to experimental approaches are lacking. Here we present evidence-based strategies for the characterisation of drug and chemical glucuronidation in vitro, and for UGT reaction phenotyping. We anticipate that the strategies will inform practice, encourage development of standardised experimental procedures where feasible, and guide ongoing research in the field.

Kinetics of metabolism of deltamethrin and cis- and trans-permethrin in vitro. Studies using rat and human liver microsomes, isolated rat hepatocytes and rat liver cytosol

The kinetics of metabolism of deltamethrin (DLM) and cis- and trans-permethrin (CPM and TPM) was studied in male Sprague-Dawley rat and human liver microsomes. DLM metabolism kinetics was also studied in isolated rat hepatocytes, liver microsomes and cytosol. Apparent intrinsic clearance (CL_int) values for the metabolism of DLM, CPM and TPM by cytochrome P450 (CYP) and carboxylesterase (CES) enzymes in rat and human liver microsomes decreased with increasing microsomal protein concentration. However, when apparent CL_int values were corrected for nonspecific binding to allow calculation of unbound (i.e., corrected) CL_int values, the unbound values did not vary greatly with microsomal protein concentration. Unbound CL_int values for metabolism of 0.05-1 μM DLM in rat liver microsomes (CYP and CES enzymes) and cytosol (CES enzymes) were not significantly different from rates of DLM metabolism in isolated rat hepatocytes. This study demonstrates that the nonspecific binding of these highly lipophilic compounds needs to be taken into account in order to obtain accurate estimates of rates of in vitro metabolism of these pyrethroids. While DLM is rapidly metabolised in vitro, the hepatocyte membrane does not appear to represent a barrier to the absorption and hence subsequent hepatic metabolism of this pyrethroid.

Structural and in Vivo Characterization of Tubastatin A, a Widely Used Histone Deacetylase 6 Inhibitor

Tubastatin A, a tetrahydro-γ-carboline-capped selective HDAC6 inhibitor (HDAC6i), was rationally designed 10 years ago, and has become the best investigated HDAC6i to date. It shows efficacy in various neurological disease animal models, as HDAC6 plays a crucial regulatory role in axonal transport deficits, protein aggregation, as well as oxidative stress. In this work, we provide new insights into this HDAC6i by investigating the molecular basis of its interactions with HDAC6 through X-ray crystallography, determining its functional capability to elevate the levels of acetylated α-tubulin in vitro and in vivo, correlating PK/PD profiles to determine effective doses in plasma and brain, and finally assessing its therapeutic potential toward psychiatric diseases through use of the SmartCube screening platform.

A patent review of histone deacetylase 6 inhibitors in neurodegenerative diseases (2014-2019)

Introduction: Histone deacetylase 6 (HDAC6) is unique in comparison with other zinc-dependent HDAC family members. An increasing amount of evidence from clinical and preclinical research demonstrates the potential of HDAC6 inhibition as an effective therapeutic approach for the treatment of cancer, autoimmune diseases, as well as neurological disorders. The recently disclosed crystal structures of HDAC6-ligand complexes offer further means for achieving pharmacophore refinement, thus further accelerating the pace of HDAC6 inhibitor discovery in the last few years.Area covered: This review summarizes the latest clinical status of HDAC6 inhibitors, discusses pharmacological applications of selective HDAC6 inhibitors in neurodegenerative diseases, and describes the patent applications dealing with HDAC6 inhibitors from 2014-2019 that have not been reported in research articles.Expert opinion: Phenylhydroxamate has proven a very useful scaffold in the discovery of potent and selective HDAC6 inhibitors. However, weaknesses of the hydroxamate function such as metabolic instability and mutagenic potential limit its application in the neurological field, where long-term administration is required. The recent invention of oxadiazole-based ligands by pharmaceutical companies may provide a new opportunity to optimize the druglike properties of HDAC6 inhibitors for the treatment of neurodegenerative diseases.

