Low-Turnover Drug Molecules: A Current Challenge for Drug Metabolism Scientists.

In vitro assays using liver subcellular fractions or suspended hepatocytes for characterizing the metabolism of drug candidates play an integral role in the optimization strategy employed by medicinal chemists. However, conventional in vitro assays have limitations in their ability to predict clearance and generate metabolites for low-turnover (slowly metabolized) drug molecules. Due to a rapid loss in the activity of the drug-metabolizing enzymes, in vitro incubations are typically performed for a maximum of 1 hour with liver microsomes to 4 hours with suspended hepatocytes. Such incubations are insufficient to generate a robust metabolic response for compounds that are slowly metabolized. Thus, the challenge of accurately estimating low human clearance with confidence has emerged to be among the top challenges that drug metabolism scientists are confronted with today. In response, investigators have evaluated novel methodologies to extend incubation times and more sufficiently measure metabolism of low-turnover drugs. These methods include plated human hepatocytes in monoculture, and a novel in vitro methodology using a relay of sequential incubations with suspended cryopreserved hepatocytes. In addition, more complex in vitro cellular models, such as HepatoPac (Hepregen, Medford, MA), a micropatterned hepatocyte-fibroblast coculture system, and the HµREL (Beverley Hills, CA) hepatic coculture system, have been developed and characterized that demonstrate prolonged enzyme activity. In this review, the advantages and disadvantages of each of these in vitro methodologies as it relates to the prediction of clearance and metabolite identification will be described in an effort to provide drug metabolism scientists with the most up-to-date experimental options for dealing with the complex issue of low-turnover drug candidates.

Pharmacogenomics of gemcitabine metabolism: functional analysis of genetic variants in cytidine deaminase and deoxycytidine kinase.

Gemcitabine (dFdC, 2',2'-difluorodeoxycytidine) is metabolized by cytidine deaminase (CDA) and deoxycytidine kinase (DCK), but the contribution of genetic variation in these enzymes to the variability in systemic exposure and response observed in cancer patients is unclear. Wild-type enzymes and variants of CDA (Lys27Gln and Ala70Thr) and DCK (Ile24Val, Ala119Gly, and Pro122Ser) were expressed in and purified from Escherichia coli, and enzyme kinetic parameters were estimated for cytarabine (Ara-C), dFdC, and its metabolite 2',2'-difluorodeoxyuridine (dFdU) as substrates. All three CDA proteins showed similar K(m) and V(max) for Ara-C and dFdC deamination, except for CDA70Thr, which had a 2.5-fold lower K(m) and 6-fold lower V(max) for Ara-C deamination. All four DCK proteins yielded comparable metabolic activity for Ara-C and dFdC monophosphorylation, except for DCK24Val, which demonstrated an approximately 2-fold increase (P < 0.05) in the intrinsic clearance of dFdC monophosphorylation due to a 40% decrease in K(m) (P < 0.05). DCK did not significantly contribute to dFdU monophosphorylation. In conclusion, the Lys27Gln substitution does not significantly modulate CDA activity toward dFdC, and therefore would not contribute to interindividual variability in response to gemcitabine. The higher in vitro catalytic efficiency of DCK24Val toward dFdC monophosphorylation may be relevant to dFdC clinical response. The substrate-dependent alterations in activities of CDA70Thr and DCK24Val in vitro were observed for the first time, and demonstrate that the in vivo consequences of these genetic variations should not be extrapolated from one substrate of these enzymes to another.

PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach.

The objective of this study is to assess the effectiveness of physiologically based pharmacokinetic (PBPK) models for simulating human plasma concentration-time profiles for the unique drug dataset of blinded data that has been assembled as part of a Pharmaceutical Research and Manufacturers of America initiative. Combinations of absorption, distribution, and clearance models were tested with a PBPK approach that has been developed from published equations. An assessment of the quality of the model predictions was made on the basis of the shape of the plasma time courses and related parameters. Up to 69% of the simulations of plasma time courses made in human demonstrated a medium to high degree of accuracy for intravenous pharmacokinetics, whereas this number decreased to 23% after oral administration based on the selected criteria. The simulations resulted in a general underestimation of drug exposure (Cmax and AUC0- t ). The explanations for this underestimation are diverse. Therefore, in general it may be due to underprediction of absorption parameters and/or overprediction of distribution or oral first-pass. The implications of compound properties are demonstrated. The PBPK approach based on in vitro-input data was as accurate as the approach based on in vivo data. Overall, the scientific benefit of this modeling study was to obtain more extensive characterization of predictions of human PK from PBPK methods.

