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Antimicrobial Agents and Chemotherapy, June 2004, p. 2061-2068, Vol. 48, No. 6
0066-4804/04/$08.00+0 DOI: 10.1128/AAC.48.6.2061-2068.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
Novel Pharmacokinetic-Pharmacodynamic Model for Prediction of Outcomes with an Extended-Release Formulation of Ciprofloxacin
Alison K. Meagher,1* Alan Forrest,1,2 Axel Dalhoff,3 Heino Stass,3 and Jerome J. Schentag1,2
CPL
Associates, L.L.C.,
Amherst,1
The School of Pharmacy, State
University of New York at Buffalo, Buffalo, New
York,2
Bayer
Healthcare, Wuppertal,
Germany3
Received 21 July 2003/
Returned for modification 9 December 2003/
Accepted 10 February 2004
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ABSTRACT
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The
pharmacokinetics of an extended-release (XR) formulation of
ciprofloxacin has been compared to that of the immediate-release (IR)
product in healthy volunteers. The only significant difference in
pharmacokinetic parameters between the two formulations was seen in the
rate constant of absorption, which was approximately 50% greater
with the IR formulation. The geometric mean plasma ciprofloxacin
concentrations were applied to an in vitro
pharmacokinetic-pharmacodynamic model exposing three different clinical
strains of Escherichia coli (MICs, 0.03, 0.5, and 2.0
mg/liter) to 24 h of simulated concentrations in plasma. A
novel mathematical model was derived to describe the time course of
bacterial CFU, including capacity-limited replication and first-order
rate of bacterial clearance, and to model the effects of ciprofloxacin
concentrations on these processes. A "mixture model"
was employed which allowed as many as three bacterial subpopulations to
describe the total bacterial load at any moment. Comparing the two
formulations at equivalent daily doses, the rates and extents of
bacterial killing were similar with the IR and XR formulations at MICs
of 0.03 and 2.0 mg/liter. At an MIC of 0.5 mg/liter, however, the
1,000-mg/day XR formulation showed a moderate advantage in
antibacterial effect: the area under the CFU-time curve was 45%
higher for the IR regimen; the nadir log CFU and 24-h log CFU values
for the IR regimen were 3.75 and 2.49, respectively; and those for XR
were 4.54 and 3.13, respectively. The mathematical model explained the
differences in bacterial killing rate for two regimens with identical
AUC/MIC
ratios.
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INTRODUCTION
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Ciprofloxacin (Cipro), the first broad-spectrum oral fluoroquinolone,
was approved by the Food and Drug Administration in 1987. An
intravenous formulation was approved in 1991, and an oral suspension
formulation followed in 1997. Recently, an extended-release (XR)
formulation of ciprofloxacin has been developed by Bayer Healthcare
(Cipro XR). Pharmacokinetic studies of XR ciprofloxacin in healthy
volunteers have demonstrated a significant difference in peak
concentrations in plasma between the XR and immediate-release (IR)
formulations: peak concentrations were 40 to 50% higher with the
XR formulation, while areas under the concentration-time curve (AUCs)
were comparable to those observed with the IR formulation (H. Stass, J.
Nagelschmitz, E. Brandel, et al., Abstr. Am. Fed. Med. Res. Cong.,
abstr. 24 and 25, 2002).
The objectives of this analysis were
threefold. The first objective was to characterize the pharmacokinetics
of multiple oral doses of ciprofloxacin when given as an IR and an XR
formulation in daily doses of either 500 mg or 1,000 mg in healthy male
volunteers. The second objective was to apply the geometric mean plasma
concentration profiles from the healthy-volunteer study to an in vitro
pharmacokinetic-pharmacodynamic (PK-PD) model exposing three different
clinical strains of Escherichia coli to 24 h of
simulated concentrations in plasma. Finally, the third objective was to
develop a mathematical model to describe bacterial replication and the
intrinsic rate of bacterial clearance and to model the effects of
ciprofloxacin concentrations on these
processes.
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MATERIALS AND METHODS
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PK study design.
