Targeted quantitative proteomics for the analysis of 14 UGT1As and -2Bs in human liver using NanoUPLC-MS/MS with selected reaction monitoring.

Targeted quantitative proteomics using heavy isotope dilution techniques is increasingly being utilized to quantify proteins, including UGT enzymes, in biological matrices. Here we present a multiplexed method using nanoLC-MS/MS and multiple reaction monitoring (MRM) to quantify 14 UGT1As and UGT2Bs in liver matrices. Where feasible, we employ two or more proteotypic peptides per protein, with only four proteins quantified with only one proteotypic peptide. We apply the method to analysis of a library of 60 human liver microsome (HLM) and matching S9 samples. Ten of the UGT isoforms could be detected in liver, and the expression of each was consistent with mRNA expression reported in the literature. UGT2B17 was unusual in that ∼30% of liver microsomes had no or little (<0.5 pmol/mg protein) content, consistent with a known common polymorphism. Liver S9 UGT concentrations were approximately 10-15% those of microsomes. The method was robust, precise, and reproducible and provides novel UGT expression data in human liver that will benefit rational approaches to evaluate metabolism in drug development.

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.

Selective mechanism-based inactivation of CYP3A4 by CYP3cide (PF-04981517) and its utility as an in vitro tool for delineating the relative roles of CYP3A4 versus CYP3A5 in the metabolism of drugs.

CYP3cide (PF-4981517; 1-methyl-3-[1-methyl-5-(4-methylphenyl)-1H-pyrazol-4-yl]-4-[(3S)-3-piperidin-1-ylpyrrolidin-1-yl]-1H-pyrazolo[3,4-d]pyrimidine) is a potent, efficient, and specific time-dependent inactivator of human CYP3A4. When investigating its inhibitory properties, an extreme metabolic inactivation efficiency (k(inact)/K(I)) of 3300 to 3800 ml · min⁻¹ · µmol⁻¹ was observed using human liver microsomes from donors of nonfunctioning CYP3A5 (CYP3A5 *3/*3). This observed efficiency equated to an apparent K(I) between 420 and 480 nM with a maximal inactivation rate (k(inact)) equal to 1.6 min⁻¹. Similar results were achieved with testosterone, another CYP3A substrate, and other sources of the CYP3A4 enzyme. To further illustrate the abilities of CYP3cide, its partition ratio of inactivation was determined with recombinant CYP3A4. These studies produced a partition ratio approaching unity, thus underscoring the inactivation capacity of CYP3cide. When CYP3cide was tested at a concentration and preincubation time to completely inhibit CYP3A4 in a library of genotyped polymorphic CYP3A5 microsomes, the correlation of the remaining midazolam 1'-hydroxylase activity to CYP3A5 abundance was significant (R² value equal to 0.51, p value of <0.0001). The work presented here supports these findings by fully characterizing the inhibitory properties and exploring CYP3cide's mechanism of action. To aid the researcher, multiple commercially available sources of CYP3cide were established, and a protocol was developed to quantitatively determine CYP3A4 contribution to the metabolism of an investigational compound. Through the establishment of this protocol and the evidence provided here, we believe that CYP3cide is a very useful tool for understanding the relative roles of CYP3A4 versus CYP3A5 and the impact of CYP3A5 genetic polymorphism on a compound's pharmacokinetics.

Medicinal chemistry approaches to avoid aldehyde oxidase metabolism.

Aldehyde oxidase (AO) is a molybdenum-containing enzyme distributed throughout the animal kingdom and capable of metabolising a wide range of aldehydes and N-heterocyclic compounds. Although metabolism by this enzyme in man is recognised to have significant clinical impact where human AO activity was not predicted by screening in preclinical species, there is very little reported literature offering real examples where drug discoverers have successfully designed away from AO oxidation. This article reports on some strategies adopted in the Pfizer TLR7 agonist programme to successfully switch off AO metabolism that was seen principally in the rat.

Optimized assays for human UDP-glucuronosyltransferase (UGT) activities: altered alamethicin concentration and utility to screen for UGT inhibitors.