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.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 1: goals, properties of the PhRMA dataset, and comparison with literature datasets.

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 2: comparative assessment of prediction methods of human volume of distribution.

The objective of this study was to evaluate the performance of various empirical, semimechanistic and mechanistic methodologies with and without protein binding corrections for the prediction of human volume of distribution at steady state (Vss ). PhRMA member companies contributed a set of blinded data from preclinical and clinical studies, and 18 drugs with intravenous clinical pharmacokinetics (PK) data were available for the analysis. In vivo and in vitro preclinical data were used to predict Vss by 24 different methods. Various statistical and outlier techniques were employed to assess the predictability of each method. There was not simply one method that predicts Vss accurately for all compounds. Across methods, the maximum success rate in predicting human Vss was 100%, 94%, and 78% of the compounds with predictions falling within tenfold, threefold, and twofold error, respectively, of the observed Vss . Generally, the methods that made use of in vivo preclinical data were more predictive than those methods that relied solely on in vitro data. However, 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. It is recommended to initially use the in vitro tissue composition-based equations to predict Vss in preclinical species and humans, putting the assumptions and compound properties into context. As in vivo data become available, these predictions should be reassessed and rationalized to indicate the level of confidence (uncertainty) in the human Vss prediction. The top three methods that perform strongly at integrating in vivo data in this way were the Øie-Tozer, the rat -dog-human proportionality equation, and the lumped-PBPK approach. Overall, the scientific benefit of this study was to obtain greater characterization of predictions of human Vss from several methods available in the literature.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach.

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

Disposition and metabolism of semagacestat, a {gamma}-secretase inhibitor, in humans.

Semagacestat is a functional gamma-secretase inhibitor that has been shown to reduce the rate of formation of amyloid-beta in vitro and in vivo. This study was conducted to characterize the disposition of semagacestat in humans. After a single 140-mg dose of [(14)C]semagacestat administered as an oral solution to six healthy male subjects, semagacestat was rapidly absorbed (T(max) approximately 0.5 h) and eliminated from the systemic circulation (terminal t(1/2) approximately 2.4 h). The major circulating metabolites of semagacestat, M2 (hydrolysis of the amide bond proximal to the benzazepine ring) and M3 (benzylic hydroxylation of the benzazepine ring), accounted for approximately 27 and 10% of total radioactivity exposure, respectively, as calculated from relative area under the plasma concentration versus time curve from 0 to 24 h derived from the plasma radiochromatograms. The radioactive dose was almost completely recovered after 7 days postdose, with 87% of the dose in urine and 8% in feces. Unchanged [(14)C]semagacestat in urine accounted for approximately 44% of the dose, which indicates that renal excretion played an important role in elimination. Metabolites M2 and M3, with their related secondary metabolites, each accounted for approximately 20% of the dose in excreta. In vitro data indicate the formation of M3 is primarily mediated by CYP3A, with cDNA-expressed CYP3A5 approximately 2 times more efficient than CYP3A4 in forming M3. Thus, the relative content of CYP3A4 and CYP3A5 in humans will likely determine the formation clearance of M3 after exposure to semagacestat.

Predictions of the in vivo clearance of drugs from rate of loss using human liver microsomes for phase I and phase II biotransformations.

PURPOSE: The utility of in vitro metabolism to accurately predict the clearance of hepatically metabolized drugs was evaluated. Three major goals were: (1) to optimize substrate concentration for the accurate prediction of clearance by comparing to Km value, (2) to prove that clearance of drugs by both oxidation and glucuronidation may be predicted by this method, and (3) to determine the effects of nonspecific microsomal binding and plasma protein binding. METHODS: The apparent Km values for five compounds along with scaled intrinsic clearances and predicted hepatic clearances for eight compounds were determined using a substrate loss method. Nonspecific binding to both plasma and microsomal matrices were also examined in the clearance calculations. RESULTS: The Km values were well within the 2-fold variability expected for between laboratory comparisons. Using both phase I and/or phase II glucuronidation incubation conditions, the predictions of in vivo clearance using the substrate loss method were shown to correlate with published human clearance values. Of particular interest, for highly bound drugs (>95% plasma protein bound), the addition of a plasma protein binding term increased the accuracy of the prediction of in vivo clearance. CONCLUSIONS: The substrate loss method may be used to accurately predict hepatic clearance of drugs.