Prediction of Fraction Unbound in Microsomal and Hepatocyte Incubations: A Comparison of Methods across Industry Datasets

The fraction unbound in the incubation, f_u,inc, is an important parameter to consider in the evaluation of intrinsic clearance measurements performed in vitro in hepatocytes or microsomes. Reliable estimates of f_u,inc based on a compound's structure have the potential to positively impact the screening timelines in drug discovery. Previous works suggested that f_u,inc is primarily driven by passive processes and can be described using physicochemical properties such as lipophilicity and the protonation state of the molecule. While models based on these principles proved predictive in relatively small datasets that included marketed drugs, their applicability domain has not been extensively explored. The work presented here from the in silico ADME discussion group (part of the International Consortium for Innovation through Quality in Pharmaceutical Development, the IQ consortium) describes the accuracy of these models in large proprietary datasets that include several thousand of compounds across chemical space. Overall, the models do well for compounds with low lipophilicity. In other words, the equations correctly predict that f_u,inc is, in general, above 0.5 for compounds with a calculated logP of less than 3. When applied to lipophilic compounds, the models failed to produce quantitatively accurate predictions of f_u,inc, with a high risk of underestimating binding properties. These models can, therefore, be used quantitatively for less lipophilic compounds. On the other hand, internal machine-learning models using a company's own proprietary dataset also predict compounds with higher lipophilicity reasonably well. Additionally, the data shown indicate that microsomal binding is, in general, a good proxy for hepatocyte binding.

An examination of protein binding and protein-facilitated uptake relating to in vitro-in vivo extrapolation

As explained by the free drug theory, the unbound fraction of drug has long been thought to drive the efficacy of a molecule. Thus, the fraction unbound term, or f_u, appears in equations for fundamental pharmacokinetic parameters such as clearance, and is used when attempting in vitro to in vivo extrapolation (IVIVE). In recent years though, it has been noted that IVIVE does not always yield accurate predictions, and that some highly protein bound ligands have more efficient uptake than can be explained by their unbound fractions. This review explores the evolution of f_u terms included when implementing IVIVE, the concept of protein-facilitated uptake, and the mechanisms that have been proposed to account for facilitated uptake.

Optimization of intestinal microsomal preparation in the rat: A systematic approach to assess the influence of various methodologies on metabolic activity and scaling factors

The metabolic capacity of the intestine and its importance as the initial barrier to systemic exposure can lead to underestimation of first‐pass, and thus overestimation of oral bioavailability. However, the in vitro tools informing estimates of in vivo intestinal metabolism are limited by the complexity of the in vitro matrix preparation and uncertainty with the scaling factors for in vitro to in vivo extrapolation. A number of methods currently exist in the literature for the preparation of intestinal microsomes; however, the impact of key steps in the preparation procedure has not been critically assessed. In the current study, changes in enterocyte isolation, the impact of buffer constituents heparin and glycerol, as well as sonication as a direct method of homogenization were assessed systematically. Furthermore, fresh vs. frozen tissue samples and the impact of microsome freeze thawing was assessed. The rat intestinal microsomes were characterized for CYP content as well as metabolic activity using testosterone and 4‐nitropheonol as probes for CYP and UGT activity, respectively. Comparisons in metabolic activity and scaled unbound intestinal intrinsic clearance (CL_intu,gut) were made to commercially available microsomes using 25 drugs with a diverse range of metabolic pathways and intestinal metabolic stabilities. An optimal, robust and reproducible microsomal preparation method for investigation of intestinal metabolism is proposed. The importance of characterization of the in vitro matrix and the potential impact of intestinal scaling factors on the in vitro–in vivo extrapolation of F_G needs to be investigated further. © 2017 The Authors Biopharmaceutics & Drug Disposition Published by John Wiley & Sons Ltd.

Drug Distribution. Part 1. Models to Predict Membrane Partitioning

PURPOSE

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution.

METHODS

Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs.

RESULTS

The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs).

