DMD#34876 Rapid Communication ASSESSMENT OF A...

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Rapid Communication

ASSESSMENT OF A MICROPATTERNED HEPATOCYTE CO-CULTURE SYSTEM

TO GENERATE MAJOR HUMAN EXCRETORY AND CIRCULATING DRUG

METABOLITES

Wendy WeiWei Wang, Salman R. Khetani, Stacy Krzyzewski, David B. Duignan, and R.

Scott Obach

Pfizer Global Research and Development

Groton, CT 06340 (WWW, DBD, and RSO)

and

Hepregen Corporation

Medford, MA 02155 (SRK and SK)

DMD Fast Forward. Published on July 1, 2010 as doi:10.1124/dmd.110.034876

Copyright 2010 by the American Society for Pharmacology and Experimental Therapeutics.

This article has not been copyedited and formatted. The final version may differ from this version.DMD Fast Forward. Published on July 1, 2010 as DOI: 10.1124/dmd.110.034876

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Running Title: Metabolite Generation in Micropatterned Hepatocyte Co-Culture

Address for Correspondence:

R.S. Obach

Pfizer, Inc.

Eastern Point Rd.

Groton, CT 06340

[email protected]

Number of:

Words in Abstract: 255

Words in Introduction: 749

Words in Discussion: 908

References: 12

Tables: 3

Figures: 2

Abbreviations: ADME: absorption, distribution, metabolism, and excretion; HPLC: high

pressure liquid chromatography


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ABSTRACT

Metabolism is one of the important determinants of the overall disposition of drugs and

the profile of m etabolites can have an impact on effi cacy and safety. Pred icting which

drug metabolites will be quantitatively predominant in humans has become increasingly

important in the r esearch and de velopment o f new dr ugs. In t his s tudy, a novel

micropatterned hepatocyte co -culture s ystem w as e valuated f or i ts ability to g enerate

human in vivo metabolites. Twenty seven compounds of diverse chemical structure and

subject to a ra nge of d rug bi otransformation re actions w ere a ssessed for me tabolite

profiles i n th e m icropatterned c o-culture s ystem u sing p ooled c ryopreserved hu man

hepatocytes. The ability of this system to generate metabolites that are >10% of dose in

excreta or >10% of total drug-related material in circulation was assessed and compared

to previously reported data obtained in human hepatocyte suspensions, liver S-9 fraction,

and li ver mi crosomes. T he mi cropatterned co-culture sy stem was i ncubated for up to

seven days without a change in medium which offered an ability to generate metabolites

for s lowly m etabolized co mpounds. T he micropatterned co -culture s ystem g enerated

82% of the exc retory m etabolites tha t exc eed 10% of dose and 75% of the circulating

metabolites that exceed 10% of total circulating drug-related material. This exceeds the

performance of hepatocyte s uspension incubations and oth er in vit ro s ystems. P hase 1

and phase 2 metabolites were generated, as well as metabolites that arise via two or more

sequential r eactions. T hese r esults s uggest th at this i n v itro s ystem o ffers the h ighest

performance a mong in vi tro m etabolism s ystems t o p redict m ajor hum an in vi vo

metabolites.


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INTRODUCTION

Data on the b iotransformation of a n ew drug represents a c ritical pi ece of

information used to understand its overall disposition in humans and laboratory animals.

Knowledge o f the m ain m etabolism r outes is im portant in u nderstanding the m ain

clearance mechanisms, potential pharmacologically active metabolites, potential for inter-

patient differences in exposure, and drug-drug interactions. It is also critically important

to c ompare the m ain m etabolism pa thways of a n ew d rug can didate in humans vs .

animals, since laboratory animal species are used in safety evaluations. It is expected that

major human metabolites are represented in animal safety s tudies; i.e. that each human

metabolite that is present in circulation at 10% or more of the total drug-related material

will be present in at least one animal species that is used in safety evaluations at equal or

greater exp osure le vels (A trakchi, 200 9; R obison and J acobs, 2009; I nternational

