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49（ 49 ）Population pharmacokinetics of cefditoren pivoxil
in non-infected adults
KAYOKO MATSUMOTO, NOBUO SATO, NAYU MITOMI,YOSHIHISA SHITARA and SHIGEKI SHIBASAKI
Pharmaceutical Research Center, Meiji Seika Pharma Co., Ltd.
(Received for publication December 10, 2013)

Population pharmacokinetic analysis was conducted on cefditoren pivoxil(CDTR-PI), a third generation oral antibiotic to evaluate the effect of covariates on
pharmacokinetic parameters. Plasma concentrations of cefditoren (CDTR, total
number of sampling points: 2864) obtained from healthy adult subjects, elderlies,
and subjects with renal dysfunction (287 subjects) after CDTR-PI administration as
well as demographic data of those subjects were used for analysis. We conducted the
population pharmacokinetic analysis of CDTR-PI using a nonlinear mixed effects
PRGHOLQJ 1210(0  PHWKRG $ RQHFRPSDUWPHQW PRGHO ZLWK D ¿UVWRUGHUDEVRUSWLRQDQGODJWLPH¿WWHGZHOOWRSODVPDFRQFHQWUDWLRQWLPHFXUYHIRU&'75
7KH VXEMHFW FRYDULDWH VLJQL¿FDQWO\ DIIHFWLQJ SKDUPDFRNLQHWLF SDUDPHWHUV RI
CDTR-PI was demonstrated by population pharmacokinetic analysis. The absorption
rate constant (ka: hr−1) of CDTR-PI decreased with age, total clearance adjusted bybioavailability (CL/F: L/hr/kg) increased with increasing creatinine clearance
adjusted by body weight (Ccr: mL/min/kg) and volume of distribution adjusted bybioavailability (Vd/F: L/kg) decreased with increasing body weight (WT: kg). In
addition, the lag time (Tlag: hr) depends on formulation (tablet or granule) of
CDTR-PI and the absorption lag time of the tablet was longer than that of the
granule.
We could obtain the population mean parameters of CDTR-PI together withinterindividual variability and intraindividual residual variability after oral
administration of CDTR-PI to adult subjects. In the future, this information will
enable us to simulate the plasma concentrations of CDTR in subjects with various
GHPRJUDSKLF EDFNJURXQGV ZKLFK FRQWULEXWHV WR IXWXUH H[DPLQDWLRQ RI WKH HI¿FDF\and safety of CDTR-PI.

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Introduction
Cefditoren pivoxil (CDTR-PI) is a third generation cephalosporin antibiotic synthesized by
Meiji Seika Pharma Co., Ltd.1). It is an oral pro-drug for which gastrointestinal absorption has
been enhanced by making pivaloyloxymethyl ester at the C4-carboxylic acid of cefditoren(CDTR) that has a broad spectrum and strong antibacterial activity2) against aerobic and anaerobic Gram-positive bacteria as well as Gram-negative bacteria3). After oral administration, thiscompound is absorbed from the gastrointestinal tract and its ester bond is immediately hydrolyzed by an esterase in the enteric canal walls. It is distributed in plasma and tissues as CDTR, anantibacterial active form1, 4〜6). This compound was approved in Japan in 2005, and the dosing
regimen for an adult is three times daily at 200 mg as maximum. As of March 2012, this compound was approved and marketed in 29 countries including not only Asian nations such as
Korea and China, but also European countries and the United States of America. One time dosageof 200 mg has been commonly used for adult patients.
Pharmacokinetics of this compound have been investigated in clinical trials in adult subjects
and reported7〜11), however, population pharmacokinetic analysis in adult has not been conductedyet.
In this analysis, population pharmacokinetics were investigated on CDTR-PI, using plasma
concentrations obtained in several clinical pharmacological studies in Japan and the USA as well
as demographic data of the subjects. As a result, the covariates that are related to pharmacokinetic
SDUDPHWHUVRI&'753,ZHUHFODUL¿HGWRGHWHUPLQHWKHSKDUPDFRNLQHWLFVRI&'75DIWHU&'75
PI administration. In addition, it would be also possible to simulate plasma concentrations of
CDTR on the basis of hypothesized particular demographic data, which would contribute to evalXDWLRQRIWKHHI¿FDF\DQGVDIHW\RIWKLVFRPSRXQG