CONCLUSIONS

Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

A Fragment-Based Approach for the Computational Prediction of the Nonspecific Binding of Drugs to Hepatic Microsomes

Correction for the nonspecific binding (NSB) of drugs to liver microsomes is essential for the accurate measurement of the kinetic parameters K_m and K_i, and hence in vitro-in vivo extrapolation to predict hepatic clearance and drug-drug interaction potential. Although a number of computational approaches for the estimation of drug microsomal NSB have been published, they generally rely on compound lipophilicity and charge state at the expense of other physicochemical and chemical properties. In this work, we report the development of a fragment-based hologram quantitative structure activity relationship (HQSAR) approach for the prediction of NSB using a database of 132 compounds. The model has excellent predictivity, with a noncross-validated r² of 0.966 and cross-validated r² of 0.680, with a predictive r² of 0.748 for an external test set comprising 34 drugs. The HQSAR method reliably predicted the fraction unbound in incubations of 95% of the training and test set drugs, excluding compounds with a steroid or morphinan 4,5-epoxide nucleus. Using the same data set of compounds, performance of the HQSAR method was superior to a model based on logP/D as the sole descriptor (predictive r² for the test set compounds, 0.534). Thus, the HQSAR method provides an alternative approach to laboratory-based procedures for the prediction of the NSB of drugs to liver microsomes, irrespective of the drug charge state (acid, base, or neutral).

Validation of Early Human Dose Prediction: A Key Metric for Compound Progression in Drug Discovery

Human dose prediction is increasingly recognized as an important parameter in Drug Discovery. Validation of a method using only in vitro and predicted parameters incorporated into a PK model was undertaken by predicting human dose and free Cmax for a number of marketed drugs and AZ Development compounds. Doses were compared to those most relevant to marketed drugs or to clinically administered doses of AZ compounds normalized either to predicted Cmin or Cmax values. Average (AFE) and absolute average (AAFE) fold-error analysis showed that best predictions were obtained using a QSAR model as the source of Vss, with Fabs set to 1 for acids and 0.5 for all other ion classes; for clearance prediction no binding correction to the well stirred model (WSM) was used for bases, while it was set to Fup/Fup(0.5) for all other ion classes. Using this combination of methods, predicted doses for 45 to 68% of the Cmin- and Cmax-normalized and marketed drug data sets were within 3-fold of the observed values, while 82 to 92% of these data sets were within 10-fold. This method for early human dose prediction is able to rank, identify, and flag risks or optimization opportunities for future development compounds within 10 days of first synthesis.

Regioselective glucuronidation of gingerols by human liver microsomes and expressed UDP-glucuronosyltransferase enzymes: reaction kinetics and activity correlation analyses for UGT1A9 and UGT2B7

OBJECTIVES

To determine the reaction kinetics for regioselective glucuronidation of gingerols (i.e. 6-, 8- and 10-gingerol) by human liver microsomes and expressed UDP-glucuronosyltransferase (UGT) enzymes, and to identify the main UGT enzymes involved in regioselective glucuronidation of gingerols.

METHODS

The rates of glucuronidation were determined by incubating the gingerols with uridine diphosphoglucuronic acid-supplemented microsomes. Kinetic parameters were derived by fitting an appropriate model to the data. Activity correlation analyses were performed to identify the main UGT enzymes contributing to hepatic metabolism of gingerols.

KEY FINDINGS

Glucuronidation at the 4'-OH group was much more favoured than that at 5-OH. The degree of position preference was compound-dependent; the catalytic efficiency ratios of 4'-O- to 5-O-glucuronidation were 9.1, 19.7 and 2.9 for 6-, 8- and 10-gingerol, respectively. UGT1A8 (an intestinal enzyme), UGT1A9 and UGT2B7 were the enzymes showing the highest activity towards gingerols. Formation of 5-O-glucuronide was mainly catalysed by UGT1A9. UGT2B7 was the only enzyme that generated glucuronides at both 4'-OH and 5-OH sites, although a strong position preference was observed with 4'-OH (≥80.2%). Further, activity correlation analyses indicated that UGT2B7 and UGT1A9 were primarily responsible for 4'-O-glucuronidation and 5-O-glucuronidation of gingerols in the liver, respectively.