Conference on Ha rmonization, 2009). S uch exp ectations ha ve b een d escribed in

regulatory guidance, and are laid out to ensure that the human metabolites of new drugs

have be en ade quately te sted f or s afety. How ever, in the ty pical dr ug de velopment

process, quantitative information on the circulating and excretory metabolites in humans

is on ly a vailable la ter s ince th e s tudies n eeded t o ga ther s uch in formation a re r esource

intensive. Many research organizations wait until after a new compound shows clinical

promise in a t argeted in dication be fore inv esting in the s tudies to g ain q uantitative

metabolite profiles (i.e. radiolabel ADME studies).

Thus, in vitro approaches and systems from which reliable predictions of in vivo

human m etabolite pr ofiles ca n be m ade ar e h ighly de sired. Co mparisons o f i n v itro

metabolism profiles across species can provide an early warning as to whether humans


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could have a different major pathway of metabolism than animals, and appropriate action

can be taken earlier so as to not delay the clinical development process. However in vitro

systems can possess so me sh ortcomings w hen u sed t o predict t he total i n v ivo

metabolism profiles in humans. Some systems, such as subcellular fractions, are limited

by the complement o f dr ug-metabolizing e nzymes pr esent, a nd t hus do not pr ovide a

complete picture of the metabolism. In other cases, some drugs are metabolized through

multiple sequential reactions in vivo before the drug-related material is excreted, while

the in vitro systems will only carry out one or two sequential reactions. Finally, when

attempting to pr edict w hether a metabolite w ill be pr esent i n circulation, o ther

dispositional a nd distributional properties o f the m etabolite w ill hav e a n impact, a nd

presently this is difficult to predict. In a previous investigation, human liver microsomes,

human liver S-9 fraction, and human hepatocyte suspensions were tested for their success

rates in the generation of major human metabolites that had been observed in previously

run r adiolabeled hu man A DME s tudies (Da lvie, et a l., 2009). W hile i t w as rea dily

demonstrated that major metabolites of many compounds could be generated by in v itro

systems, rat es o f su ccess g enerally were i n t he ran ge o f 5 0%. S imilar fi ndings w ere

made by Anderson, et al., (2009). Thus, there is considerable room for improvement for

in vitro systems as applied to the generation of relevant human metabolite profiles.

Hepatocytes presently offer the most complete complement of drug-metabolizing

enzymes for the generation of metabolite profiles. The typical use of human hepatocytes

in m etabolite gen eration in volves i ncubations of new c ompounds w ith s uspensions of

primary cells (fresh or cryopreserved). However these studies are limited by the duration

over which incubations can be run, since metabolic capacity declines after a few hours,


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and i n m any cas es m etabolite pr ofiles o f co mpounds that ar e e ither s lowly and/o r

extensively metabolized are inadequate. H epatocyte culture systems in w hich the cells

are l onger-lived have generally no t been u sed f or the generation o f m etabolite profiles

because it is well-known that the expression levels of various drug-metabolizing enzymes

change (Hewett, et al., 2007; Guillouzo and Guguen-Guillouzo, 2008). Thus, unrealistic

metabolite profiles w ould b e obt ained. R ecently, a n ovel m icropatterned c o-culture

system has be en de veloped an d i t h as been de monstrated that im portant drug-

metabolizing enzyme expression levels are maintained over extended time periods (24-42

days) (Khetani and Bhatia, 2008). Such a system offers the potential to generate superior

human m etabolite p rofiles, s ince en zyme l evels a re m aintained an d the pot ential exi sts

for le ngthy inc ubation t imes ( i.e. m ultiple day s) to be tter han dle s lowly m etabolized

drugs. T he o bjective o f t his s tudy w as to de termine t he s uccess r ate o f this

micropatterned co -culture s ystem to g enerate m ajor h uman m etabolites. A s et o f 27

compounds (Figure 1) for w hich metabolite profile data from human radiolabel ADME

studies were available had been previously used to assess the ability of human in vitro

systems to g enerate m ajor human m etabolites. T his s ame s et w as us ed in t he present

study and the metabolite profile data from the micropatterned co-culture were compared

to the previous data.