Interactions of two major metabolites of prasugrel, a thienopyridine antiplatelet agent, with the cytochromes P450.

The biotransformation of prasugrel to R-138727 (2-[1-2-cyclopropyl-1-(2-fluorophenyl)-2-oxoethyl]-4-mercapto-3-piperidinylidene]acetic acid) involves rapid deesterification to R-95913 (2-[2-oxo-6,7-dihydrothieno[3,2-c]pyridin-5(4H)-yl]-1-cyclopropyl-2-(2-fluorophenyl)ethanone) followed by cytochrome P450 (P450)-mediated formation of R-138727, the metabolite responsible for platelet aggregation. For identification of the P450s responsible for the formation of the active metabolite, the current studies were conducted with R-95913 as the substrate. Incubations required supplementation with reduced glutathione. Hyperbolic kinetics (K(m) 21-30 microM), consistent with a single enzyme predominating, were observed after incubations with human liver microsomes. Correlation analyses revealed a strong relationship between R-138727 formation and CYP3A-mediated midazolam 1'-hydroxylation (r(2) = 0.98; p < 0.001) in a bank of characterized human liver microsomal samples. The human lymphoblast-expressed enzymes capable of forming R-138727, in rank order of rates, were CYP3A4>CYP2B6>CYP2C19 approximately CYP2C9>CYP2D6. A monoclonal antibody to CYP2B6 and the CYP3A inhibitor ketoconazole substantially inhibited R-138727 formation, whereas inhibitors of CYP2C9 (sulfaphenazole) and CYP2C19 (omeprazole) did not. Scaling of in vitro intrinsic clearance values from expressed enzymes to the whole liver using a relative abundance approach indicated that either CYP3A4 alone or CYP3A4 and CYP2B6 are the major contributors to R-138727 formation. R-95913 and R-138727 were also examined for their ability to inhibit metabolism mediated by five P450s. R-138727 did not inhibit the P450s tested. In vitro, R-95913 inhibited CYP2C9, CYP2C19, CYP2D6, and CYP3A, with K(i) values ranging from 7.2 microM to 82 microM, but did not inhibit CYP1A2. These K(i) values exceed circulating concentrations in humans by 3.8- to 43-fold. Therefore, neither R-95913 nor R-138727 is expected to substantially inhibit the P450-mediated metabolism of coadministered drugs.

Clinical pharmacokinetics of atomoxetine.

Atomoxetine (Strattera, a potent and selective inhibitor of the presynaptic norepinephrine transporter, is used clinically for the treatment of attention-deficit hyperactivity disorder (ADHD) in children, adolescents and adults. Atomoxetine has high aqueous solubility and biological membrane permeability that facilitates its rapid and complete absorption after oral administration. Absolute oral bioavailability ranges from 63 to 94%, which is governed by the extent of its first-pass metabolism. Three oxidative metabolic pathways are involved in the systemic clearance of atomoxetine: aromatic ring-hydroxylation, benzylic hydroxylation and N-demethylation. Aromatic ring-hydroxylation results in the formation of the primary oxidative metabolite of atomoxetine, 4-hydroxyatomoxetine, which is subsequently glucuronidated and excreted in urine. The formation of 4-hydroxyatomoxetine is primarily mediated by the polymorphically expressed enzyme cytochrome P450 (CYP) 2D6. This results in two distinct populations of individuals: those exhibiting active metabolic capabilities (CYP2D6 extensive metabolisers) and those exhibiting poor metabolic capabilities (CYP2D6 poor metabolisers) for atomoxetine. The oral bioavailability and clearance of atomoxetine are influenced by the activity of CYP2D6; nonetheless, plasma pharmacokinetic parameters are predictable in extensive and poor metaboliser patients. After single oral dose, atomoxetine reaches maximum plasma concentration within about 1-2 hours of administration. In extensive metabolisers, atomoxetine has a plasma half-life of 5.2 hours, while in poor metabolisers, atomoxetine has a plasma half-life of 21.6 hours. The systemic plasma clearance of atomoxetine is 0.35 and 0.03 L/h/kg in extensive and poor metabolisers, respectively. Correspondingly, the average steady-state plasma concentrations are approximately 10-fold higher in poor metabolisers compared with extensive metabolisers. Upon multiple dosing there is plasma accumulation of atomoxetine in poor metabolisers, but very little accumulation in extensive metabolisers. The volume of distribution is 0.85 L/kg, indicating that atomoxetine is distributed in total body water in both extensive and poor metabolisers. Atomoxetine is highly bound to plasma albumin (approximately 99% bound in plasma). Although steady-state concentrations of atomoxetine in poor metabolisers are higher than those in extensive metabolisers following administration of the same mg/kg/day dosage, the frequency and severity of adverse events are similar regardless of CYP2D6 phenotype.Atomoxetine administration does not inhibit or induce the clearance of other drugs metabolised by CYP enzymes. In extensive metabolisers, potent and selective CYP2D6 inhibitors reduce atomoxetine clearance; however, administration of CYP inhibitors to poor metabolisers has no effect on the steady-state plasma concentrations of atomoxetine.

