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Department of Medicinal Chemistry (J.M.N., K.L.K., R.H.L., W.F.T.), School of Pharmacy, University of Washington, Seattle, Washington and Department of Medicine (R.A.O.), Santa Clara Valley Medical Center, San Jose, California
(Received January 7, 2003; Accepted April 22, 2003)
| Abstract |
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The implicit assumption of the guidance and indeed of all in vitroin
vivo correlations is that the qualitative behaviors of the P450s are largely
independent of their external biochemical environments. Thus, the same P450
should form the same primary metabolites from a given substrate and an
inhibitor should inhibit the same enzymes, both in vitro and in vivo
(Wrighton et al., 1993
;
Houston, 1994
;
Rodrigues, 1994
;
Ball et al., 1995
;
Houston and Carlile, 1997
;
Iwatsubo et al., 1997
;
Rodrigues and Wong, 1997
;
Ito et al., 1998
). The
assumption is essential because without it, in vitroin vivo
correlations would not be possible. Accumulated evidence suggests that in
general it does hold, at least qualitatively. Quantitatively, the picture is
much less clear and often problematic.
Of the possible in vitro kinetic inhibition parameters that might be used to predict the magnitude of an in vivo drug interaction resulting from competitive inhibition, the in vitro Ki is particularly useful. It is a constant that can be readily determined.2 Moreover, it is a constant that is largely independent of substrate identity and one that can be used to predict enzyme behavior over a large range of substrate and enzyme concentrations.
However, even competitive inhibition, the simplest of cases, is subject to
at least three potential problems that can result in significant differences
in the in vitro and in vivo properties of an enzyme. First, equal nominal
concentrations of inhibitor in plasma or microsomes do not guarantee equal
concentrations of the inhibitor at the active site of the enzyme in the in
vivo and in vitro environments. Active uptake or differences in lipid
solubility and/or protein binding properties in the immediate vicinity of the
enzyme could foster differences in concentrations
(von Moltke et al., 1994
;
Obach, 1996
;
Iwatsubo et al., 1997
;
Yamano et al., 1999
). Second,
differences between the two environments in factors such as pH, ionic strength
or solvent could perturb enzyme activity. Different pHs or ionic strengths can
alter active site water content, conformational architecture, and/or
reactivity by modulating environmental charge
(Schrag and Weinkers, 2000
).
The common solvents used to dissolve inhibitor in in vitro experiments can
have differential effects on the measured enzyme kinetic parameters
(Busby et al., 1999
;
Tang et al., 2000
;
Easterbrook et al., 2001
).
Third, a metabolite of the inhibitor, rather than the inhibitor itself, could
be the primary species inhibiting the enzyme. Although significant metabolite
inhibition is probably uncommon, it does happen
(He et al., 1995
;
Schmider et al., 1999
). When
it does, it can easily be missed because the time frame of microsomal
experiments are often insufficient to produce the levels of metabolite
generated in vivo and thereby produce the magnitude of inhibition seen in
vivo. The overall effect of these three problems in general is to render a
given concentration of the inhibitor to be more potent in vivo than it is in
vitro. This is particularly true with highly lipid soluble inhibitors.
Despite these problems, the ability to predict drug interactions is a goal
clearly worth pursuing. But, recognizing that greater understanding is
required before the problems associated with using an in vitro
Ki as a predictor of inhibition in vivo can be completely
and systematically solved a more direct approach might be useful in the
interim. Determination of the in vivo Ki,
Kiiv, of an inhibitor represents such an approach, at
least for interactions governed by competitive enzyme inhibition
(Kunze and Trager, 1996
).
Theoretically, Ki and Kiiv should
be identical (Kunze and Trager,
1996
). Any difference in their measured values should be a
reflection of differences encountered by the inhibitor in the in vitro and in
vivo environments as discussed above. Of the two constants,
Ki more accurately measures the molecular interaction of
the inhibitor with the enzyme. In contrast Kiiv is a
direct experimental measure of the actual in vivo effectiveness of the
inhibitor. That is, Kiiv unlike Ki
automatically incorporates into its value the effects of factors such as
differences in active site inhibitor concentration, environmental differences,
and/or inhibitor metabolism. Thus, Kiiv should be a
powerful and practical parameter for predicting an interaction providing that
certain underlying assumptions can be confirmed. A major assumption is that
Kiiv, like Ki, is independent of
inhibitor concentration. Although not addressed directly, two recent in vivo
metabolic studies from our laboratory with an inhibitor for two different
P450s (CYP1A2 and CYP2C19) indicate that Kiiv is indeed
independent of inhibitor concentration (Yao et al.,
2001
,
2003
). The present study was
undertaken with yet another inhibitor (fluconazole) and enzyme (CYP2C9) to
further establish the concentration independence of Kiiv
by directly testing this assumption.