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METHODS

Preparation of Micropatterned Hepatocyte Co-Culture. Plateable cryopreserved primary

human hepatocyte v ials were purchased f rom Celsis In Vitro Technologies (Baltimore,

MD) (lots RCP and BOB), and BD Biosciences (Woburn, MA) (lot 109). Cryopreserved

hepatocyte vials were thawed at 370C for 90 -120 seconds followed by d ilution with 50

mL of warm Hepregen-customized and proprietary hepatocyte culture medium (HCM).

The cell suspension was spun at 50xg for 5 minutes. The supernatant was discarded, cells

were r esuspended i n H CM, a nd v iability w as as sessed using T rypan blue e xclusion

(typically 70–90%). Liver-derived nonparenchymal cells, as judged by their size (~10 um

in diameter) and morphology (nonpolygonal), were consistently found to be less than 1%

in these preparations.

To c reate m icropatterned co-cultures in 24-well p lates, w e fi rst p roduced a

hepatocyte pa ttern by s eeding hepatocytes ( pooled s uspension f rom the three s eparate

hepatocyte donors) on collagen- patterned substrates that mediate selective cell adhesion.

The cells were washed with medium 4-6 hours later to remove unattached cells (leaving

~30,000 a ttached hepatocytes on 91 collagen-coated i slands) a nd in cubated in HCM.

Stromal cells were seeded 12–24 h later t o create co-cultures (Khetani and Bhatia, 2008).

Culture medium was replaced every 2 days (400 uL per well) pr ior to incubation with

compounds.

Metabolism Incubations. T wo s eparate s tudies ut ilizing a ll of t he 2 7 c ompounds were

conducted. F or e ach st udy, m icropatterned co -cultures co ntaining po oled he patocytes

from 3 se parate donors w ere a llowed 7 days t o fu lly st abilize w ith re spect t o li ver-

specific functions. Cultures were washed to remove serum and compounds in serum-free


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HCM (400 uL per well) were added to the cells. At 2 and 7 days the culture medium was

removed f rom 2 r epresentative w ells and immediately f rozen on dr y ice . T ime po ints

selected w ere bas ed o n a n initial a ssessment o f metabolite pr ofiles o bserved a t time

points ranging from 4 h r to 10 days for six of the compounds. Samples were kept a t -

800C until further analysis.

HPLC-MS/MS Analysis. A nalyses of i ncubation s amples for 2 7 c ompounds w ere

performed on a Thermo LTQ system. The system consisted of an Agilent HPLC injector,

a HP-11 00 qu aternary gra dient pump, an d a HP-11 00 diode a rray d etector (A gilent

Technologies, Palo Alto, CA) in line with a LTQ mass spectrometer (Thermo, Waltham,

MA). The chr omatography was pe rformed us ing a P olaris C18 (4.6 × 250 m m; 5 μm;

Varian, Lake Forest, CA) column. The mobile phase consisted of 0.1% formic acid (A)

and ac etonitrile (B ), and w as delivered a t a flow ra te of 0 .8 m L/min. T he gra dient

consisted of 5% B for 5 min followed by a linear gradient to 80% B at 50 min. This was

followed by a 10 m in re-equilibration of the column at 95% A. The effluent was passed

through the diode array detector operated in the wavelength range of 200 to 400 nm. This

was followed by introduction, at a split, of approximately 20 to 1, into the source of the

mass spectrometer. The mass spectrometer was operated in a p ositive ion mode and was

equipped with an electrospray ionization source. The source parameters for the LTQ were

source potential, 4.5 kV; capillary potential, 2 V; source temperature, 3500C. The mass

spectrometer was op erated in a data dependent scanning mode t o MS3. Th e n ormalized

collision energy for the data dependent scanning was 30-40%.