CONCLUSIONS

Gingerols were metabolized by multiple hepatic and gastrointestinal UGT enzymes. Also, UGT1A9 and 2B7 were the main contributors to regioselective glucuronidation of gingerols in the liver.

Presence and effects of pharmaceutical and personal care products on the Baca National Wildlife Refuge, Colorado

Pharmaceuticals and personal care products (PPCPs) have raised concerns due to their potential effects to aquatic organisms. These chemicals appear in mixtures at very low concentrations thus making their detection and quantification difficult. Polar organic chemical integrative samplers (POCIS) concentrate trace levels of chemicals over time increasing method sensitivity and thus represent a cost-effective screening tool for biomonitoring studies. The Baca National Wildlife Refuge (BNWR), Colorado, is home for several endemic fish species, including Rio Grande chub (Gila pandora). The objectives of this study were to (1) determine the types and concentrations of PPCPs in the Refuge, (2) compare and contrast two methods (grab and POCIS) for the quantification of PPCPs from surface water, and (3) determine effects due to PPCP exposure in fish. Between 2011 and 2013, 141 PPCPs were quantified using a combination of grab samples and POCIS. Although no PPCPs were detected from the grab samples, high concentrations of N,N-Diethyl-meta-toluamide (DEET) and triclosan were detected in all fish sampling sites with POCIS. Fathead minnows (Pimephales promelas) and Rio Grande chubs of both sexes were collected in 2011 and 2012. Several biological responses were observed in both species from creeks contaminated with PPCPs; however the presence of PPCPs in the reference site did not allow for valid data comparison and interpretation. We conclude that POCIS is a sensitive method for the detection and quantification of PPCPs and for identification of reference sites and that appropriate "reference" sites need to be identified at the BNWR for follow-up studies with native fish.

Rationalizing underprediction of drug clearance from enzyme and transporter kinetic data: from in vitro tools to mechanistic modeling

Over the years, there has been an increase in the number and quality of available in vitro tools for the assessment of clearance. Complexity of data analysis and modelling of corresponding in vitro data has increased in an analogous manner, in particular for the simultaneous characterization of transporter and metabolism kinetics, together with intracellular binding and passive diffusion. In the current chapter, the impact of different factors on the in vitro-in vivo extrapolation of clearance will be addressed in a stepwise manner, from the selection of the most adequate in vitro system and experimental design/condition to the corresponding modelling of data generated. The application of static or physiologically based pharmacokinetic models in the prediction of clearance will be discussed, highlighting limitations and current challenges of some of the approaches. Particular focus will be on the ability of in vitro and in silico predictive tools to overcome the trend of clearance underprediction. Improvements made as a result of inclusion of extrahepatic metabolism and consideration of transporter-metabolism interplay across different organs will be discussed.

Consideration of the unbound drug concentration in enzyme kinetics

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system under investigation. As a consequence, the apparent kinetic parameters that are derived, such as K m or K i, can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus, as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components that can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

Integration of in vitro binding mechanism into the semiphysiologically based pharmacokinetic interaction model between ketoconazole and midazolam

In vitro screening for drug–drug interactions is an integral component of drug development, with larger emphasis now placed on the use of in vitro parameters to predict clinical inhibition. However, large variability exists in K_i reported for ketoconazole with midazolam, a model inhibitor–substrate pair for CYP3A. We reviewed the literature and extracted K_i for ketoconazole as measured by the inhibition of hydroxymidazolam formation in human liver microsomes. The superset of data collected was analyzed for the impact of microsomal binding, using Langmuir and phase equilibrium binding models, and fitted to various inhibition models: competitive, noncompetitive, and mixed. A mixed inhibition model with binding corrected by an independent binding model was best able to fit the data (K_ic = 19.2 nmol/l and K_in = 39.8 nmol/l) and to predict clinical effect of ketoconazole on midazolam area under the concentration–time curve. The variability of reported K_i may partially be explained by microsomal binding and choice of inhibition model.