Two randomized, single-center,
two-way-crossover, multiple-dose studies were conducted by Bayer
Healthcare in which ciprofloxacin was given to Caucasian male
volunteers. Both of the two studies evaluated a total of 19 healthy
volunteers. In a randomized sequence, volunteers received either 250 mg
of IR ciprofloxacin twice daily and 500 mg of XR ciprofloxacin once
daily or 500 mg of IR ciprofloxacin twice daily and 1,000 mg of XR
ciprofloxacin once daily. All doses were given for five consecutive
study days under fasting conditions. Urine and plasma samples were
taken on the first and on the last day of treatment. Twenty-nine plasma
samples were collected: 14 samples on day 1 and 15 samples on day 5 of
the study (predose and at 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 6, 8, 12, 16,
24, 96, 96.5, 97, 97.5, 98, 98.5, 99, 99.5, 100, 102, 104, 108, 112,
120, and 124 h post-first dose). Urine was collected over two
24-h periods, with four collection periods during day 1 (0 to 4, 4 to
8, 8 to 12, and 12 to 24 h postdose) and five collection
periods during day 5 of treatment (96 to 100, 100 to 104, 104 to 108,
108 to 120, and 120 to 124 h postdose). Heparinized plasma
and urine were stored in plastic vials at 18°C until
analysis. Analysis of specimens was performed using validated
high-performance liquid chromatography procedures with fluorescence
detection (lower limit of quantitation, 10 mg/liter; interday
coefficient of variation, <9%)
(3).Ofloxacin was used as the internal standard. Quality control samples
produced out of blank matrix spiked with a known concentration of the
analyte were assessed together with the study samples to control
validity of the data. The interday precision and accuracy for the
high-performance liquid chromatography assay were 2.4 and 2.1%,
respectively, as determined from the quality control
samples.
In vitro PD study.
An in vitro PK-PD model was conducted
by Bayer Healthcare using three different clinical strains of E.
coli for which the MICs were 0.03, 0.5, and 2.0
mg/liter. MICs were determined according to NCCLS broth
microdilution methods at an inoculum of 105 CFU/ml. None of
the isolates were extended-spectrum ß-lactamase producers, as
they were susceptible to the cephalosporins. Bacterial inocula were
exposed to ciprofloxacin (Bayer Healthcare, Wuppertal, Germany) in
concentrations similar to those achieved in the central compartment in
the human body. Mathematical corrections for dilution were not made
based on our previous work showing that demonstrated dilution did not
impact antibacterial effect (A. Dalhoff, A. MacGowan, O. Carrs, et al.,
Abstr. 43rd Intersci. Conf. Antimicrob. Agents Chemother., abstr.
A-1147, 2003). The geometric mean concentrations in plasma from the
first 24 h of the four-dosage regimens in the
healthy-volunteer trial (ciprofloxacin, 250 mg IR twice daily, 500 mg
XR once daily, 500 mg IR twice daily, and 1,000 mg XR once daily) were
simulated in the in vitro model. The highest MIC, 2.0 mg/liter, was
only tested against the two higher-dosage regimens (ciprofloxacin total
daily dose of 1,000 mg).
For the experimental evaluation of the
PK-PD relationship of ciprofloxacin against E. coli, a
slightly modified in vitro method, that of Grasso et al.
(9), was used. The
experimental setting consisted of a central compartment without a
separating membrane (calibrated Erlenmeyer flasks with a total volume
of 300 ml and containing 100 ml of medium) into which the antibiotic is
pumped via programmable pumps until the maximum serum concentration to
be simulated is reached. Thereafter, antibiotic-free medium is pumped
into the central compartment and is continuously eliminated in parallel
to mimic half-life values. The variability between the resulting in
vitro profiles compared to the desired human target profiles were
extremely low, <4% deviation at any given time. Flasks
were maintained at 37°C and agitated on a rotary shaker.
Control growth in the absence of antibiotic was studied in the same
model.