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RESULTS AND DISCUSSION

In a p reviously reported s tudy, 27 compounds for w hich quantitative metabolite

profiles in cir culation and e xcreta w ere av ailable f rom hum an r adiolabel s tudies w ere

examined in three in v itro systems to determine how well these in v itro systems could

generate m etabolites th at r epresent at l east 1 0% o f do se o r 10% o f c irculating dr ug-

related m aterial (Da lvie, et a l, 2009). T his s ame s et of c ompounds w as u sed in th e

present an alysis o f the m icropatterned co -culture sy stem so that a c omparison o f

performance could be made. The 27 compounds represent a range of structure types and

a variety of drug biotransformation reactions (Table 1). Also, some of the metabolites are

the product of a s ingle bi otransformation reac tion w hile ot hers a rise via t wo or m ore

sequential reactions. For these 27 compounds, a total of 56 metabolites were observed in

humans at 10% or more of ei ther c irculating d rug-related material or exc reted dose (or

both). In the previous work, liver microsomes, liver S-9 fraction, and human hepatocyte

suspension produced 22(39%), 26(46%), and 31(55%) of these metabolites, respectively

(Dalvie, e t al ., 2009). T he m icropatterned co-culture sy stem can be i ncubated m uch

longer than hepatocyte suspensions, and 2 and 7 day incubations of this system yielded

38 ( 68%) a nd 43 ( 73%) o f the se m etabolites, r espectively. A list o f the m etabolites

detected in each of the in vitro systems is shown in Table 2. The in vivo metabolites that

were not generated were similar across al l four systems; there was only one metabolite

that w as not o bserved i n the c o-culture s ystem t hat had been previously ob served i n

hepatocyte suspension.

The data are broken down by categories of metabolites in Table 3. In a ll cases,

the c o-culture s ystem ou tperformed a ll ot her i n vi tro s ystems. F or t he 39 exc retory


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metabolites, a seven day incubation of the micropatterned co-culture system yielded 82%

of t hese, a s c ompared t o hepatocyte s uspension w hich y ielded 6 4%. E xcretory

metabolites t hat were one s tep away f rom the par ent drug were generated in 15 o f 16

cases in the 7-day incubation, while those requiring two or more steps were generated at a

lower f requency, al beit at a notable im provement o ver o ther in v itro s ystems.

Metabolites ar ising v ia functionalization ( phase 1) an d conjugation (phase 2) r eactions

were generated at equal frequencies.

For some of the compounds, a direct comparison of the micropatterned co-culture

system and suspension incubations were made using the same pool of hepatocytes. This

was do ne to e nsure th at the co -culture s ystem was no t o utperforming the pr evious

suspension incubations by virtue of different metabolic capacities of different hepatocyte

pools. Example HPLC-UV chromatograms for linezolid and ziprasidone incubations are

shown in Figure 2. Ziprasidone has four important human metabolites which arise via N-

dealkylation, sulfoxidation, reduction, and methylation reactions (Prakash, et al., 1997).

The m icropatterned c o-culture s ystem gen erated th ree of f our of t hese m etabolites in

good quantity while the suspension incubation yielded just two and in low quantities. For

linezolid, w hich is a r elatively s lowly m etabolized co mpound ( Slatter, e t al ., 2 001;

Wienkers, 2000), the major oxidative metabolites were not identified in suspension, but

both were shown in the micropatterned co-culture system.