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.

A semi-physiologically-based pharmacokinetic model characterizing mechanism-based auto-inhibition to predict stereoselective pharmacokinetics of verapamil and its metabolite norverapamil in human

Verapamil and its major metabolite norverapamil were identified to be both mechanism-based inhibitors and substrates of CYP3A and reported to have non-linear pharmacokinetics in clinic. Metabolic clearances of verapamil and norverapmil as well as their effects on CYP3A activity were firstly measured in pooled human liver microsomes. The results showed that S-isomers were more preferential to be metabolized than R-isomers for both verapamil and norverapamil, and their inhibitory effects on CYP3A activity were also stereoselective with S-isomers more potent than R-isomers. A semi-physiologically based pharmacokinetic model (semi-PBPK) characterizing mechanism-based auto-inhibition was developed to predict the stereoselective pharmacokinetic profiles of verapamil and norverapamil following single or multiple oral doses. Good simulation was obtained, which indicated that the developed semi-PBPK model can simultaneously predict pharmacokinetic profiles of S-verapamil, R-verapamil, S-norverapamil and R-norverapamil. Contributions of auto-inhibition to verapamil and norverapamil accumulation were also investigated following the 38th oral dose of verapamil sustained-release tablet (240mg once daily). The predicted accumulation ratio was about 1.3-1.5 fold, which was close to the observed data of 1.4-2.1-fold. Finally, the developed semi-PBPK model was further applied to predict drug-drug interactions (DDI) between verapamil and other three CYP3A substrates including midazolam, simvastatin, and cyclosporine A. Successful prediction was also obtained, which indicated that the developed semi-PBPK model incorporating auto-inhibition also showed great advantage on DDI prediction with CYP3A substrates.

Progress curve mechanistic modeling approach for assessing time-dependent inhibition of CYP3A4

A progress curve method for assessing time-dependent inhibition of CYP3A4 is based on simultaneous quantification of probe substrate metabolite and inhibitor concentrations during the experiment. Therefore, it may overcome some of the issues associated with the traditional two-step method and estimation of inactivation rate (k(inact)) and irreversible inhibition (K(I)) constants. In the current study, seven time-dependent inhibitors were investigated using a progress curve method and recombinant CYP3A4. A novel mechanistic modeling approach was applied to determine inhibition parameters using both inhibitor and probe metabolite data. Progress curves generated for clarithromycin, erythromycin, diltiazem, and N-desmethyldiltiazem were described well by the mechanistic mechanism-based inhibition (MBI) model. In contrast, mibefradil, ritonavir, and verapamil required extension of the model and inclusion of competitive inhibition term for the metabolite. In addition, this analysis indicated that verapamil itself causes minimal MBI, and the formation of inhibitory metabolites was responsible for the irreversible loss of CYP3A4 activity. The k(inact) and K(I) estimates determined in the current study were compared with literature data generated using the conventional two-step method. In the current study, the inactivation efficiency (k(inact)/K(I)) for clarithromycin, ritonavir, and erythromycin were up to 7-fold higher, whereas k(inact)/K(I) for mibefradil, N-desmethyldiltiazem, and diltiazem were, on average, 2- to 4.8-fold lower than previously reported estimates. Use of human liver microsomes instead of recombinant CYP3A4 resulted in 5-fold lower k(inact)/K(I) for erythromycin. In conclusion, the progress curve method has shown a greater mechanistic insight when determining kinetic parameters for MBI in addition to providing a more comprehensive experimental protocol.