E. coli was grown in brain heart infusion broth
(Oxoid, Wesel, Germany). The initial inoculum into the model for the
ciprofloxacin 500-mg total daily dose regimens was 108.2
CFU, and the inoculum for the ciprofloxacin 1,000 mg total daily dose
regimens was 107.58 CFU. Viable bacterial
counts (CFU) were determined on agar plates containing charcoal, which
completely adsorbs fluoroquinolones. The lower limit of detectability
was 100 CFU/ml. CFU counts were obtained at 16 time points: 0, 1, 2, 3,
4, 5, 6, 7, 8, 10, 12, 14, 18, 20, 22, and 24 h. At the same
time points as those for quantification of CFU, the antibiotic
concentrations were measured by a conventional cup-agar diffusion test
with Bacillus subtilis spore suspension as the indicator
organism (14).
Postexposure MIC testing was performed, and changes in MICs were not
observed.
PK and PD modeling methods.
The
concentrations of ciprofloxacin in plasma and urine and the
log10-transformed counts of CFU were characterized by
fitting candidate PK-PD models to the data, using a maximum a
posteriori-Bayesian parameter value estimator available in Adapt II
(User's guide for release 4, Biomedical Simulations Resource,
University of Southern California, Los Angeles). A PK-PD model was
derived by fitting smooth curves through the experimental data,
resulting in the computation of model parameter values which summarize
and characterize the observed data and which are more amenable to
hypothesis testing. Two PK-PD models were explored: one in which drug
effect was hypothesized to inhibit bacterial replication (A. Meagher,
A. Forrest, A. Dalhoff, et al. Abstr. 42nd Intersci. Conf. Antimicrob.
Agents Chemother., abstr. A-1257, 2002) and one in which drug effect
enhanced the rate of bacterial killing. Model discrimination was
accomplished using the rule of parsimony
(10) and Akaike's
information criterion
(1).
Experimental measures that were BLQ.
A
number of drug plasma samples or counts of number of CFU, for which the
signal (e.g., peak area)-to-noise (random assay error) ratio was low,
were judged to be below the limit of quantitation (BLQ). These plasma
concentration values or CFU counts were originally reported as
<0.01 mg/liter or <100 CFU/ml, respectively. The true
values for these samples were actually somewhere between zero and the
lower limit of quantitation of the assay. It is inappropriate to assign
these samples a value of zero, which is biased low, and it is also
suboptimal to discard these data as they contain usable information.
Our approach for concentrations in plasma was to use 0.0 mg/liter for
predose samples. Postdose plasma samples that were BLQ were entered as
either 0.0 or 0.005 mg/liter (the midpoint between 0.0 and 0.01
mg/liter), whichever was closer to the values predicted by
extrapolation of the other detectable terminal concentrations in
plasma. CFU counts that were below 100 were entered as
missing.
Procedures for declaring outliers.
Individual plasma
or urine drug concentrations, suspected to be outliers, were tested as
follows. The data set was fit with and without the suspect value. If
the residual of the observation (the difference between fitted and
observed values) was at least 3 standard deviations (SDs) of the
measurement, and if the trajectory of the fitted line changed when the
value was removed, the point was declared an outlier. No CFU values
were excluded as outliers.
Residual ("error") variance models.
The empirical variance model assumed
that the random errors in measurements of concentrations of
ciprofloxacin in plasma and urine were similar for all of the subjects
in the study and that the residual (error) SDs of the observations
(
) were linearly related to the true values (Y):
= SDslope Y +
SDintercept, in which SDslope and
SDintercept are the variance parameters.
SDintercept is the asymptotic minimum
(the value
as Y approaches zero) and is mainly a measure of sensitivity,
and the SDslope is the asymptotic minimum coefficient of
variation (the value as Y approaches infinity) and is mainly a
measure of precision. In cases where the intercept approaches zero,
this relationship collapses to a constant coefficient of variance (CV)
model (with SDslope equaling the CV). Even with a nonzero
intercept, at values of Y much greater than the
SDintercept, the SDslope approximates the CV. In
cases where SDslope approaches zero, the relationship
collapses to a homoscedastic variance model (with
SDintercept equaling the observation SD). The initial
empirical estimates for the variance parameters were based on the assay
performance. Later in the process, the values for the variance
parameters were fitted (determined from the data). The choice was made
to model the CFU counts as base 10 log values. This transforms weights
data like assuming a constant CV does and no further weighting was
used.
SHAM analysis.