The generation of relevant human metabolites using in vitro systems represents an

important need i n t he d iscovery and de velopment o f ne w dr ugs. T here has be en a n

increasing e mphasis o n e nsuring th at m ajor h uman metabolites ar e ade quately

represented in animal toxicology studies of the parent molecule (Atrakchi, 2009; Robison


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and Jacobs, 2010; Smith and Obach, 2009). Identifying a major human metabolite for the

first time in a clinical study can cause delays in the development of a new drug, since that

metabolite will req uire a ttention t o assure th at it s r isk has been adequately q ualified in

preclinical s afety s tudies b efore s tudies c an c ontinue. T hus ga ining in sight int o which

metabolites may be quantitatively important in humans in v ivo prior to clinical s tudies

would be adv antageous, s ince t hen it can be determined w hether t hese m ajor h uman

metabolites w ere pr esent i n l aboratory ani mal s pecies us ed to test f or t oxicity o f the

parent co mpound. I n v itro m etabolism e xperiments using w idely av ailable hum an-

derived r eagents ( e.g. l iver m icrosomes, S -9 f raction, he patocytes) hav e bee n us ed

routinely to better understand the metabolism of new compounds. However, while these

systems ar e us eful, t hey do not generate al l im portant cir culating and e xcretory

metabolites. One of the reasons for this may be that the incubations do not remain active

for e xtended incubation pe riods. A lso, t he determinants o f w hich m etabolites w ill be

major in humans in vivo is driven not only by the extent of their generation, but also their

individual dispositional properties (e.g. rate of subsequent metabolism, rate and extent of

active s ecretion in to exc retory b iofluids, and di stribution into ti ssues). T he

micropatterned co -culture s ystem o ffers an ab ility to car ry out m etabolism incubations

for periods of up to 7 days without changing the medium. T hus, a drug added to this

system c an be s ubjected to m ultiple s equential m etabolic rea ctions. A lso, m etabolites

generated from drugs that are very slowly but extensively metabolized can be observed in

a 7-day incubation.

In co nclusion, t he m icropatterned human hepatocyte co -culture s ystem o ffers a

superior in vitro approach to generate major human metabolites. S uch a system can be


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used for generating human metabolite profiles that are more realistic to the in vivo profile.

Furthermore, the potential exists for applying this system to other types of in v itro drug

metabolism e xperiments t hat are us ed to pr edict a nd/or understand the human

dispositional pr ofile o f dr ugs, s uch as p harmacokinetics a nd dr ug-drug inte ractions.

Investigations into these areas are ongoing.


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REFERENCES

Anderson S, L uffer-Atlas D, a nd K nadler M P ( 2009) Pre dicting C irculating H uman

Metabolites: How Good Are We? Chem. Res. Toxicol. 22: 243–256.

Atrakchi A H ( 2009) I nterpretation an d Considerations o n the S afety Evaluation o f

Human Drug Metabolites. Chem. Res. Toxicol. 22: 1217-1220.

Dalvie D, Ob ach RS, Kang P, Pra kash C, Loi C M, Hu rst S, Ne dderman A , Gou let L,

Smith E, Bu HZ, and Smith DA. (2009) Assessment of Three Human in Vitro Systems

in the Generation of Major Human Excretory and Circulating Metabolites. C hem. Res.

Toxicol. 22: 357-368.

Guillouzo A and Guguen-Guillouzo C. (2008) Evolving concepts in liver tissue modeling

and implications for in vitro toxicology. Expert Opin. Drug Metab. Toxicol. 4: 1279-1294.

Hewitt N J, L echon MJ G, H ouston J B, e t al . ( 2007) Pri mary h epatocytes: c urrent

understanding of t he regu lation of m etabolic en zymes a nd t ransporter p roteins, an d

pharmaceutical practice f or the us e of he patocytes in m etabolism, e nzyme in duction,

transporter, clearance, and hepatotoxicity studies. Drug Metab. Rev. 39: 159-234.

International Conference on Ha rmonization (200 9) G uidance o n nonclinical s afety

studies f or t he co nduct o f human cl inical tr ials and m arketing a uthorization f or


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pharmaceuticals M 3(R2). http://www.ich.org/cache/compo/276-254-1.html ( accessed,

May 5, 2010).

Khetani S R and Bhatia S N ( 2008) Microscale cul ture o f h uman l iver ce lls f or dr ug

development. Nat. Biotechnol. 26: 120-126.