Characterization of in vitro glucuronidation clearance of a range of drugs in human kidney microsomes: comparison with liver and intestinal glucuronidation and impact of albumin

Previous studies have shown the importance of the addition of albumin for characterization of hepatic glucuronidation in vitro; however, no reports exist on the effects of albumin on renal or intestinal microsomal glucuronidation assays. This study characterized glucuronidation clearance (CL(int, UGT)) in human kidney, liver, and intestinal microsomes in the presence and absence of bovine serum albumin (BSA) for seven drugs with differential UDP-glucuronosyltransferase (UGT) 1A9 and UGT2B7 specificity, namely, diclofenac, ezetimibe, gemfibrozil, mycophenolic acid, naloxone, propofol, and telmisartan. The impact of renal CL(int, UGT) on accuracy of in vitro-in vivo extrapolation (IVIVE) of glucuronidation clearance was investigated. Inclusion of 1% BSA for acidic drugs and 2% for bases/neutral drugs in incubations was found to be suitable for characterization of CL(int, UGT) in different tissues. Although BSA increased CL(int, UGT) in all tissues, the extent was tissue- and drug-dependent. Scaled CL(int, UGT) in the presence of BSA ranged from 2.22 to 207, 0.439 to 24.4, and 0.292 to 23.8 ml · min(-1) · g tissue(-1) in liver, kidney, and intestinal microsomes. Renal CL(int, UGT) (per gram of tissue) was up to 2-fold higher in comparison with that for liver for UGT1A9 substrates; in contrast, CL(int, UGT) for UGT2B7 substrates represented approximately one-third of hepatic estimates. Scaled renal CL(int, UGT) (in the presence of BSA) was up to 30-fold higher than intestinal glucuronidation for the drugs investigated. Use of in vitro data obtained in the presence of BSA and inclusion of renal clearance improved the IVIVE of glucuronidation clearance, with 50% of drugs predicted within 2-fold of observed values. Characterization and consideration of kidney CL(int, UGT) is particularly important for UGT1A9 substrates.

Measuring in vitro biotransformation rates of super hydrophobic chemicals in rat liver s9 fractions using thin-film sorbent-phase dosing

Methods for rapid and cost-effective assessment of the biotransformation potential of very hydrophobic and potentially bioaccumulative chemicals in mammals are urgently needed for the ongoing global evaluation of the environmental behavior of commercial chemicals. We developed and tested a novel solvent-free, thin-film sorbent-phase in vitro dosing system to measure the in vitro biotransformation rates of very hydrophobic chemicals in male Sprague-Dawley rat liver S9 homogenates and compared the rates to those measured by conventional solvent-delivery dosing. The thin-film sorbent-phase dosing system using ethylene vinyl acetate coated vials was developed to eliminate the incomplete dissolution of very hydrophobic substances in largely aqueous liver homogenates, to determine biotransformation rates at low substrate concentrations, to measure the unbound fraction of substrate in solution, and to simplify chemical analysis by avoiding the difficult extraction of test chemicals from complex biological matrices. Biotransformation rates using sorbent-phase dosing were 2-fold greater than those measured using solvent-delivery dosing. Unbound concentrations of very hydrophobic test chemicals were found to decline with increasing S9 and protein concentrations, causing measured biotransformation rates to be independent of S9 or protein concentrations. The results emphasize the importance of specifying both protein content and unbound substrate fraction in the measurement and reporting of in vitro biotransformation rates of very hydrophobic substances, which can be achieved in a thin-film sorbent-phase dosing system.

Lack of appreciable species differences in nonspecific microsomal binding

Species differences in microsomal binding were evaluated for 43 drug molecules in human, monkey, dog and rat liver microsomes, using a fixed concentration of microsomal protein. The dataset included 32 named drugs and 11 proprietary compounds encompassing a broad spectrum of physicochemical properties (11 acids, 24 bases, 8 neutral, c log D -1 to 7, MW 200 to 700 and free fraction <0.001 to 1). Free fractions (f(u,mic)) in monkey, dog, rat and human microsomes were highly correlated, with linear regression correlation coefficients greater than 0.97. The average fold-difference in f(u,mic) between monkey, dog, or rat, and human was 1.6-, 1.3-, and 1.5-fold, respectively. Species differences in f(u,mic) were also assessed for a range of microsomal protein concentrations (0.2-2 mg/mL) for midazolam, clomipramine, astemizole, and tamoxifen, drugs with low to high microsomal binding. The mean fold species-difference in f(u,mic) for midazolam, clomipramine, astemizole, and tamoxifen was 1.1-, 1.2-, 1.3-, and 2.0-fold, respectively, and was independent of normalized microsomal protein concentration. For a fixed concentration of microsomal protein, greater than 76% and 90% of drugs examined in this study had preclinical species f(u,mic) within 1.5- and 2-fold, respectively, of experimentally measured human values.