Materials and Methods
Pharmacokinetic sampling
Plasma CDTR concentrations (total sampling points: 2864) obtained from 287 subjects in 5
clinical trials (clinical pharmacology studies) that were conducted in Japan between 1987 and1997 and 6 clinical trials (clinical pharmacology studies)5, 8〜10, 12) in the USA between 1998 and
1999, and demographic data of those subjects were used for analysis (Table 1). These studies
were all performed in accordance with the declaration of Helsinki, the ethics committee approval,
and the informed consent of all subjects. CDTR-PI was administered at doses of 1.3 mg/kg〜
5.9 mg/kg (100〜300 mg/man: Japan) or 2.1 mg/kg〜8.5 mg/kg (400 mg/man: USA). The plasma
CDTR concentrations were measured with Bioassay method where Escherichia coli NIHJ JC-2
was used as a test bacterial strain (quantitation limit, 0.025 ȝg/mL)13), or HPLC-UV method

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51（ 51 ）Table 1. Sources of plasma cefditoren concentration data collected in adult clinical trials*; after administration(quantitation limit, 0.05 ȝg/mL)7, 14), or LC-MS/MS method (quantitation limit, 0.02 ȝg/mL). The
plasma concentrations of CDTR and demographic data of the subjects used for analysis were collected retrospectively from medical records and clinical study reports.
Software and algorithms
For standard pharmacokinetic analysis, Phenix Winnonlin (ver. 6.1) was used. For population pharmacokinetic analysis, the non-linear mixed effects modeling program, NONMEM (Ver.
VI, LEVEL 2.0, PREDPP Ver. V LEVEL 2.0) and Wings for NONMEM (Ver. 6) were used. The¿UVWRUGHUFRQGLWLRQDOHVWLPDWLRQ )2&( PHWKRGZLWKRXWLQWHUDFWLRQZDVHPSOR\HGDVDOJRULWKP
Digital Visual Fortran (Version 11.1, Intel Corporation) was used as compiler. Wings for NONMEM (Ver. 6) was used for model validation by bootstrap method, and Microsoft Excel 2003
0LFURVRIW&RUSRUDWLRQ ZDVXVHGIRUSUHSDUDWLRQRIWDEOHVDQG¿JXUHVDVZHOODVFDOFXODWLRQRI
statistical parameters. The computer used for analysis was NEC MC-7 (CPU, Celeron 1.8 GHz;
memory, 960 MB; OS, Windows XP Professional).
Population pharmacokinetic analysis
Population pharmacokinetic analysis was conducted using NONMEM to estimate the population pharmacokinetic parameters (population mean parameter, interindividual variability, andintraindividual residual variability), and to estimate the pharmacokinetic parameters of each subject by Bayesian method.
$RQHFRPSDUWPHQWPRGHOZLWK¿UVWRUGHUDEVRUSWLRQZDVXVHGIRUSKDUPDFRNLQHWLFPRGHOing (equation shown below). Pharmacokinetic parameters included in the model were absorption52（ 52 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