Prakash C, Kamel A, Gummerus J, and Wilner K. (1997) Metabolism and excretion of a

new antipsychotic drug, ziprasidone, in humans. Drug Metab. Dispos. 25: 863-872.

Robison TW and Jacobs A ( 2009) Metabolites in safety testing. Bioanalysis 1: 1193-

1200.

Slatter JG, S talker DJ, F eenstra KL, Welshman IR, Bruss JB, Sams JP , Johnson MG,

Sanders PE, H auer MJ, F agerness PE, St ryd R P, Pe ng G W, a nd Sh obe EM (200 1)

Pharmacokinetics, m etabolism, a nd excretion o f l inezolid f ollowing an o ral do se o f

[14C]linezolid to healthy human subjects. Drug Metab. Dispos. 29: 1136-1145.

Smith DA and Obach RS (2009) Metabolites in Safety Testing (MIST): Considerations of

Mechanisms of Toxicity with Dose, Abundance, and Duration of Treatment. Chem. Res.

Toxicol 22: 267-279.

Wienkers LC. (2000) Oxidation of the novel oxazolidinone antibiotic linezolid in human

liver microsomes. Drug Metab. Dispos. 28: 1014-1017.


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FIGURE LEGENDS

FIGURE 1. Chemical structures of the 27 drugs used in this analysis.

FIGURE 2 . HPL C-UV c hromatograms of lin ezolid (left ) a nd zi prasidone (ri ght) in

micropatterned human hepatocyte co-cultures (0 hr, 4 hr , 48 hr , 7 days) and suspended

human he patocytes ( 4 hr-s). L = l inezolid, a a nd b = morpholine r ing o pened ac id

metabolites, Z = ziprasidone, 1 = N-dealkylziprasidone S-oxide, 2 = ziprasidone S-oxide,

3 = S-methyldihydroziprasidone.


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TABLE 1. Metabolites for the 27 compounds utilized in this analysis and their amount in human circulation and excreta. The amount in circulation or excreta are included only if values exceed 10%.

compound name in vivo human metabolites

Ph 1 or

Ph 2

primary or

secondary

metabolite

% in

excreta

% of

circulating

radioactivity

gemcabene gem cabene glucuronide 2 1 44

avasimibe de hydrogenated avasimibe 1 1 16

h ydroxyavasimibe 1 1 10

pagoclone h ydroxypagoclone 1 1 65

axitinib hy droxyaxitinib 1 1 11

a xitinib sulfoxide 1 1 16

a xitinib glucuronide 2 1 50

capravirine hy droxycapravirine sulfoxide 1 2 11

hy droxycapraivirinesulfone N-oxide 1 2 10

CJ-13610 C J-13610 sulfoxide 1 1 36 17

C J-13610 sulfone 1 2 21 10

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traxoprodil traxoprodil methoxy sulfate 2 2 40 28

traxoprodil methoxy glucuronide 2 2 10 18

CP-122721 desmethyl CP-122721 glucuronide 2 2 27 14

N-dealkylated CP-122721 glucuronide 2 2 11

de smethylhydroxyCP-122721 glucuronide 2 2 25

5 -trifluoromethoxysalicylic acid 1 2 56

tofimulast di hydroxytofimulast 1 2 23 14

r ing-opened tofimulast 1 2 33

d esthiophene tofimulast 1 2 13

lasofoxifene la sofoxifene glucuronide 2 1 22

capromorelin carboxylic acid of capromorelin 1 2 11 14

O -debenzyl hydroxycapromorelin 1 2 12

carboxylic acid of N-desmethyl-O-

debenzylcapromorelin 1 2 12

N -desmethyl-O-debenzyl hydroxycapromorelin 1 2 15




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torcetrapib bistrifluoromethyl benzoic acid 1 2 50 50

