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Population pharmacokinetic modeling andpharmacodynamic assessment of cefozopran inpediatric patients
KAZURO IKAWA*, TOSHIHIRO KOZUMI,KAYO IKEDA and NORIFUMI MORIKAWA
Department of Clinical Pharmacotherapy, Graduate School of Biomedical
Sciences, Hiroshima University

RYOJI KOBAYASHI
Department of Pediatrics, Sapporo Hokuyu Hospital(Received for publication July 13, 2009)

The aims of this study were to develop a population pharmacokinetic model forcefozopran in pediatric patients, and to use this model to evaluate the pharmacodynamics of cefozopran regimens against common bacterial populations. Plasma drugconcentration data (110 samples from 31 pediatric patients) were modeled using the
NONMEM program. The mean estimate and interindividual variance of the model
were used in a Monte Carlo simulation to estimate the probabilities of attaining thebactericidal target for cefozopran (the time which the drug concentration remains
above the minimum inhibitory concentration for the bacterium is 70% of the dosinginterval). A two-compartment model ﬁtted the data and body weight (BW, kg) was themost signiﬁcant covariate. The ﬁnal model was: Cl (l/h)⫽0.674⫻BW0.538, Vc (l)⫽0.00233⫻BW2.25⫹1.85, Q (l/h)⫽1.46, and Vp (l)⫽0.0964⫻BW, where Cl is the clearance, Vc, and Vp are the volumes of distribution of the central and peripheral compartments, and Q is the intercompartmental clearance. The approved regimens of 20- or
40-mg/kg four times a day (0.5-h infusions), which were more effective than the corresponding three times a day-regimens, provided sufﬁcient bactericidal effects on common bacterial populations (Escherichia coli, Streptococcus pneumoniae, Haemophilus
inﬂuenzae, and Pseudomonas aeruginosa) in most typical patients. These results betterdeﬁne the pharmacokinetics of cefozopran and help in the choice of appropriate regimens for pediatric patients.

Introduction
Cefozopran is a parenteral cephalosporin with a broad spectrum of activity against Gram-positive and Gram-negative bacteria. It has been clinically available in Japan since the late 1990s for the436 (42)

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treatment of various infections such as pneumonia, sepsis, urinary-tract- and intra-abdominal-infections, not only in adult patients but also in pediatric patients1).
Understanding the pharmacokinetics of an antibacterial agent in speciﬁc populations, such as
pediatric and geriatric patients, is important for adjusting or optimizing dosing regimens. Although
the pharmacokinetic proﬁles of cefozopran have been well deﬁned in adult patients2), those in pediatric patients have not been fully characterized. Treatment of pediatric patients would beneﬁt by abetter deﬁnition of cefozopran pharmacokinetics in this population. In particular, a population pharmacokinetic approach has the advantage that it can predict the pharmacokinetic parameters of a particular subject from covariates, such as body size and physiological functions, without the need totake blood samples.
The pharmacology of antibacterial chemotherapy is determined by the interrelationshipbetween its pharmacokinetics and pharmacodynamics. Cephalosporins exhibit time-dependent in vitro
and in vivo activity, and their antibacterial effects correlate with the time that the drug concentration
remains above the minimum inhibitory concentration (MIC) for the bacterium (T⬎MIC)3). In order
to assess the pharmacodynamics of cephalosporin therapy, the probability that a T⬎MIC target isattained (the probability of target attainment)4) should be estimated. These estimations should involve
Monte Carlo simulations5,6) which enable variability to be incorporated into individual pharmacokinetics and antibacterial activities against a population of clinical isolates.
The present study therefore aimed to develop a population pharmacokinetic model for cefozopran in pediatric patients in order to estimate the associated pharmacokinetic parameters, their variability and the inﬂuence of potential covariates. By incorporation of this model into a Monte Carlosimulation, this study also aimed to assess the pharmacodynamics of cefozopran regimes against
common bacterial populations in order to help in the choice of dosage for pediatric patients.