Effect of tadalafil on cytochrome P450 3A4-mediated clearance: studies in vitro and in vivo.

OBJECTIVES: Tadalafil was examined in vitro and in vivo for its ability to affect human cytochrome P450 (CYP) 3A-mediated metabolism. METHODS: Reversible and mechanism-based inhibition of CYP3A by tadalafil was examined in human liver microsomes. The ability of tadalafil to influence CYP3A activity was also examined in primary cultures of human hepatocytes. The effect of tadalafil on the pharmacokinetics of CYP3A probe substrates was evaluated in human volunteers before and after coadministration with either a single dose or multiple doses of tadalafil (10 or 20 mg). RESULTS: Negligible competitive inhibition of CYP3A was observed in vitro. Mechanism-based inhibition of CYP3A was detected, albeit with a low potency. In human hepatocytes, exposure to 1 micromol/L or greater of tadalafil resulted in increased CYP3A protein expression; however, as with a combined effect of induction and inhibition, a corresponding increase in CYP3A activity did not occur. The clinical pharmacokinetics of midazolam and lovastatin, probe substrates of CYP3A, were unaffected by up to 14 days of tadalafil administration (90% confidence intervals for the ratio of least squares means for the pharmacokinetic parameters of tadalafil were contained within the no-effect boundaries of 0.7 to 1.43). CONCLUSIONS: In vitro results suggested that tadalafil would have little effect on the pharmacokinetics of drugs metabolized by CYP3A. Clinical studies demonstrated that the pharmacokinetics of 2 different CYP3A substrates, midazolam and lovastatin, were virtually unchanged after tadalafil coadministration. Thus therapeutic concentrations of tadalafil do not produce clinically significant changes in the clearance of drugs metabolized by CYP3A.

The effect of incubation conditions on the enzyme kinetics of udp-glucuronosyltransferases.

Traditionally, the Michaelis-Menten equation has been used to determine kinetic parameters for in vitro glucuronidation assays. Recently, estradiol-3-glucuronide formation was shown to exhibit non-Michaelis-Menten kinetics consistent with autoactivation. A concern with the observation of nontraditional kinetics is that they may result as an artifact of the incubation conditions. To examine this concern, the formation of estradiol-3-glucuronide was investigated using human liver microsomes prepared by two different methods, a range of assay conditions, and activation by alamethecin, sonication, or Brij 58 (polyoxyethylene monocetyl ether). Interestingly, holding the other assay components constant, estradiol-3-glucuronide formation was up to 2.5-fold greater using microsomes prepared in phosphate buffer compared with those prepared in sucrose. Incubations activated by alamethecin consistently exhibited the highest rates of estradiol glucuronidation versus the other activators. Furthermore, estradiol-3-glucuronidation exhibited autoactivation kinetics in all of the conditions investigated (n = 1.2-1.7). Nontraditional kinetics were also observed when other UGT1A1 substrates such as ethinylestradiol, buprenorphine, and anthraflavic acid were studied with both human liver microsomes and recombinant UGT1A1. Naphthol, propofol, morphine, and androstanediol were used as probe UGT substrates selective for UGT1A6, UGT1A9, UGT2B7, and UGT2B15, respectively. Of these substrates, only androstanediol exhibited nontraditional kinetics using human liver microsomes. In conclusion, the Hill and/or Michaelis-Menten equations should be used to fit kinetic data to obtain an accurate assessment of in vitro glucuronidation.