7- trifluoromethylquinaldic acid 1 2 29 63

CP-533536 h ydroxy CP-533536 1 1 70

C P-533536 sulfate 2 1 11

CP-547632 N-d ealkyl CP-547632 1 1 15

zoniporide hy droxyzoniporide 1 1 52 64

carboxylic acid of zoniporide 1 2 17

celecoxib carboxylic acid of celecoxib 1 2 73 20

c elecoxib glucuronide 2 2 15

CP-690550 h ydroxy CP-690550 1 1 20 12

d ihydroxy CP-690550 1 2 12 12

dihydroxy CP-690550 glucuronide 2 2 11 13

ziprasidone zi prasidone sulfoxide 1 1 18 69

S -methyldihydroziprasidone 1 2 18 69

N -dealkylziprasidone S-oxide 1 2 11 21




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N -dealkylziprasidone sulfone 1 2 11 21

sunepitron hy droxysunepitron 1 1 17 61

trovafloxacin t rovafloxacin glucuronide 2 1 13 22

linezolid r ing-opened linezolid 1 2 45

r ing-opened linezolid 1 2 10

sunitinib N-d ealkyl sunitinib 1 1 32 21

irinotecan ring opened carboxylic acid 1 2 11

delavirdine N -dealkyldelavirdine 1 1 46 25

de pyridinyl delavirdine 1 1 38

valdecoxib h ydroxyvaldecoxib glucuronide 2 2 23

va ldecoxib N-glucuronide 2 1 20

eplerenone 6β-hydroxyeplerenone 1 1 32 16

6β,21-dihydroxeplerenone 1 2 21

maraviroc h ydroxymethyl maraviroc 1 1 13

N-d esalkyl maraviroc 1 2 22




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N-desalkyl hydroxymethyl maraviroc 1 2 11




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TABLE 2. Human metabolites detected in incubations with micropatterned human hepatocyte co-culture as compared with other in

vitro human liver systems. There was 100% concordance in metabolite formation between the two separate micropatterned co-culture

studies. Data for hepatocytes, S9 and microsomes are taken from Dalvie et al, 2009.

Metabolites Detected in:

Micropatterned Co-

Culture Incubated for:

Compound In Vivo Human Metabolites Hepatocytes S9 Microsomes 48 hr 7 day

gemcabene gem cabene glucuronide no no no yes yes

avasimibe de hydrogenated avasimibe no no no yes yes

hy droxyavasimibe no no no no no

pagoclone hydroxypagoclone yes yes n o yes yes

axitinib hy droxyaxitinib yes yes y es yes yes

a xitinib sulfoxide yes yes yes yes yes

axitinib glucuronide yes n o n o yes yes

capravirine h ydroxycapravirine sulfoxide yes yes yes yes yes




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hydroxycapraivirinesulfone N-oxide yes yes n o yes yes

CJ-13610 C J-13610 sulfoxide yes yes yes yes yes

C J-13610 sulfone yes yes yes yes yes

traxoprodil traxoprodil methoxy sulfate yes no no yes yes

traxoprodil methoxy glucuronide yes no no yes yes

CP-122721 desmethyl CP-122721 glucuronide yes yes yes yes yes

N-dealkylated CP-122721 glucuronide no no no no no

desmethylhydroxy CP-122721 glucuronide no no no no no

5- trifluoromethoxysalicylic acid no no no no no

tofimulast d ihydroxytofimulast no yes yes yes yes

ring-opened tofimulast yes y es no yes yes

d esthiophene tofimulast no no no yes yes

lasofoxifene la sofoxifene glucuronide yes yes yes yes yes

capromorelin carboxylic acid of capromorelin no no no no no

O -debenzyl hydroxycapromorelin no no yes yes yes




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carboxylic acid of N-desmethyl-O-