Materials and Methods
Pharmacokinetic data
Pharmacokinetic data were collected from 31 Japanese pediatric patients, who underwent therapeutic drug monitoring at Sapporo Hokuyu Hospital or were included in clinical studies7,8). Plasma
samples were obtained after a 0.05- to 0.5-h infusion of 10⬃40 mg/kg cefozopran. Drug concentrations in plasma were measured using two compatible methods, high-performance liquid chromatography and bioassay, as reported previously9,10). Patient characteristics that were determined included
sex, age, body weight, serum creatinine, and blood urea nitrogen.
Population pharmacokinetic analysis
Population pharmacokinetic analysis was performed using the NONMEM program version VI(ICON Development Solutions, Ellicott, MD, USA). Both one-compartment and two-compartment

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models were tested to deﬁne the most appropriate basic pharmacokinetic model. The interindividual
variability was modeled exponentially using the following equation:q i⫽q ⫻exp(h i)where q i is the ﬁxed-effects parameter for the i-th subject, q is the mean value of the ﬁxedeffects parameter in the population, and h is a random interindividual variable which is normally
distributed with a mean of 0 and variance w 2. The residual (intraindividual) variability was modeledusing a proportional error model according to the following equation:
Cobs, ij⫽Cpred, ij⫻(1⫹e ij)
where Cobs, ij and Cpred, ij denote the j-th observed and predicted concentrations for the i-th subject,and e is a random intraindividual error which is normally distributed with a mean of 0 and variances 2.
The individual pharmacokinetic parameters obtained from the basic model were plotted against
patient characteristics. Covariates that showed a correlation with the pharmacokinetic parameters
were then introduced into the model. The signiﬁcance of the inﬂuence of the covariates was evaluated by changes of the ⫺2 log likelihood (the minimum value of the objective function, OBJ). An
OBJ decrease of ⬎3.84 from the basic model (P⬍0.05; c 2 test) was considered statistically signiﬁcant during the covariate screening process. The full model was built by incorporating the signiﬁcant covariates, and the ﬁnal model was developed by a backward deletion method. The coefﬁcientsin the full model were excluded from the model one at a time, and an OBJ increase of ⬎6.63 fromthe full model (P⬍0.01; c 2 test) was considered statistically signiﬁcant.
Microbiological data
Four common types of pathogenic bacteria were selected for study, and the MIC distribution
data of their clinical isolates (from pediatric, adult, and geriatric patients) were based on a recent
nationwide susceptibility surveillance11): Pseudomonas aeruginosa (n⫽306; MIC50⫽2 m g/ml; MIC90⫽
16 m g/ml), Haemophilus inﬂuenzae (b -lactamase negative ampicillin-susceptible, b -lactamase negative ampicillin-resistant, and b -lactamase positive ampicillin-resistant strains) (n⫽253; MIC50⫽
1 m g/ml; MIC90⫽16 m g/ml), Streptococcus pneumoniae (penicillin-susceptible, penicillin-intermediate, and penicillin-resistant strains) (n⫽184; MIC50⫽0.5 m g/ml; MIC90⫽2 m g/ml), and Escherichia
coli (n⫽130; MIC50⫽0.06 m g/ml; MIC90⫽0.12 m g/ml).
Pharmacodynamic evaluation using a Monte Carlo simulation
A Monte Carlo simulation was conducted to evaluate the pharmacodynamics of cefozopran
regimens approved in Japan (40⬃160 mg/kg daily, divided into three or four doses). For each tested
regimen, the following process was repeated 10000 times using Crystal Ball 2000 software (Oracle,
Redwood Shores, CA, USA). A set of ﬁxed-effects parameters was randomly generated according toeach mean estimate (q ) and interindividual variance (w ) of the ﬁnal population pharmacokinetic

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model. The curve of the plasma concentration of cefozopran versus time was simulated using theﬁxed-effects parameters. The total drug concentration was employed for this purpose because it isclinically equivalent to the free concentration due to negligible protein binding (6.2%)12). The time
point at which the drug concentration coincided with a speciﬁc MIC value was determined, and thetime for which the drug concentration remained above the MIC was ﬁnally calculated as a percentage of the dosing interval.
The probability of target attainment (%) was determined as the fraction that achieved at least
70% T⬎MIC (the bactericidal target)2,13) of 10000 estimates. The probability at a speciﬁc MIC wasthen multiplied by the fraction of the population of the bacterium in each MIC category, and thesum of the individual products was deﬁned as the expected population probability of target attainment (%)4).