Strategic use of plasma and microsome binding to exploit in vitro clearance in early drug discovery

Apparent intrinsic clearance (CLia) determined from microsomal stability assays is a cornerstone in drug discovery. Categorical bins are routinely applied to this end point to facilitate analysis. However, such bins ignore the interdependent nature of apparent intrinsic microsome clearance on several ADME parameters. Considering CLia as a determinant for both metabolic stability and potential dose is more appropriate. In this context with proper accounting for nonspecific binding to microsomes and plasma, consideration of compounds with higher CLia may be warranted. The underlying benefit is the potential increase in the number of hits or chemical diversity for evaluation during the early stages of programs.

Time-dependent inhibitory effects of (1R,9S,12S,13R,14S,17R,18E,21S,23S,24R,25S,27R)-1,14-dihydroxy-12-(E)-2-[(1R,3R,4R)-4-hydroxy-3-methoxycyclohexyl]-1-methylvinyl-23,25-dimethoxy-13,19,21,27-tetramethyl-17-(2-oxopropyl)-11,28-dioxa-4-azatricyclo[22.3.1.0(4.9)]octacos-18-ene-2,3,10,16-tetrone (FK1706), a novel nonimmunosuppressive immunophilin ligand, on CYP3A4/5 activity in humans in vivo and in vitro

We investigated the inhibitory effects of (1R,9S,12S,13R,14S,17R,18E,21S,23S,24R,25S,27R)-1, 14-dihydroxy-12-(E)-2-[(1R,3R,4R)-4-hydroxy-3-methoxycyclohexyl]-1-methylvinyl-23,25-dimethoxy-13,19,21,27-tetramethyl-17-(2-oxopropyl)-11,28-dioxa-4-azatricyclo [22.3.1.0(4.9)]octacos-18-ene-2,3,10,16-tetrone (FK1706), a novel nonimmunosuppressive immunophilin ligand, on CYP3A4/5 in in vitro and in vivo settings. First, the inhibitory effects of FK1706 (preincubation dependence, inactivation rate estimation, and reversibility) were tested using human liver microsomes. Second, the effect of repeated oral doses of FK1706 (60 mg q.d. for 14 days) on the pharmacokinetics of midazolam (single oral 2-mg dose) was tested in healthy volunteers. Finally, pharmacokinetic modeling and simulation were performed. In vitro experiments showed that FK1706 inhibited CYP3A4/5 in a time-dependent and irreversible manner. The in vitro maximum inactivation rate constant (k(inact)) and concentration of inhibitor that gave half-maximal k(inact) (K(I)) were estimated to be 10.1 h(-1) and 2050 ng/ml, respectively. In the clinical study, FK1706 produced a 2-fold increase in the area under the time-concentration curve (AUC) of midazolam. A pharmacokinetic model developed for this study, which described the time course of concentrations of both FK1706 and midazolam and incorporated CYP3A4/5 inactivation in the liver and intestine, successfully predicted the change in the pharmacokinetics of midazolam using in vitro k(inact) and K(I) values (1.66- to 2.81-fold increases in AUC predicted) and estimated the in vivo inactivation rate to be 0.00404 to 0.0318 h(-1) x ml/ng. In conclusion, FK1706 weakly or moderately inhibited the activity of CYP3A4/5 in vitro and vivo at the tested dose. The model developed here would be helpful in predicting drug-drug interactions and in the design of dose regimens that avoid drug-drug interactions.