debenzylcapromorelin no no no no no

N-desmethyl-O-debenzyl hydroxycapromorelin no no no yes y es

torcetrapib bistrifluoromethyl benzoic acid no no no no no

7 -trifluoromethylquinaldic acid no yes yes yes yes

CP-533536 h ydroxy CP-533536 yes yes yes yes yes

C P-533536 sulfate no no no yes yes

CP-547632 N -dealkyl CP-547632 no no no no no

zoniporide h ydroxyzoniporide yes yes yes yes yes

zoniporide carboxylic acid yes no no no yes

celecoxib carboxylic acid of celecoxib yes yes no yes yes

celecoxib glucuronide yes n o n o yes yes

CP-690550 h ydroxy CP-690550 no no yes no yes

d ihydroxy CP-690550 yes yes yes yes yes

dihydroxy CP-690550 glucuronide no no no no no




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ziprasidone zi prasidone sulfoxide yes yes yes yes yes

S-methyldihydroziprasidone yes y es no yes yes

N -dealkylziprasidone S-oxide no no no yes yes

N -dealkylziprasidone sulfone no no no no no

sunepitron h ydroxysunepitron yes yes yes yes yes

trovafloxacin t rovafloxacin glucuronide yes yes yes no yes

linezolid r ing-opened linezolid no no no no yes

r ing-opened linezolid no no no no yes

sunitinib N-d ealkyl sunitinib yes yes yes yes yes

irinotecan ring opened carboxylic acid yes yes yes yes yes

delavirdine N-d ealkyldelavirdine yes yes yes yes yes

de pyridinyl delavirdine no no no no no

valdecoxib hydroxyvaldecoxib glucuronide h metabolite yes yes no yes yes

valdecoxib N-glucuronide yes n o n o yes yes

eplerenone 6β-hydroxyeplerenone yes yes yes yes yes




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6β,21-dihydroxeplerenone yes no no no no

maraviroc h ydroxymethyl maraviroc yes yes yes yes yes

N -desalkyl maraviroc no no no no no

N-desalkyl hydroxymethyl maraviroc no no no yes yes




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TABLE 3. Success of the Micropatterned Hepatocyte Co-Culture System at Generation of Major Human Metabolites for 27 Compounds As Compared to Other In Vitro Systemsb.

Micropatterned Co-

Culture

In Vivo Microsomesa S-9a Hepatocyte

Suspensiona 48 hr 7 days

Excretory Metabolites >10% of Dose:

all excretory metabolites 39 19 (49) 22 (56) 25 (64) 27 (69) 32 (82)

metabolites arising by phase 1 reactions only 29 17 (59) 19 (66) 19 (66) 20 (69) 24 (83)

metabolites arising by a phase 2 reaction 10 2 (30) 3 (30) 6 (60) 7 (70) 8 (80)

metabolites that are one reaction from parent (primary) 16 12 (69) 11 (69) 12 (75) 13 (81) 15 (94)

metabolites that are two or more reactions from parent (secondary) 23 7 (48) 11 (48) 13 (57) 14 (61) 17 (74)

Circulatory Metabolites >10% of Total Drug-Related Material:

all circulating metabolites 40 17 (43) 19 (48) 21 (53) 28 (70) 30 (75)

metabolites arising by phase 1 reactions only 31 14 (52) 16 (52) 14 (45) 22 (71) 23 (74)

metabolites arising by a phase 2 reaction 9 3 (33) 3 (33) 7 (78) 6 (67) 7 (78)

metabolites that are one reaction from parent (primary) 16 11 (69) 11 (69) 12 (75) 12 (75) 14 (88)

metabolites that are two or more reactions from parent (secondary) 24 6 (25) 8 (33) 9 (38) 16 (67) 16 (67) aData from Dalvie, et al., 2009; bValues in parentheses represent success rates expressed as percentages.




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N

N

N

S

Cl

Cl

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O S NH

O

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NN

NN NCl N

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OH ON

N

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F3C

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F3C

CF3

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capravirine

avasimibe

axitinibpagoclone

CP-122721traxoprodilCJ-13610

lasofoxifene capromorelin torcetrapib

CP-533536

zoniporidecelecoxib

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ziprasidone sunipetron

trovafloxacin

linezolid

sunitinibirinotecan

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