| Materials and Methods |
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-(2,4-Dichlorophenyl)-1H-imidazole-1-ethanol was
purchased from Janssen Pharmaceutica (New Brunswick, NJ). Clinical Protocol. Seven, healthy, paid male volunteers of ages 21 to 35 served as study subjects in a protocol of an open label, one-sequence, 4-period crossover design. After being carefully informed of the nature and risk of the study, all the volunteers signed written consent forms in accordance with all conditions required by federal regulations and by the institutional review board of the Santa Clara Valley Medical Center of San Jose, CA. None of the subjects had taken any drug for the preceding two months, and each served as his own control. Complete blood counts and panel-20 blood tests were performed on all subjects before and after all periods.
The study was divided into two phases, warfarin alone, the control phase
(first period), or warfarin combined with fluconazole, the interaction phase
(second, third, and fourth periods). For the control phase, each subject
received a 500-mg capacity gelatin capsule containing pseudoracemic warfarin,
0.75 mg/kg [37.5 mg/kg each of (R)- and (S)-warfarin], mixed
in lactose. The capsule was ingested with a full glass of water 2 h before
breakfast. No additional food or liquid was ingested before breakfast. Blood
samples (12 ml) were obtained by venipuncture just before warfarin ingestion
and at 2, 6, 24, 48, 72, 96, 120, 144, 168, 192, 216, 240 h after ingestion.
Each blood sample was mixed in a glass tube with citrate buffer in a ratio of
9:1. The buffer was prepared by mixing solutions of sodium citrate, 0.1 mol/l,
and citric acid, 0.1 mol/l in a ratio of 3:2. After addition of the citrate,
each blood sample was centrifuged at 2000 rpm for 30 min at 4°C, the
plasma removed and divided into two portions (
3 ml each). Subsequently,
one plasma portion, after addition of the internal standard
pentadeuteriowarfarin (final concentration, 1 µg/ml), was used to determine
(R)- and (S)-warfarin concentration. The second plasma
portion was used for a prothrombin time determination. Both plasma portions
were stored at -20°C until workup for analysis.
After a 4-week wash out and rest period, the second phase was begun.
Fluconazole was administered on three separate occasions in daily doses of 200
(2 tablets, second period followed by a 4-week wash out), 100 (1 tablet, third
period followed by a 4-week wash out), and finally 300 mg (3 tablets, fourth
period). In each period the fluconazole dose was administered before breakfast
beginning 7 days before administration of a single dose of pseudoracemic
warfarin, 0.75 mg/kg [37.5 mg/kg each of (R)- and
(S)-warfarin], and continuing for an additional 11 days. Zero hour
blood samples (12 ml) were obtained by venipuncture just before fluconazole
administration (day 1) and again just before warfarin administration (day 8).
After warfarin administration, serial blood samples (12 ml each) were
collected at 2, 6, 24, 48, 72, 96, 120, 144, 168, 192, 216, 240 h after
ingestion. Each blood sample was mixed with the citrate solution, centrifuged,
and the plasma divided into two portions as described for the control. The
internal standard for the measurement of fluconazole,
-(2,4-dichlorophenyl)-1H-imidazole-1-ethanol (100 µl of a
700 µg/ml solution), was added to 1 ml of plasma from one of the plasma
portions. The internal standard for the measurement of (R)- and
(S)-warfarin levels, pentadeuteriowarfarin, was added to the
remaining plasma (
2 ml) from that plasma portion (final concentration of
1 µg/ml). The three plasma portions from each serial plasma sample were
stored at -20°C until workup for analysis.
Urine was collected throughout the control and fluconazole studies every 24 h and the daily volume noted. For each subject, aliquots (1/100 by volume) were taken from each 24-h urine sample and pooled. Nine milliliters of this pool were spiked with a 1 ml aqueous solution containing deuterated internal standards at final concentrations of 0.1 µg/ml pentadeuteriowarfarin, 1.0 µg/ml each of a mixture of pentadeuteriowarfarin alcohols 1 and 2, and the pentadeuterio-6-, 7-, and 8-hydroxywarfarins. All urine samples were stored at -20°C until workup for analysis.
Prothrombin Time Measurements. The one-stage prothrombin time of
plasma was measured by a modification of the method of Quick, as described
previously (O'Reilly and Aggeler,
1968
). The total anticoagulant effect was determined by measuring
the area under the curve for the response of the prothrombin time
(AUCPT) from a semilogarithmic plot by the trapezoidal method for
the one-stage prothrombin time expressed in arbitrary units.