Results
In order to develop a population pharmacokinetic model for cefozopran in pediatric patients,
we ﬁrst carried out a population pharmacokinetic analysis of cefozopran plasma concentration data
(110 samples from 31 pediatric patients). The characteristics of the patients (18 males and 13 females) were as follows: age, 5.6⫾2.7 years (mean⫾standard deviation; range, 2.0⬃13.0 years);
body weight, 18.0⫾5.2 kg (11.0⬃43.5 kg); serum creatinine, 0.31⫾0.20 mg/dl (0.10⬃0.90 mg/dl);
and blood urea nitrogen, 6.8⫾4.5 mg/dl (2.5⬃22.0 mg/dl).
Because Akaike information criterion values indicated that the two-compartment model
described the data better than the one-compartment model, the two-compartment model was selected
as the basic model. Therefore, the pharmacokinetic parameters used were: clearance (Cl, l/h), volume of distribution of the central compartment (Vc, l), intercompartmental clearance (Q, l/h), andvolume of distribution of the peripheral compartment (Vp, l).
During the forward inclusion process of building the covariate model, incorporation of bodyweight (BW) into Cl, Vc or Vp caused the largest OBJ change, although age also had a signiﬁcanteffect on each of these parameters. Because age showed a high correlation with BW, it was not additionally incorporated into these three pharmacokinetic parameters in order to avoid a collinearity
effect. None of the covariates examined had a signiﬁcant effect on Q. During the backward deletion
process, every covariate and coefﬁcient remained in the model, causing a signiﬁcant OBJ increase.
Therefore, the ﬁnal model was as follows:
Cl (l/h)⫽0.674⫻BW0.538, Vc (l)⫽0.00233⫻BW2.25⫹1.85, Q (l/h)⫽1.46, and Vp (l)⫽0.0964⫻BW.
The estimates (mean and variability), their standard errors and 95% conﬁdence intervals of the
population pharmacokinetic parameters of the ﬁnal model are summarized in Table 1. Diagnostic
scatter plots indicated that the ﬁnal model accurately reﬂected the data (Fig. 1).
Based on the ﬁnal model, three typical patients, with a BW of 10, 20 or 30 kg, were supposed.

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Table 1. Final population pharmacokinetic parameters of cefozopran in pediatric patients.

As shown in Fig. 2, the probabilities of target (70% T⬎MIC) attainment for six different cefozopran
regimens in the three patients generally increased in the following order: (20 mg/kg, 10 mg/kg, 10
mg/kg) three times a day (t.i.d.)⬍10 mg/kg four times a day (q.i.d.)ⱌ(40 mg/kg, 20 mg/kg, 20 mg/kg) t.i.d.⬍20 mg/kg q.i.d.ⱌ(80 mg/kg, 40 mg/kg, 40 mg/kg) t.i.d.⬍40 mg/kg q.i.d.
Table 2 lists the expected population probabilities of target attainment against common pathogenic bacteria. For all patients, 10 mg/kg q.i.d. achieved 93.6⬃94.3% probability against E. coli
isolates and 20 mg/kg q.i.d. achieved 88.7⬃99.7% probability against S. pneumoniae isolates. However, the probability values were lower against H. inﬂuenzae and P. aeruginosa isolates. A regimenof 20 mg/kg q.i.d. achieved only 83.5⬃84.3% probability in a patient with a BW of 30 kg, and 40
mg/kg q.i.d. was required to achieve a probability ⬎80% in a patient with a BW of 20 kg.

Discussion
We have employed pharmacokinetic analysis to develop a population model for cefozopran inpediatric patients and have identiﬁed BW as the most signiﬁcant covariate that affects cefozopran
pharmacokinetics. Pharmacodynamic assessment using this model showed that administration ofcefozopran at 20 mg/kg q.i.d. and 40 mg/kg q.i.d. achieved a high probability of target attainmentFig. 1.

Diagnostic scatter plots of the ﬁnal population pharmacokinetic model of cefozopran.