The measurement of the effect of new chemical entities on human UDP-glucuronosyltransferase (UGT) marker activities using in vitro experimentation represents an important experimental approach in drug development to guide clinical drug-interaction study designs or support claims that no in vivo interaction will occur. Selective high-performance liquid chromatography-tandem mass spectrometry functional assays of authentic glucuronides for five major hepatic UGT probe substrates were developed: ß-estradiol-3-glucuronide (UGT1A1), trifluoperazine-N-glucuronide (UGT1A4), 5-hydroxytryptophol-O-glucuronide (UGT1A6), propofol-O-glucuronide (UGT1A9), and zidovudine-5'-glucuronide (UGT2B7). High analytical sensitivity permitted characterization of enzyme kinetic parameters at low human liver microsomal and recombinant UGT protein concentration (0.025 mg/ml), which led to a new recommended optimal universal alamethicin activation concentration of 10 µg/ml for microsomes. Alamethicin was not required for recombinant UGT incubations. Apparent enzyme kinetic parameters, particularly for UGT1A1 and UGT1A4, were affected by nonspecific binding. Unbound intrinsic clearance for UGT1A9 and UGT2B7 increased significantly after addition of 2% bovine serum albumin, with minimal changes for UGT1A1, UGT1A4, and UGT1A6. Eleven potential UGT and cytochrome P450 inhibitors were evaluated as UGT inhibitors, resulting in observation of nonselective UGT inhibition by chrysin, mefenamic acid, silibinin, tangeretin, ketoconazole, itraconazole, ritonavir, and verapamil. The pan-cytochrome P450 inhibitor, 1-aminobenzotriazole, minimally inhibited UGT activities and may be useful in reaction phenotyping of mixed UGT and cytochrome P450 substrates. These methods should prove useful in the routine assessments of the potential for new drug candidates to elicit pharmacokinetic drug interactions via inhibition of human UGT activities and the identification of UGT enzyme-selective chemical inhibitors.

Investigation into UDP-glucuronosyltransferase (UGT) enzyme kinetics of imidazole- and triazole-containing antifungal drugs in human liver microsomes and recombinant UGT enzymes.

Imidazoles and triazoles represent major classes of antifungal azole derivatives. With respect to UDP-glucuronosyltransferase (UGT) enzymes, the drug metabolism focus has mainly concentrated on their inhibitory effects with little known about azoles as substrates for UGTs. N-Glucuronide metabolites of the imidazole antifungals, tioconazole and croconazole, have been reported, but there are currently no reports of N-glucuronidation of triazole antifungal agents. In this study, evidence for glucuronidation of azole-containing compounds was studied in human liver microsomes (HLM). When a glucuronide metabolite was identified, azoles were incubated in 12 recombinant UGT (rUGT) enzymes, and enzyme kinetics were determined for the UGT with the most intense glucuronide peak. Six imidazole antifungals, three triazoles, and the benzodiazepine alprazolam (triazole) were evaluated in this study. All compounds investigated were identified as substrates of UGT. UGT1A4 was the main enzyme involved in the metabolism of all compounds except for fluconazole, which was mainly metabolized by UGT2B7, probably mediating its O-glucuronide metabolism. UGT1A3 was also found to be involved in the metabolism of all imidazoles but not triazoles. In both HLM and rUGT K(m) values were lower for imidazoles (14.8-144 microM) than for triazoles (158-3037 microM), with the exception of itraconazole (8.4 microM). All of the imidazoles studied inhibited their own metabolism at high substrate concentrations. In terms of UGT1A4 metabolism, itraconazole showed kinetic features characteristic of imidazole rather than triazole antifungals. This behavior is attributed to the physicochemical properties of itraconazole that are similar to those of imidazoles in terms of clogP.

Excretion and metabolism of lersivirine (5-{[3,5-diethyl-1-(2-hydroxyethyl)(3,5-14C2)-1H-pyrazol-4-yl]oxy}benzene-1,3-dicarbonitrile), a next-generation non-nucleoside reverse transcriptase inhibitor, after administration of [14C]Lersivirine to healthy volunteers.