Assay for Fluconazole, Warfarin Enantiomers, and Metabolites.
Fluconazole plasma concentrations were measured by high performance liquid
chromatography as previously described
(Black et al., 1996
). The
extraction and gas chromatography/mass spectrometry assay methods for the
measurement of warfarin enantiomers and their metabolites in plasma and urine
were as previously described (Toon et al.,
1986
).
Pharmacokinetic Treatment of Data. A single-compartment model
sufficiently described the plasma concentration-time data for (R)-
and (S)-warfarin in all subjects. The elimination rate constants,
k, were obtained by linear regression analysis and AUCinf
by the trapezoid rule. CL for the individual enantiomers of dose, D,
was calculated from CL/F = D/AUC, where F is
bioavailability and is assumed to be unity as reported previously
(O'Reilly et al., 1966
). The
apparent volume of distribution, Vss, and elimination
half-life, t
, were calculated according to
Vss/F = D/k · AUC and
t
; = ln2/k, respectively. The formation clearance,
CLf, for each of the metabolites was calculated according
to CLf = fm · CL, where
fm is the fraction of dose recovered in the urine as a
specific metabolite.
Data Analysis. Comparative data are expressed as mean ± (S.D. or S.E.). Statistical analyses were done using Stata 7.0 (Stata Corporation, College Station, TX). A difference in the mean of prothrombin time or the mean of clearance across the control phase and three different fluconazole dose phases was tested for using repeated measures of analysis of variance and determining the p value for the F-statistic. A difference in the mean of the calculated Kiiv value across three different fluconazole dose phases was also similarly tested for.
| Results |
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Plasma Data. Plasma levels of (R)- and
(S)-warfarin were measured for each of the seven subjects and the
mean pharmacokinetic parameters calculated
(Table 2). For controls the
mean half-life of (S)-warfarin was 33 ± 9 h, whereas that for
(R)-warfarin was 49 ± 11 h. As expected, fluconazole inhibited
the metabolism of both (R)and (S)-warfarin, the effect was
dose-dependent, and the volume of distribution was unchanged
(Black et al., 1996
). On
average the clearance of (S)-warfarin was inhibited by 26, 47, and
49% at the 100, 200, and 300 dose levels of fluconazole, respectively, whereas
the clearance of (R)-warfarin was reduced by 25, 38, and 42% at the
corresponding levels of fluconazole (Table
2).
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Urinary Data. Total urinary levels of parent drug and metabolites
were determined for all patients (0216 h collection period). The mean
recovery of pseudoracemic warfarin and metabolites in urine for controls was
32% for the (S)-enantiomers and 29% for the (R)enantiomers
for a total dose recovery 61% (data not shown). The mean recovery of
pseudoracemic warfarin and metabolites in urine in the fluconazole experiments
was 31, 32, and 29% for the (S)-enantiomers and 27, 27, and 26% for
the (R)-enantiomers. This represented total dose recoveries of 58,
59, and 56% for the 100, 200, and 300 mg of fluconazole doses, respectively
(data not shown). These urinary recoveries fall within the normal limits
defined in previous studies (Toon et al.,
1986
; Heimark et al.,
1992
; O'Reilly et al.,
1992
; Black et al.,
1996
). The mean renal clearances of (S)-warfarin and
(R)warfarin are presented in Table
2. The means of the clearances for each of the enantiomers across
the control phase and the three fluconazole dose phases were significantly
different (p < 0.001). The formation clearances for each of the
coumarin ring hydroxylated metabolites of both (S)- and
(R)-warfarin are given in Table
3.
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(S)-Warfarin. As previously reported the formation
clearances to the minor and the two major (S)-warfarin metabolites
(S)-8-, (S)-6-, and (S)-7-hydroxywarfarin,
respectively, were found to be significantly inhibited by fluconazole
(Black et al., 1996
). On
average, the P450 2C9-dependent 7-hydroxylation of (S)-warfarin was
inhibited by 31, 55, and 77% by daily doses of fluconazole of 100, 200, and
300 mg, respectively (Table 3). Similarly, the 6-hydroxylation of (S)-warfarin was inhibited, on
average, by 45, 49, and 69%, by the same daily doses of fluconazole,
respectively (Table 3).
Fluconazole inhibition of the 8-hydroxylation of (S)-warfarin, while
profound, could not be accurately assessed because of the low level of
turnover to this specific metabolite (Table
3).
(R)-Warfarin. As previously reported
(Black et al., 1996
)
fluconazole was effective in inhibiting the formation of the 6-, 7-, and
8-hydroxylated metabolites of (R)-warfarin at all three doses.