Differential modulation of UDP-glucuronosyltransferase 1A1 (UGT1A1)-catalyzed estradiol-3-glucuronidation by the addition of UGT1A1 substrates and other compounds to human liver microsomes.

Previous results demonstrating homotropic activation of human UDP-glucuronosyltransferase (UGT) 1A1-catalyzed estradiol-3-glucuronidation led us to investigate the effects of 16 compounds on estradiol glucuronidation by human liver microsomes (HLM). In confirmation of previous work using alamethicin-treated HLM pooled from four livers, UGT1A1-catalyzed estradiol-3-glucuronidation demonstrated homotropic activation kinetics (S(50) = 22 microM, Hill coefficient, n = 1.9) whereas estradiol-17-glucuronidation (catalyzed by other UGT enzymes) followed Michaelis-Menten kinetics (K(m) = 7 microM). Modulatory effects of the following compounds were investigated: bilirubin, eight flavonoids, 17alpha-ethynylestradiol (17alpha-EE), estriol, 2-amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP), anthraflavic acid, retinoic acid, morphine, and ibuprofen. Although the classic UGT1A1 substrate bilirubin was a weak competitive inhibitor of estradiol-3-glucuronidation, the estrogens and anthraflavic acid activated or inhibited estradiol-3-glucuronidation dependent on substrate and effector concentrations. For example, at substrate concentrations of 5 and 10 microM, estradiol-3-glucuronidation activity was stimulated by as much as 80% by low concentrations of 17alpha-EE but was unaltered by flavanone. However, at higher substrate concentrations (25-100 microM) estradiol-3-glucuronidation was inhibited by about 55% by both compounds. Anthraflavic acid and PhIP were also stimulators of estradiol 3-glucuronidation at low substrate concentrations. The most potent inhibitor of estradiol 3-glucuronidation was the flavonoid tangeretin. The UGT2B7 substrates morphine and ibuprofen had no effect on estradiol 3-glucuronidation, whereas retinoic acid was slightly inhibitory. Estradiol-17-glucuronidation was inhibited by 17alpha-EE, estriol, and naringenin but was not activated by any compound. This study demonstrates that the interactions of substrates and inhibitors at the active site of UGT1A1 are complex, yielding both activation and competitive inhibition kinetics.

The interactions of a selective protein kinase C beta inhibitor with the human cytochromes P450.

Studies were performed to determine the cytochromes P450 (P450) responsible for the biotransformation of (S)-13[(dimethylamino)methyl]-10,11,14,15-tetrahydro-4,9:16,21-dimetheno-1H, 13H-dibenzo[e,k]pyrrolo[3,4-h][1,4,13]oxadiazacyclohexadecene-1,3(2H)-dione (LY333531) to its equipotent metabolite, N-desmethyl LY333531, and to examine the ability of these two compounds to inhibit P450-mediated metabolism. Kinetic studies indicated that a single enzyme in human liver microsomes was able to form N-desmethyl LY333531 with an apparent K(M) value of approximately 1 microM. The formation rate of N-desmethyl LY333531 was correlated with markers of nine P450s in a bank of 20 human liver microsomes. The only significant correlation observed was with the form-selective activity for CYP3A. Of the nine cDNA-expressed P450s examined, only CYP3A4 and CYP2D6 formed N-desmethyl LY333531. However, CYP3A4 formed N-desmethyl LY333531 at a rate 57-fold greater than that observed with CYP2D6. In incubations with human liver microsomes, quinidine, an inhibitor of CYP2D6, demonstrated little inhibition of metabolite formation while ketoconazole, an inhibitor of CYP3A, demonstrated almost complete inhibition. Thus, CYP3A is responsible for the formation of N-desmethyl LY333531. LY333531 and N-desmethyl LY333531 were also examined for their ability to inhibit metabolism mediated by CYP2D6, CYP2C9, CYP3A, and CYP1A2. LY333531 and N-desmethyl LY333531 were found to competitively inhibit CYP2D6 with calculated K(i) values of 0.17 and 1.0 microM, respectively. Less potent inhibition by these compounds of metabolism mediated by the other three P450s examined was observed. In conclusion, CYP3A is primarily responsible for forming N-desmethyl LY333531. Therefore, alterations in the activity of this enzyme have the potential to affect LY333531 clearance. In addition, LY333531 and its metabolite are predicted to be potential inhibitors of CYP2D6-mediated reactions in vivo.