Lersivirine [UK-453,061, 5-((3,5-diethyl-1-(2-hydroxyethyl)(3,5-14C2)-1H-pyrazol-4-yl)oxy)benzene-1,3-dicarbonitrile] is a next-generation non-nucleoside reverse transcriptase inhibitor, with a unique binding interaction within the reverse transcriptase binding pocket. Lersivirine has shown antiviral activity and is well tolerated in HIV-infected and healthy subjects. This open-label, Phase I study investigated the absorption, metabolism, and excretion of a single oral 500-mg dose of [14C]lersivirine (parent drug) and characterized the plasma, fecal, and urinary radioactivity of lersivirine and its metabolites in four healthy male volunteers. Plasma C(max) for total radioactivity and unchanged lersivirine typically occurred between 0.5 and 3 h postdose. The majority of radioactivity was excreted in urine (approximately 80%) with the remainder excreted in the feces (approximately 20%). The blood/plasma ratio of total drug-derived radioactivity [area under the plasma concentration-time profile from time zero extrapolated to infinite time (AUC(inf))] was 0.48, indicating that radioactive material was distributed predominantly into plasma. Lersivirine was extensively metabolized, primarily by UDP glucuronosyltransferase- and cytochrome P450-dependent pathways, with 22 metabolites being identified in this study. Analysis of precipitated plasma revealed that the lersivirine-glucuronide conjugate was the major circulating component (45% of total radioactivity), whereas unchanged lersivirine represented 13% of total plasma radioactivity. In vitro studies showed that UGT2B7 and CYP3A4 are responsible for the majority of lersivirine metabolism in humans.

Understanding CYP2D6 interactions.

Owing to the polymorphic nature of CYP2D6, clinically significant issues can arise when drugs rely on that enzyme either for clearance, or metabolism to an active metabolite. Available screening methods to determine if the compound is likely to cause drug-drug interactions, or is likely to be a victim of inhibition of CYP2D6 by other compounds will be described. Computational models and examples will be given on strategies to design out the CYP2D6 liabilities for both heme-binding compounds and non-heme-binding compounds.

Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction.

Cytochrome P450 3A4 (CYP3A4) is the most important enzyme in drug metabolism and because it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) it is highly desirable to be able to predict CYP3A4-based DDIs from in vitro data. In this study, the prediction of clinical DDIs for 30 drugs on the pharmacokinetics of midazolam, a probe substrate for CYP3A4, was done using in vitro inhibition, inactivation, and induction data. Two DDI prediction approaches were used, which account for effects at both the liver and intestine. The first was a model that simultaneously combines reversible inhibition, time-dependent inactivation, and induction data with static estimates of relevant in vivo concentrations of the precipitant drug to provide point estimates of the average magnitude of change in midazolam exposure. This model yielded a success rate of 88% in discerning DDIs with a mean -fold error of 1.74. The second model was a computational physiologically based pharmacokinetic model that uses dynamic estimates of in vivo concentrations of the precipitant drug and accounts for interindividual variability among the population (Simcyp). This model yielded success rates of 88 and 90% (for "steady-state" and "time-based" approaches, respectively) and mean -fold errors of 1.59 and 1.47. From these findings it can be concluded that in vivo DDIs for CYP3A4 can be predicted from in vitro data, even when more than one biochemical phenomenon occurs simultaneously.

In vitro and in vivo glucuronidation of midazolam in humans.