A number of data sets were not
amenable to mathematical modeling. This was caused by apparent
multiphasic absorption. These data were analyzed using slope, height,
area, and moment (SHAM) analysis, which is sometimes referred to as
noncompartmental analysis
(4,
7,
10). The AUC from time
zero to 24 h (AUC0
24) for plasma
concentration data was determined using the linear-trapezoidal rule.
The terminal rate constant of elimination (ß) was determined by
linear least-squares regression of the last three detectable
concentrations in plasma. The AUC from 24 h to infinity
(AUC24
) was computed as
C24/ß, where C24 is the
drug concentration in plasma at 24 h. The
AUC0
was computed as the sum of
AUC0
24 and AUC24
. The
percentage of the AUC0
that was
extrapolated was computed as 100 times
AUC24
divided by
AUC0
. Oral plasma clearance
(CLT/F) was computed as
dose/AUC0
. Renal clearance
(CLR) was computed as amount of drug (in milligrams)
excreted in 24 h divided by
AUC0
24.
Summary statistics, including mean,
median, SD, and CV, were determined using Systat computer software
(16).
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RESULTS
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PK study subjects and in vitro PD model.
Data for concentrations in plasma and
urine were obtained from PK studies of healthy volunteers comparing
ciprofloxacin in 500-mg once-daily XR and 1,000-mg once-daily XR
formulations with two corresponding twice-daily IR formulation regimens
(H. Stass, J. Nagelschmitz, E. Brandel, et al., Abstr. Am. Fed. Med.
Res. Cong., abstr. 24, 2002; H. Stass, J. Nagelschmitz, E. Brandel, et
al., Abstr. Am. Fed. Med. Res. Cong., abstr. 25, 2002). Volunteer
demographics are shown in Table
1. No significant differences were noted between the two groups. Serial
determinations of CFU counts of three strains of E. coli
following exposure to the geometric mean plasma ciprofloxacin
concentrations to the four dosage regimen profiles were obtained. These
data were used to determine the PK-PD relationship between
concentrations of ciprofloxacin in plasma and net bacterial growth and
eradication.
Final PK structural model.
A
two-compartment PK model was employed for this analysis,
and the model fit the data very well (median r2
= 0.996). In this model, drug is administered into an
absorptive compartment with the amount of drug available systemically
dependent on F, the oral bioavailability of the drug. After a
lag time (TLag), ciprofloxacin is absorbed per
first-order rate constant (ka) into the central
compartment (of apparent volume, V1). Drug in the
central compartment equilibrates via a distributional clearance
(CLd) with drug in the peripheral compartment (of apparent
volume, Vp), and is eliminated from the central
compartment by both renal and nonrenal clearance (CLR and
CLNR, respectively). Because ciprofloxacin was administered
as an oral formulation, the fitted volumes and clearances are
conditioned on F, which could not be estimated in a study of
this design. Other PK parameter values were derived from the fitted
parameters. For example, the oral volume of distribution at steady
state, VSS/F =
V1/F+Vp/F,
was calculated.
Fitted PK parameter values.
Studied doses within
subject-regimen were often unable to be comodeled due to apparent
within-subject interoccasion variability. For this reason, each dosing
event on days 1 and 5 of the healthy-volunteer study for each of the
four dosing regimens was modeled as a separate data set, and each
subject had two or four data sets, depending upon dosage regimen.
Therefore, a total of 218 data sets were created and modeled. Data were
not available for two subjects in the XR-ciprofloxacin 500-mg group and
for one subject in the IR-ciprofloxacin 500-mg group. For two separate
volunteers, one of the four data sets was considered an outlier and was
censored. In these cases plasma drug concentrations were suspiciously
low and it appeared as though study drug was not administered. Ten
(10) of the 218 subject
data sets (two in the 250-mg IR-ciprofloxacin twice-daily group, one in
the 500-mg XR-ciprofloxacin once-daily group, four in the 500-mg
IR-ciprofloxacin twice-daily group, and three in the 1,000-mg
XR-ciprofloxacin once-daily group) could not be fitted adequately by
the PK model due to apparent multiphasic absorption. For these cases,
SHAM analysis was used to calculate the total and renal clearance of
ciprofloxacin. Table
2 summarizes the fitted PK parameter values. Although there appears to be
an inverse relationship in values of V1 and
Vp between the IR and XR formulations, this
difference is most likely to be a modeling artifact. Supportive
evidence is the opposing trend in CLd between formulations
and the relative constancy of VSS across all four
regimens. Even if these differences were real, they would be of no
clinical significance. The CLR and total clearances and
TLag values do not differ between dosage regimens. However,
as expected, the ka is approximately 50%
greater in the IR than in the XR formulation. Figure
1 depicts the PK profiles for the four ciprofloxacin dosage
regimens.