(R)-6-Hydroxywarfarin formation was inhibited by 43, 48, and 65%,
(R)-7-hydroxywarfarin formation was inhibited by 29, 54, and 89%, and
(R)-8-hydroxywarfarin formation was inhibited by 83, 72, and 97%, at
daily doses of 100, 200, and 300 mg of fluconazole, respectively
(Table 3).
Fluconazole Plasma Levels. To insure steady-state fluconazole levels
[t1/2 = 3040 h
(Lazar and Hiligoss, 1990
)],
fluconazole (100, 200, or 300 mg) was administered once a day for 6 days prior
to the administration of a single dose of pseudoracemic warfarin. Mean plasma
levels at the 24-time interval ranged from 8.7 to 22 to 29.5 µM for the
100, 200, and 300 mg dose levels, respectively
(Table 4).
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| Discussion |
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If the plasma concentration of a drug is well below its
Km for the major P450 responsible for its clearance, and
this is generally true for most drugs, the classic equation for competitive
inhibition in Michaelis-Menten enzyme kinetics can be simplified and
rearranged to eq. 1. This equation allows the direct determination of
Kiiv. In the equation, [I] = the plasma
concentration of inhibitor
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A single dose of pseudoracemic warfarin was administered to each subject after fluconazole steady state had been reached (6 days) and serial blood and urine collected over 10 days. Over this time period, anticoagulant activity was monitored by daily prothrombin times determinations. Prothrombin times showed an excellent dose-response relationship with mean AUCPT increasing with increasing fluconazole dose (Table 1).
The pharmacokinetic parameters calculated from the (S)- and
(R)warfarin plasma data were as expected
(Table 2) and consistent with
previous studies (Toon et al.,
1986
; Heimark et al.,
1992
; O'Reilly et al.,
1992
; Black et al.,
1996
). Fluconazole inhibited the metabolism of
(S)warfarin to a greater extent than that of (R)-warfarin.
The extent of inhibition of both warfarin enantiomers was fluconazole
dose-dependent whereas the volume of distribution was unchanged
(Table 2). Recovery of the
warfarin enantiomers and their metabolites from urine after approximately 10
days was about 60% of the administered dose, a value that was consistent with
previous studies (Toon et al.,
1986
; Heimark et al.,
1992
; O'Reilly et al.,
1992
; Black et al.,
1996
). The formation clearances to each of the coumarin ring
hydroxylated metabolites of both (S)- and (R)-warfarin in
the presence and absence of fluconazole are presented in
Table 3. As previously
reported, fluconazole is effective in inhibiting the formation of each of the
coumarin ring hydroxylated warfarin metabolites but to varying degrees
(Black et al., 1996
).
Of the various warfarin metabolites that are formed,
(R)-10-hydroxywarfarin, (R)-8-hydroxywarfarin, and
(S)-6- and 7-hydroxywarfarin are known reporters of P450 3A4
(Kunze et al., 1996
), P450
2C19 (Weinkers et al., 1996
),
and P450 2C9 (Rettie et al.,
1992
), respectively. Unfortunately, unanticipated analytical
problems precluded accurate measurement of (R)-10-hydroxywarfarin
levels and its inclusion in the present studies. Levels of
(R)-8-hydroxywarfarin and (S)-6- and 7-hydroxywarfarin were
measurable and are reported in the form of formation clearances in
Table 3. Inspection of the
formation clearance values for (R)-8-hydroxywarfarin in the presence
of various concentrations of fluconazole
(Table 3) reveals that the
maximum level of inhibition is attained at even the lowest dose of inhibitor.
It is known that both P450 2C19 (low Km form) and P450 1A2
(high Km form) catalyze the formation of
(R)-8-hydroxywarfarin but that only P450 2C19 is susceptible to
inhibition by fluconazole (Ki 2 µM)
(Kunze et al., 1996
;
Weinkers et al., 1996
). This
suggests that the steady-state fluconazole plasma level of 8.7 µM
(Table 4) obtained from the 100
mg daily dose is sufficient to eliminate most of the contribution of P450 2C19
to the formation of (R)-8-hydroxywarfarin. The
(R)-8-hydroxywarfarin that is formed is formed by P450 1A2. The
magnitude of the degree of inhibition at the fluconazole dose levels studied
coupled to the involvement of at least two P450s precludes
(R)-8-hydroxywarfarin formation being a useful parameter for testing
the assumption that Kiiv is independent of inhibitor
concentration. Moreover, these facts do not allow for any useful estimate of
Kiiv for P450 2C19.