AIMS: Midazolam (MDZ) is a benzodiazepine used as a CYP3A4 probe in clinical and in vitro studies. A glucuronide metabolite of MDZ has been identified in vitro in human liver microsome (HLM) incubations. The primary aim of this study was to understand the in vivo relevance of this pathway. METHODS: An authentic standard of N-glucuronide was generated from microsomal incubations and isolated using solid-phase extraction. The structure was confirmed using proton nuclear magnetic resonance (NMR) and (1)H-(13)C long range correlation experiments. The metabolite was quantified in vivo in human urine samples. Enzyme kinetic behaviour of the pathway was investigated in HLM and recombinant UGT (rUGT) enzymes. Additionally, preliminary experiments were performed with 1'-OH midazolam (1'-OH MDZ) and 4-OH-midazolam (4-OH MDZ) to investigate N-glucuronidation. RESULTS: NMR data confirmed conjugation of midazolam N-glucuronide (MDZG) standard to be on the alpha-nitrogen of the imidazole ring. In vivo, MDZG in the urine accounted for 1-2% of the administered dose. In vitro incubations confirmed UGT1A4 as the enzyme of interest. The pathway exhibited atypical kinetics and a substrate inhibitory cooperative binding model was applied to determine K(m) (46 microM, 64 microM), V(max) (445 pmol min(-1) mg(-1), 427 pmol min(-1) mg(-1)) and K(i) (58 microM, 79 microM) in HLM and rUGT1A4, respectively. From incubations with HLM and rUGT enzymes, N-glucuronidation of 1'-OH MDZ and 4-OH MDZ is also inferred. CONCLUSIONS: A more complete picture of MDZ metabolism and the enzymes involved has been elucidated. Direct N-glucuronidation of MDZ occurs in vivo. Pharmacokinetic modelling using Simcyp illustrates an increased role for UGT1A4 under CYP3A inhibited conditions.

Maraviroc: in vitro assessment of drug-drug interaction potential.

AIMS: To characterize the cytochrome P450 enzyme(s) responsible for the N-dealkylation of maraviroc in vitro, and predict the extent of clinical drug-drug interactions (DDIs). METHODS: Human liver and recombinant CYP microsomes were used to identify the CYP enzyme responsible for maraviroc N-dealkylation. Studies comprised enzyme kinetics and evaluation of the effects of specific CYP inhibitors. In vitro data were then used as inputs for simulation of DDIs with ketoconazole, ritonavir, saquinavir and atazanvir, using the Simcyptrade mark population-based absorption, distribution, metabolism and elimination (ADME) simulator. Study designs for simulations mirrored those actually used in the clinic. RESULTS: Maraviroc was metabolized to its N-dealkylated product via a single CYP enzyme characterized by a K(m) of 21 microM and V(max) of 0.45 pmol pmol(-1) min(-1) in human liver microsomes and was inhibited by ketoconazole (CYP3A4 inhibitor). In a panel of recombinant CYP enzymes, CYP3A4 was identified as the major CYP responsible for maraviroc metabolism. Using recombinant CYP3A4, N-dealkylation was characterized by a K(m) of 13 microM and a V(max) of 3 pmol pmol(-1) CYP min(-1). Simulations therefore focused on the effect of CYP3A4 inhibitors on maraviroc pharmacokinetics. The simulated median AUC ratios were in good agreement with observed clinical changes (within twofold in all cases), although, in general, there was a trend for overprediction in the magnitude of the DDI. CONCLUSION: Maraviroc is a substrate for CYP3A4, and exposure will therefore be modulated by CYP3A4 inhibitors. Simcyptrade mark has successfully simulated the extent of clinical interactions with CYP3A4 inhibitors, further validating this software as a good predictor of CYP-based DDIs.

Development of an in vitro drug-drug interaction assay to simultaneously monitor five cytochrome P450 isoforms and performance assessment using drug library compounds.

INTRODUCTION: Inhibition of cytochrome P450 (CYP) is a principal mechanism for metabolism-based drug-drug interactions (DDIs). This article describes a robust, high-throughput CYP-mediated DDI assay using a cocktail of 5 clinically relevant probe substrates with quantification by liquid chromatography/tandem mass spectrometry (LC/MS-MS). METHODS: The assay consisted of human liver microsomes and a cocktail of probe substrates metabolized by the five major CYP isoforms (tacrine for CYP1A2, diclofenac for CYP2C9, (S)-mephenytoin for CYP2C19, dextromethorphan for CYP2D6 and midazolam for CYP3A4). The assay was fully automated in both 96- and 384-well formats. RESULTS: A series of experiments were conducted to define the optimal kinetic parameters and solvent concentrations, as well as, to assess potential reactant and product interference. The assay was validated against known CYP inhibitors (miconazole, sulfaphenazole, ticlopidine, quinidine, ketoconazole, itraconazole, fluoxetine) and evaluated in a screening environment by testing 9494 compounds. DISCUSSION: Our findings show that this assay has application in early stage drug discovery to economically, reliably and accurately assess compounds for DDIs.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor. WHAT THIS STUDY ADDS: Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions. AIMS: The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques. METHODS: The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP. RESULTS: When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs. CONCLUSIONS: The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.