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FIG. 1. Ciprofloxacin
PK profiles for four different dosage regimens. The solid symbols
represent the geometric mean concentrations in plasma surrounded by a
±1 SD envelope (dashed lines). The solid line represents the
empirical connection from point to
point.
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Final PD model.
The PD model derived
for this analysis is depicted in Fig.
2. The model fit the data very well (see r2 values in
Table
3). The total concentration of bacteria in the body was the net result of a
saturable capacity-limited mechanism for bacterial replication and a
first-order process characterizing the rate of death in a drug-free
environment (natural death). The modeled drug effect was to increase
the rate constant for bacterial death (Kd)
according to a Hill-type model. The other model considered, which
assumed drug effect to decrease the rate of replication, yielded
similar goodness of fit but was inferior by Akaike's information
criterion and generated greater variability in final PD parameter
values within strains of bacteria and across dosing regimens. Results
from this model are not reported here.

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FIG. 2. Final
PD model, where the bacterial load is represented as a pool within the
body in which replication is saturable and driven by the concentration
of viable bacteria in the pool. Clearance from the body is by a
first-order process where the drug effect is to enhance the natural
death
rate.
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TABLE 3. Fitted
PD parameters for four ciprofloxacin dosage regimens against E.
coli strains for which the MICs differ
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The mathematical model for
a bacterial inoculum of homogenous sensitivity is shown
below.
This
differential equation describes the time course of the total bacterial
load (CFU in CFU per milliliter). The rate of replication is
parameterized by the maximal velocity of bacterial growth
(VGmax) (CFU per milliliter per hour) and the median effect
CFU (CFUm) (in CFU per milliliter). The CFUm is
the CFU at which the rate of replication is half maximal. The rate
of bacterial death due to natural elimination processes
(i.e., non-drug-related elimination) is characterized by
Kd (where units are hour1), the
first-order bacterial elimination rate constant. In any instant in
time, these rates are driven by the current total bacterial load. The
effect of ciprofloxacin, which is to increase Kd by
a Hill-type function, is contained within the parenthetical phrase. The
time course of concentrations of drug (C) (in milligrams per
liter), scaled to the nominal MIC, is the forcing function for drug
effect. Under certain assumptions, C/MIC is a reasonable
estimate of the inverse serum inhibitory titer (SIT). The
SITm is the median effect value for C/MIC, the
value at which the drug effect is half maximal.
Emax is the maximal fractional increase in
Kd (i.e., if Emax is 0.3,
Kd is increased by 30%). Hill's
constant (H) affects the shape of the curve. As H increases, the slope
of the PD function also increases.
Neither this equation nor any
other considered that assumed a homogenous drug sensitivity
throughout the inoculum was able to fit the experimental data.
Therefore, we employed a "mixture model" in which the
total bacterial load at any moment is characterized as a mixture of as
many as three bacterial subpopulations. These populations were allowed
to differ only in their initial concentrations (CFU at time zero in the
experiment) and in their susceptibility to drug (SITm, the
value of C/MIC at which the replication rate is reduced by
half). Thus, the final model included three values for
SITm: SITms is for the most sensitive
subpopulation, SITmi is for the intermediately sensitive
subpopulation, and SITmr is for the relatively resistant
subpopulation. These SITm values are approximately equal to
the MIC for the subpopulation divided by the nominal MIC of the initial
inoculum.
Fitted PD parameter values.