Comparative metabolic capabilities of CYP3A4, CYP3A5, and CYP3A7.

The human cytochromes P450 (P450) CYP3A contribute to the biotransformation of 50% of oxidatively metabolized drugs. The predominant hepatic form is CYP3A4, but recent evidence indicates that CYP3A5 contributes more significantly to the total liver CYP3A than was originally thought. CYP3A7 is the major fetal form and is rarely expressed in adults. To compare the metabolic capabilities of CYP3A forms for 10 substrates, incubations were performed using a consistent molar ratio (1:7:9) of recombinant CYP3A, P450 reductase, and cytochrome b5. A wide range of substrate concentrations was examined to determine the best fit to kinetic models for metabolite formation. In general, K(m) or S(50) values for the substrates were 3 to 4 times lower for CYP3A4 than for CYP3A5 or CYP3A7. For a more direct comparison of these P450 forms, clearance to the metabolites was determined as a linear relationship of rate of metabolite formation for the lowest substrate concentrations examined. The clearance for 1'-hydroxy midazolam formation at low substrate concentrations was similar for CYP3A4 and CYP3A5. For CYP3A5 versus CYP3A4, clearance values at low substrate concentrations were 2 to 20 times lower for the other biotransformations. The clearance values for CYP3A7-catalyzed metabolite formation at low substrate concentrations were substantially lower than for CYP3A4 or CYP3A5, except for clarithromycin, 4-OH triazolam, and N-desmethyl diltiazem (CYP3A5 - CYP3A7). The CYP3A forms demonstrated regioselective differences in some of the biotransformations. These results demonstrate an equal or reduced metabolic capability for CYP3A5 compared with CYP3A4 and a significantly lower capability for CYP3A7.

Identification of the human cytochromes P450 responsible for atomoxetine metabolism.

Studies were performed to determine the human enzymes responsible for the biotransformation of atomoxetine to its major metabolite, 4-hydroxyatomoxetine, and to a minor metabolite, N-desmethylatomoxetine. Utilizing human liver microsomes containing a full complement of cytochrome P450 (P450) enzymes, average K(m) and CL(int) values of 2.3 microM and 103 microl/min/mg, respectively, were obtained for 4-hydroxyatomoxetine formation. Microsomal samples deficient in CYP2D6 exhibited average apparent K(m) and CL(int) values of 149 microM and 0.2 microl/min/mg, respectively. In a human liver bank characterized for P450 content, formation of 4-hydroxyatomoxetine correlated only to CYP2D6 activity. Of nine expressed P450s examined, 4-hydroxyatomoxetine was formed at a rate 475-fold greater by CYP2D6 compared with the other P450s. These results demonstrate that CYP2D6 is the enzyme primarily responsible for the formation of 4-hydroxyatomoxetine. Multiple P450s were found to be capable of forming 4-hydroxyatomoxetine when CYP2D6 was not expressed. However, the efficiency at which these enzymes perform this biotransformation is reduced compared with CYP2D6. The formation of the minor metabolite N-desmethylatomoxetine exhibited average K(m) and CL(int) values of 83 microM and 0.8 microl/min/mg, respectively. Utilizing studies similar to those outlined above, CYP2C19 was identified as the primary enzyme responsible for the biotransformation of atomoxetine to N-desmethylatomoxetine. In summary, CYP2D6 was found to be the primary P450 responsible for the formation of the major oxidative metabolite of atomoxetine, 4-hydroxyatomoxetine. Furthermore, these studies indicate that in patients with compromised CYP2D6 activity, multiple low-affinity enzymes will participate in the formation of 4-hydroxyatomoxetine. Therefore, coadministration of P450 inhibitors to poor metabolizers of CYP2D6 substrates would not be predicted to decrease the clearance of atomoxetine in these individuals.