Induction of cytochrome P450: assessment in an immortalized human hepatocyte cell line (Fa2N4) using a novel higher throughput cocktail assay.

Over recent years the application of cocktail studies to measure biological markers has become increasingly popular. The current study investigated a novel approach in assessing cytochrome P450 (P450) enzyme induction in an immortalized cell line using a cocktail of five P450 substrate probes compared with the traditional single-probe approach. The findings reported herein support use of a cocktail approach to assess the induction of the major P450s, namely, CYP3A4, CYP1A2, and CYP2C9. CYP2C19 and CYP2D6 could also be followed as part of the cocktail approach reported. Response to prototypical inducers did not differ to those observed in the presence of the specific probes alone. Consequently, this approach requires significantly fewer sample numbers if screening the induction potential of more than one P450. Moreover, these studies highlight the utility of the immortalized cell line Fa2N4 as a robust model system for induction studies. In conclusion, the current experimental setup is an improvement on current approaches used to assess P450 induction, significantly increasing sample throughput.

Minimizing polymorphic metabolism in drug discovery: evaluation of the utility of in vitro methods for predicting pharmacokinetic consequences associated with CYP2D6 metabolism.

Minimizing interindividual variability in drug exposure is an important goal for drug discovery. The reliability of the selective CYP2D6 inhibitor quinidine was evaluated in a retrospective analysis using a standardized approach that avoids laboratory-to-laboratory variation. The goal was to evaluate the reliability of in vitro metabolism studies for predicting extensive metabolizer (EM)/poor metabolizer (PM) exposure differences. Using available literature, 18 CYP2D6 substrates were selected for further analysis. In vitro microsomal studies were conducted at 1 microM substrate and 0.5 microM P450 to monitor substrate depletion. An estimate of the fraction metabolized by CYP2D6 in microsomes was derived from the rate constant determined with and without 1 microM quinidine for 11 substrates. Clearance in EM and PM subjects and fractional recovery of metabolites were taken from the literature. A nonlinear relationship between the contribution of CYP2D6 and decreased oral clearance for PMs relative to EMs was evident. For drugs having <60% CYP2D6 involvement in vivo, a modest difference between EM and PM exposure was observed (<2.5-fold). For major CYP2D6 substrates (>60%), more dramatic exposure differences were observed (3.5- to 53-fold). For compounds primarily eliminated by hepatic P450 and with sufficient turnover to be evaluated in vitro, the fraction metabolized by CYP2D6 in vitro compared favorably with the in vivo data. The in vitro estimation of fraction metabolized using quinidine as a specific inhibitor provided an excellent predictive tool. Results from microsomal substrate depletion experiments can be used with confidence to select compounds in drug discovery using a cutoff of >60% metabolism by CYP2D6.

Utility of human/human-derived reagents in drug discovery and development: An industrial perspective.