The final fitted PD
parameter values are summarized in Table
3. IC4 and IC5 are the
fitted baseline initial conditions (in CFU per milliliter) for the
sensitive and intermediate subpopulations, respectively. Ten
experiments were performed: the three bacterial strains were exposed to
the geometric mean plasma concentration profiles for each of the four
dosage regimens, except for the E. coli for which the MIC was
highest, 2.0 mg/liter, which was exposed only to the 1,000-mg total
daily dose regimens. None of the experiments required three bacterial
subpopulations to fully describe the PD profile of ciprofloxacin. Two
bacterial subpopulations were required to describe the dynamics for all
the regimens against the E. coli strain for which the MIC was
0.5 mg/liter, and one bacterial population was adequate for all other
regimens at all tested MICs.
The PD profiles for the four
ciprofloxacin dosage regimens versus E. coli at three
different ciprofloxacin MICs (0.03, 0.5, and 2.0 mg/liter) are shown in
Fig.
3 through 5. As can be seen
graphically, the model fit the data extremely well. In general,
comparing the two formulations at equivalent daily doses, the
once-daily XR formulation provided a net bacterial kill that was at
least as rapid and extensive. At the lowest MIC, 0.03 mg/liter (Fig.
3), near-maximal activity was exhibited with all four dosage regimens
against E. coli. Bacterial CFU were at or below the limit of
detection (100 CFU/ml) at approximately 5 h with all studied
regimens. At the next highest MIC of 0.5 mg/liter (Fig.
4), for the two regimens
with 500 mg/day, the shape of the curves were different but the overall
effects were similar. For the two regimens with the total daily dose of
1,000 mg, however, the XR formulation showed a moderate
advantage in antibacterial effect. For these two regimens, the area under the
CFU-time curve was 45% higher for the IR regimen; the nadir log
CFU values, for IR versus XR formulations, respectively, were 3.75 and
2.49; and the 24-h log CFU values were 4.54 and 3.13, respectively. If
the experiment is extended to 48 h through simulation, only
the regimen with 1,000 mg of XR ciprofloxacin once-daily would be
predicted to drive the CFU to nondetectable concentrations. Neither the
IR nor XR formulation at the highest daily dose, 1,000 mg of
ciprofloxacin, was able to achieve more than a 1-log kill during the
24-h experiment with the E. coli strain for which the MIC was
2.0 mg/liter (Fig.
5).

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FIG. 3. PD
profiles with E. coli for which the MIC was 0.03 mg/liter. The
symbols represent the observations, and the solid lines depict the
fitted function for each of the four dosage regimens (median
r2 =
0.985).
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FIG. 5. PD
profiles with E. coli for which the MIC was 2.0 mg/liter. The
symbols represent the observations, and the solid lines depict the
fitted function for each of the four dosage regimens (median
r2 =
0.763).
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DISCUSSION
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This
data analysis represents our first publication using a new model we
have developed for PK and PD of bacteria in vitro and in animal models
and should prove useful for modeling human trials. The main
characteristic of this approach is describing the initial inoculum of
bacteria as a mixture of subpopulations, each with different
susceptibilities to a drug. Bacterial replication is modeled as a
capacity-limited, saturable process, and rate of clearance of bacteria
from the system is modeled as a first-order process. Drug effects can
be hypothesized to either inhibit replication or enhance the rate of
kill. One major difficulty with these models is their complexity and
that no single experiment within a group of experiments is informative
about all the parameters in the model. One of our observations is that
a large range of drug exposures, including a drug-free control and a
large dose that will elicit near-maximal effect, must be considered,
and all the experiments with a given bacterial strain should be
comodeled and analyzed simultaneously. This is an exceedingly difficult
analysis to perform, and we are currently exploring two general
approaches to accomplish this task. The first approach is to treat each
separate experiment as if it were observed in a separate
"subject" and fit the sample of subjects using a
population PK-PD tool, such as iterative two-stage analysis, IT2S
(15). The other approach
could be thought of as a pooled approach in which all of the
experiments using a given strain are comodeled as if they had been
studied in the same subject multiple times.
These guidelines
would have been beneficial in this study in two cases in particular.