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Fig. 2. Probabilities of 70% T⬎MIC attainment using different cefozopran regimens(0.5-h infusions) in patients of differing body weight (BW).
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Table 2. Expected population probabilities of 70% T⬎MIC attainment (%) in three typicalpatients (body weight (BW): 10, 20 or 30 kg) against Escherichia coli, Streptococcus pneumoniae, Haemophilus inﬂuenzae, and Pseudomonas aeruginosa isolates using cefozopran
regimens (0.5-h infusions) of three times a day (t.i.d.) or four times a day (q.i.d.).

against common pathogenic bacteria in most typical patients. This is the ﬁrst report of the population pharmacokinetics and pharmacodynamics of cefozopran in a pediatric patient population.
Previous population pharmacokinetic analysis of cefozopran in adults (23⬃82 years old)2) indicated that cefozopran followed a two-compartment model and that body weight had the greatest
inﬂuence on drug distribution. Population pharmacokinetic modeling of cefozopran in neonates(1⬃27 days old)14) also showed that body weight was the covariate that had the greatest inﬂuence on
cefozopran clearance. The results of our study (Table 1) are consistent with these earlier ﬁndings ofthe importance of body weight. Thus, although age often plays an important role in pharmacokinetics, especially in pediatrics, BW appears to have a more direct effect than age on cefozopran
pharmacokinetics.
The ﬁnal population pharmacokinetic model lacked any bias, regardless of the drug concentration (Fig. 1c) or the time (Fig. 1d), and the observed drug concentration was almost identical to theindividual predicted concentration after the Bayesian step (Fig. 1b). Therefore, the ﬁnal model isOct. 2009

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considered to have a good predictive performance.
In this study, the population pharmacokinetic model was developed not only for descriptive
purposes but also for pharmacodynamic assessment and practical use. The results of the Monte
Carlo simulation (Fig. 2) showed that the probabilities of target attainment for 10 mg/kg q.i.d.
(40 mg/kg/day regimen) and 20 mg/kg q.i.d. (80 mg/kg/day regimen) were comparable to those for(40, 20, 20 mg/kg) t.i.d. (80 mg/kg/day regimen) and (80, 40, 40 mg/kg) t.i.d. (160 mg/kg/day regimen), respectively. This result suggests that the dosing interval is more important than the daily
dosage for dosing of cefozopran, which exhibits time-dependent killing. From a cost-effective viewpoint, q.i.d. regimens would be preferable to t.i.d. regimens, unless frequent drug administration is
unacceptable due to an increase in the patient’s burden and in the medical workload.
The observed differences in the expected population probability of target attainment among thebacteria tested (Table 2) resulted from their varying speciﬁc susceptibilities to cefozopran. Based on
the differences, a regimen of 20 mg/kg q.i.d. would be sufﬁcient against high-susceptibility bacteriasuch as E. coli and S. pneumoniae. However, if infection with cefozopran-resistant bacteria such as
H. inﬂuenzae and P. aeruginosa is suspected then a regimen of 40 mg/kg q.i.d. is recommended,
especially for a patient with a low BW. We should note that susceptibility of clinical isolates (especially resistance of S. pneumoniae) can vary with patient factors such as children/adults and in-/outpatients. Therefore, our results have a limitation in that we could neither obtain MIC distributions
exclusively from children nor extract the MIC distributions for pediatric patients from the surveillance data11). Nevertheless, the proﬁles of the probability of target attainment versus MIC (Fig. 2)
are useful when the MIC value for a bacterium is given, regardless of its susceptibility pattern.

Conclusions
The present study developed a population model for cefozopran in pediatric patients and identiﬁed BW as the most signiﬁcant covariate that affected cefozopran pharmacokinetics. The pharmacodynamics of approved cefozopran regimes were assessed based on this model. The Monte Carlosimulation showed that 20 mg/kg q.i.d. and 40 mg/kg q.i.d. regimens, which were more effective
than the corresponding t.i.d. regimens, had sufﬁcient bactericidal effects against common bacteria inmost typical patients. These results provide a better understanding of the pharmacokinetics of cefozopran. They are also useful in the choice of a cefozopran regimen based on the BW of the pediatricpatient and the susceptibility of the causative bacteria (either suspected because of the patient’s
symptoms or identiﬁed by MIC data). The implications of our ﬁndings and proposals need to be
conﬁrmed in a clinical setting.

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