Similar to (R)-8-hydroxywarfarin, the formation of
(S)-6-hydroxywarfarin would not be a good test of the assumption. Its
formation is also dependent upon a minimum of two P450s, P450 2C9 (a low
Km form) and P450 3A4 (a high Km form)
(Rettie et al., 1992
;
Kunze et al., 1996
).
Conversely, the formation of (S)-7-hydroxywarfarin is dependent upon
the activity of a single enzyme, P450 2C9
(Rettie et al., 1992
;
Kunze et al., 1996
).
Inhibition of the formation of (S)-7-hydroxywarfarin by different
steady state levels of fluconazole presents a clear test of the assumption
that Kiiv is independent of inhibitor concentration. At
the 100, 200, and 300 mg daily doses of fluconazole, the formation of
(S)-7-hydroxywarfarin was inhibited by 31, 55, and 77%, respectively
(Table 3).
After steady state had been reached, trough levels of fluconazole plasma
concentrations were determined for the remainder of the study at 24-h
intervals immediately preceding the next fluconazole dose at each of the dose
levels (Table 4). Although a
24-h sampling does not provide the mean fluconazole concentration over the
dosing interval, it does provide a consistent steady-state concentration of
fluconazole that can be conveniently sampled throughout the course of the
study without jeopardizing the question of whether or not
Kiiv remains
constant.3
Kiiv was then calculated for each of the fluconazole doses
using eq. 1, the mean steady-state 24-h fluconazole plasma concentrations and
the (S)-7-hydroxywarfarin formation clearance values from
Table 4. The results are
presented in Table 4. The
values of Kiiv at the three fluconazole dosage levels of
100, 200, and 300 mg were found to be 30.7 ± 23.7, 19.6 ± 3.8,
and 17.9 ± 7.5 µM, respectively. In addition, the
Kiiv value for a 400-mg dose of fluconazole calculated
from the 24-h fluconazole concentration, and (S)-hydroxywarfarin
clearance data determined in the earlier study
(Black et al., 1996
) was found
to be 19.8 ± 3.5. Except for the 100-mg dose experiment, the agreement
between the Kiiv values for the various fluconazole-dosing
levels was excellent. The reason for the greater diversity in individual
Kiiv values for the 100-mg dose experiment is unknown but
is presumably due to an unrecognized source of experimental error. Despite the
unexplainably erratic estimate of Kiiv from the 100-mg
dose experiment, the evidence overall confirms the hypothesis that
Kiiv is independent of inhibitor concentration. This
conclusion is based on 1) the excellent agreement between
Kiiv values at the 200-, 300-, and 400-mg dose levels, 2)
the mean Kiiv value for the 100-mg dose experiment is not
significantly different from the Kiiv values for the other
three doses, 3) the slope of a plot of all individual
CLf(c)/CLf(i) ratio values versus fluconazole dose for
the four dose levels gives a composite Kiiv value of 20.4
µM, Fig. 1, and 4) the
confirmatory results of the two earlier studies (Yao et al.,
2001
,
2003
). Thus, the independence
of Kiiv from inhibitor concentration as well as substrate
identity as previously determined (Kunze
and Trager, 1996
) provides strong support for the notion that
Kiiv can be expected to be a powerful tool for predicting
and assessing the magnitude of drug interactions involving competitive enzyme
inhibition.
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| Footnotes |
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1 Abbreviations used are: P450, cytochrome P450; Kiiv, in
vivo constant for competitive inhibition of an enzyme; Ki,
in vitro constant for competitive inhibition of an enzyme; AUC, area under the
curve; PT, the response of the prothrombin time; CL, clearance limits;
F, bioavailability; Vss, apparent volume of
distribution. ![]()
2 The classic expression for competitive enzyme inhibition is
![]() | (1) |
3 The difference between the mean fluconazole concentration over 24 h and the
24-h fluconazole concentration, ranges between 10 and 20% with the mean value
being higher (Kunze and Trager,
1996
). Thus, use of the 24-h value in eq. 2 would be expected to
lead to a slightly lower value for Kiiv than would be
obtained using the mean value. This is exactly what is found. Using the data
from the earlier paper by Kunze and Trager
(1996
), the mean fluconazole
concentrations over 24 h yielded a Kiiv of 22.5 ±
3.5 µM whereas the fluconazole concentrations from the same study at 24-h
postdose yielded a Kiiv of 19.8 ± 3.5 µM. ![]()
Address correspondence to: Dr. William F. Trager, Box 357610, Department of Medicinal Chemistry, University of Washington, Seattle, WA 98195. E-mail: trager{at}u.washington.edu
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