The first is the experiment performed with the bacterial strain for
which the MIC was 0.03 mg/liter. All the drug concentrations for all
four tested regimens were far enough above the MIC throughout the study
period that the SITms was poorly estimated. The median value
of 0.04 mg/liter should simply be taken to be a low value, as there is
no way to determine the value satisfactorily from this experiment. The
other case is the experiment with the bacterial strain for which the
MIC was 2.0 mg/liter. Drug concentrations for the two tested regimens
were never high enough above the nominal MIC to allow a precise
estimation of Emax, and the fitted value of 43
(i.e., a maximal Kd value that is 44-fold higher
than the initial Kd) should again be considered
with caution.
Fluoroquinolones are considered to
work primarily in a concentration-dependent manner
(2,
5,
11,
13). Both AUC/MIC ratios
and peak/MIC ratios have been used to describe fluoroquinolone PDs in
human and animal models
(8,
12). Optimizing these
ratios and providing more-rapid bacterial eradication has the potential
to improve outcomes as well as prevent the emergence of resistance.
There are no clinically significant differences in either PK parameters
or AUC between the XR and IR ciprofloxacin formulations (H. Stass et
al., Abstr. Am. Fed. Med. Res. Cong., abstr. 24 and 25). As expected,
the rate constant of absorption was found to be lower with the XR
formulation. What may be clinically significant, however, are the peak
concentrations achieved with the newly developed XR formulations.
Overall, peak ciprofloxacin concentrations in plasma are approximately
40% higher with the 500-mg once-daily XR formulation and
approximately 50% higher with the 1,000-mg once-daily XR
formulation than with IR regimens with the same total daily dose given
in two separate doses (H. Stass et al., Abstr. Am. Fed. Med. Res.
Cong., abstr. 24 and 25). Despite comparable AUC values when the total
daily doses are the same, the XR once-daily formulation was generally
associated with greater in vitro bacterial killing in this
model.
At this time, Cipro XR is approved by the U.S. Food and
Drug Administration only for use in urinary tract infections. The
concentration of ciprofloxacin achieved in urine is much higher than
that in plasma. The present study exposed inocula of
bacteria to exposure profiles consistent with concentrations in plasma.
We would expect this model to be reasonably predictive of outcomes for
infection sites that achieve similar concentrations to that seen in
plasma. This probably would include complicated urinary tract
infections, where there is a significant tissue component to the
infection. If you envision a simple urinary tract infection as being an
infection of bacteria in urine only, then all of the regimens
considered in this analysis would be predicted to provide maximum rates
of kill and rapid eradication of susceptible bacteria in
urine.
This model predicts more rapid bacterial killing for the
once-daily XR formulation than for the IR product given in two divided
doses despite similar AUC values. The two main hypotheses for these
findings cannot be discriminated by this study data. One of these
hypotheses is that the once-daily XR formulation yields a higher AUC
during a portion of the 24-h dosing period and would have increased
activity against resistant subpopulations. The second mechanism would
be a relationship between rate of kill and peak drug concentration. We
believe the first of these hypotheses to be more likely. That is, the
once-daily XR formulation, compared to the equivalent twice-daily
regimen, provided maximal AUC values during the period when the CFU
counts were highest. The mathematical model suggests higher AUCs early
in the dosing interval results in greater bacterial killing of both the
sensitive and the more resistant bacterial
subpopulations.

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|
FIG. 4. PD
profiles with E. coli for which the MIC was 0.5 mg/liter. The
symbols represent the observations, and the solid lines depict the
fitted function for each of the four dosage regimens (median
r2 =
0.946).
|
|
 |
FOOTNOTES
|
|---|
* Corresponding
author. Mailing address: Division of Infectious Diseases, Cognigen
Corporation, 395 Youngs Rd., Buffalo, NY 14221. Phone: (716) 633-3463.
Fax: (716) 633-7404. E-mail:
alison.meagher{at}cognigencorp.com. 
 |
REFERENCES
|
|---|
- Akaike,
H. 1979. A Bayesian extension of the minimum AIC
procedure of autoregressive model fitting. Biometrika
66:237-242.[Abstract/Free Full Text]
- Andes,
D., and W. A. Craig. 2002. Animal model
pharmacokinetics and pharmacodynamics: a critical review. Int.