The shift to combinatorial chemistry and parallel synthesis in drug discovery has resulted in large numbers of compounds entering the lead seeking and lead development phases of the process. To support this, higher throughput computational (in silico) and in vitro approaches have become the forefront of the drug metabolism and pharmacokinetic (DMPK) input into drug discovery. This has been accompanied by a shift in focus from animal-derived data to human based studies, reflecting the realisation that extrapolation from animals to human has its limitations. In silico approaches may be regarded as human derived tools for DMPK, since models (template/pharmacophore and protein homology modelling), for example, for the human CYP enzymes, are widely used for identifying qualitatively enzyme/substrate interactions. Quantitative assessment of drug metabolism using human hepatocytes or sub-cellular fractions provide a valuable tool both for the screening out of high metabolic lability and in estimations of human intrinsic clearance. In terms of drug absorption, the human colon adenocarcinoma cell line, Caco-2, offers a versatile human derived system for measuring drug permeability, despite over expression of the efflux transporter P-glycoprotein (P-gp). The importance of P-gp can then be further assessed in recombinant systems expressing the human P-gp, where substrate affinity and inhibition potency can be measured, important factors when considering transporter mediated drug-drug interactions. The primary cause of pharmacokinetic-based drug-drug interactions (DDIs) is through enzyme inhibition or induction, with the CYP enzymes being of major importance. Human liver microsomes and hepatocytes are invaluable tools in assessment of DDI vulnerability of new chemical entities, having the capacity to identify enzymes responsible for specific routes of metabolism, and hence areas of vulnerability for a DDI. In addition, human-based screening tools can be used to identify the perpetrator of a DDI through enzyme inhibition/induction. Large differences in the nature of enzymes induced and the extent of induction when comparing animals to man are known. Thus, in vitro models allowing assessment of induction potential in human tissue, establishes some relevance to the clinical situation.

Drug-drug interactions for UDP-glucuronosyltransferase substrates: a pharmacokinetic explanation for typically observed low exposure (AUCi/AUC) ratios.

Glucuronidation is a listed clearance mechanism for 1 in 10 of the top 200 prescribed drugs. The objective of this article is to encourage those studying ligand interactions with UDP-glucuronosyltransferases (UGTs) to adequately consider the potential consequences of in vitro UGT inhibition in humans. Spurred on by interest in developing potent and selective inhibitors for improved confidence around UGT reaction phenotyping, and the increased availability of recombinant forms of human UGTs, several recent studies have reported in vitro inhibition of UGT enzymes. In some cases, the observed potency of UGT inhibitors in vitro has been interpreted as having potential relevance in humans via pharmacokinetic drug-drug interactions. Although there are reported examples of clinically relevant drug-drug interactions for UGT substrates, exposure increases of the aglycone are rarely greater than 100% in the presence of an inhibitor relative to its absence (i.e., AUCi/AUC < or = 2). This small magnitude in change is in contrast to drugs primarily cleared by cytochrome P450 enzymes, where exposures have been reported to increase as much as 35-fold on coadministration with an inhibitor (e.g., ketoconazole inhibition of CYP3A4-catalyzed terfenadine metabolism). In this article the evidence for purported clinical relevance of potent in vitro inhibition of UGT enzymes will be assessed, taking the following into account: in vitro data on the enzymology of glucuronide formation from aglycone, pharmacokinetic principles based on empirical data for inhibition of metabolism, and clinical data on the pharmacokinetic drug-drug interactions of drugs primarily cleared by glucuronidation.

Reaction phenotyping in drug discovery: moving forward with confidence?

For the pharmaceutical industry, one of the challenges in evaluating the risk of future compound attrition at the discovery stage is the successful prediction of the major routes of clearance in humans. For compounds cleared by metabolism, such information will help to avoid the development of compounds that will exhibit large interpatient differences in pharmacokinetics via 1). routes of metabolism catalyzed by functionally polymorphic enzymes and/or 2). clinically significant metabolic drug-drug interactions, in the later stages of development. The degree of intersubject variability that is acceptable for a drug candidate is uncertain in the discovery stage where knowledge of other important factors is limited or unavailable (i.e. therapeutic index, pharmacodynamic variability, etc). Reaction phenotyping is the semi-quantitative in vitro estimation of the relative contributions of specific drug-metabolizing enzymes to the metabolism of a test compound. However, reaction phenotyping in the discovery stage of drug development is complicated by the absence of radiolabelled parent compound or metabolite bioanalytical standards relative to later stages of development. In this commentary, some of the approaches, based on published data, which can be taken to overcome these challenges are discussed. In addition, knowledge of the molecular structure (i.e. specific chemical substituents), physicochemical properties, and routes of clearance in animals can all help in making a successful prediction for the routes of clearance in humans. In combination, the objective of these studies should be to reduce to a minimum the risk of finding significant inter-patient differences in pharmacokinetics at a later stage in development due to significant metabolism by polymorphic enzymes or drug-drug interactions. Consequently, this data should be used to avoid costly late stage attrition.