J. Antimicrob. Agents
19:261-268.[CrossRef][Medline]
- Bannefeld,
K. H., H. Stass, and G. Blaschke. 1997.
Capillary electrophoresis with laser-induced fluorescence detection, an
adequate alternative to high-performance liquid chromatography, for the
determination of ciprofloxacin and its metabolite
desethyleneciprofloxacin in human plasma. J.
Chromatogr. B
692:453-459.[CrossRef]
- Caprani,
O., E. Sveinsdottir, and N. Lassen. 1975. SHAM, a
method for biexponential curve resolution using initial slope, height,
area and moment of the experimental decay type curve. J. Theor.
Biol.
52:299-315.[CrossRef][Medline]
- Craig,
W. 1993. Pharmacodynamics of antimicrobial agents as a
basis for determining dosage regimens. Eur. J. Clin.
Microbiol. Infect. Dis. 12(Suppl.
1):S6-S8.
- D'Argenio,
D. Z., and A. Schumitzky. 1979. A program
package for simulation and parameter estimation in pharmacokinetic
systems. Comput. Programs Biomed.
9:115-134.[CrossRef][Medline]
- DiStefano,
J. J., III. 1982. Noncompartmental vs.
compartmental analysis: some basis for choice. Am. J.
Physiol
243:R1-R6.
- Forrest,
A., D. E. Nix, C. H. Ballow, T. F. Goss,
M. C. Birmingham, and J. J. Schentag.1993
. Pharmacodynamics of intravenous ciprofloxacin in
seriously ill patients. Antimicrob. Agents Chemother.
37:1073-1081.[Abstract/Free Full Text]
- Grasso,
S., G. Meinardi, I. de Carneri, and V. Tamassia. 1978.
New in vitro model to study the effect of antibiotic concentration and
rate of elimination on antibacterial activity. Antimicrob.
Agents Chemother.
13:570-576.[Abstract/Free Full Text]
- Jusko,
W. J. 1992. Guidelines for collection and
analysis of pharmacokinetic data, p.1
-43. In W. E.
Evans, J. J. Schentag, and W. J. Jusko (ed.),
Applied pharmacokinetics: principles of therapeutic drug monitoring,
3rd ed. Applied Therapeutics, Inc., Vancouver,
Canada.
- MacGowan,
A., C. Rogers, and K. Bowker. 2000. The use of in
vitro pharmacodynamic models of infection to optimize fluoroquinolone
dosing regimens. J. Antimicrob. Chemother.
46:163-170.[Free Full Text]
- Preston,
S. L., G. L. Drusano, A. L. Berman,
C. L. Fowler, A. T. Chow, B. Dornseif, V. Reichl,
J. Natarajan, and M. Corrado. 1998. Pharmacodynamics
of levofloxacin: a new paradigm for early clinical trials.JAMA
279:125-129.[Abstract/Free Full Text]
- Roosendaal,
R., I. A. Bakker-Woudenberg, M. van den Berghe-van Raffe,
J. C. Vink-van den Berg, and M. F. Michel.1987
. Comparative activities of ciprofloxacin and
ceftazidime against Klebsiella pneumoniae in vitro and in
experimental pneumonia in leukopenic rats. Antimicrob. Agents
Chemother.
31:1809-1815.[Abstract/Free Full Text]
- Stass,
H., and A. Dalhoff. 1997. Determination of BAY
12-8039, a new 8-methoxyquinolone, in human body fluids by
high-performance liquid chromatography with fluorescence detection
using on-column focusing. J. Chromatogr. B
702:163-174.[CrossRef][Medline]
- Steimer,
J. L., A. Mallet, J. L. Golmard, and J. F.
Boisvieux. 1984. Alternative approaches to estimation
of population pharmacokinetic parameters: comparison with the nonlinear
mixed effect model. Drug Metab. Rev.
15:265-292.[Medline]
- Wilkinson,
L. 1999. SYSTAT: the system for statistics. SYSTAT,
Inc., Evanston, Ill.
Antimicrobial Agents and Chemotherapy, June 2004, p. 2061-2068, Vol. 48, No. 6
0066-4804/04/$08.00+0 DOI: 10.1128/AAC.48.6.2061-2068.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
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