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rate constant (ka), total clearance adjusted by bioavailability (CL/F), volume of distribution adjusted by bioavailability (Vd/F), and lag time (Tlag). As there is a difference in weight between
Americans and Japanese (Table 2), the dose was adjusted by body weight (mg/kg) and thus theparameters of CL/F and Vd/F were also adjusted by body weight.
C(t)＝ka*Dose / (Vd/F) / (ka−kel)*{EXP (−kel*(t−Tlag))−EXP (−ka*(t−Tlag))}
C(t): plasma CDTR concentration (ȝg/mL) at time after CDTR-PI administration
Dose: single dosage (mg/kg)
ka: absorption rate constant (hr−1)
F: bioavailability
Vd/F: volume of distribution adjusted with F (L/kg)
kel (＝(CL/F) / (Vd/F)): elimination rate constant (hr−1)
CL/F: total clearance adjusted with F (L/hr/kg)
Tlag: lag time for absorption (hr)The exponential error model was used for determination of interindividual variability inpharmacokinetic parameters, and the proportional error model was used for determination of intraindividual residual variability.
Interindividual variability: Pi＝P×Exp (Și)
Intraindividual residual variability: Cpij＝Cpij+İij
Pi: individual pharmacokinetic parameter
P: population mean of pharmacokinetic parameter
Cpij: individual plasma concentration
Cpij: estimated plasma concentration
Și: error of interindividual variability in pharmacokinetic parameter (the normally distributed interindividual random effect of mean 0 and variance Ȧ2)İij: error of intraindividual residual variability in plasma concentrations (the normally
distributed intraindividual random effect of mean 0 and variance ı2)Firstly, population pharmacokinetic analysis was conducted using the basic model without
any covariates. Bayesian method was used to estimate pharmacokinetic parameters for each subject, and then individual pharmacokinetic parameters and the demographic data of subjects (covariates) were plotted to investigate for any correlations between the parameters.
Covariate analysis
7KHLQÀXHQFHRIHDFKVXEMHFWFRYDULDWHVRQWKHSKDUPDFRNLQHWLFSDUDPHWHUVZDVDQDO\]HGFeb. 2014

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53（ 53 ）The following steps were taken to establish a full model.
Step 1: Demographic data (age, weight: WT, creatinine clearance: Ccr) were sequentially related to the pharmacokinetic parameters (ka, CL/F, Vd/F, Tlag) in the basic model to build addiWLYHPRGHOV$OLNHOLKRRGUDWLRWHVWZDVFRQGXFWHGWRDVVHVVWKHVLJQL¿FDQFHRIGHFUHDVHRI2%-¨ REMHFWLYHIXQFWLRQYDOXH2%- LQWKLVPRGHOFRPSDUHGWRWKDWLQWKHEDVLFPRGHO
7KHFULWHULDIRUMXGJLQJWKHVLJQL¿FDQFHRI ¨ 2%-ZDVVHWWREHDVLJQL¿FDQFHOHYHORIRU
lower in accordance with X2GLVWULEXWLRQ7KHPRGHOZLWKWKHODUJHVW ¨ 2%-ZDVVHOHFWHGDPRQJVLJQL¿FDQWPRGHOVDemographic data were further sequentially related to the selected model in the above to
EXLOG D QHZ DGGLWLYH PRGHO DQG D OLNHOLKRRG UDWLR WHVW ZDV FRQGXFWHG RQ WKH VLJQL¿FDQFH RI
¨ 2%-LQWKLVPRGHOWRWKDWLQWKHDERYHPHQWLRQHGPRGHO
7KLVSURFHGXUHZDVUHSHDWHGXQWLOQRPRUHDGGLWLYHPRGHOZLWKVLJQL¿FDQW ¨ 2%-FRXOGEH
built even though demographic data were sequentially related to any of pharmacokinetic parameWHUV7KHDGGLWLYHPRGHOWKDWZDV¿QDOO\VHOHFWHGZDVGHVLJQDWHGDVD¿QDOPRGHOLQ6WHS
Step 2: Bayesian estimates of individual pharmacokinetic parameters obtained in population
pharmacokinetic analysis using the basic model and the demographic data were plotted. With reference to this result, if the relationship between them is well described by introducing a switch
point into demographic values, such a compartment was adopted in constructing a model. A likelihood ratio test was carried out for the models with and without such a compartment (Finalmodel at Step 1).
Step 3: Using the model selected in Steps 1 and 2 by incorporating the demographic data, theeffects of factors such as the location where the clinical trial was conducted (Japan or the USA) ,formulation of drug product (tablet or granule), and the effect of the gender were examined withthe likelihood ratio test to build a full model.
1H[WDUHGXFHGPRGHOZDVEXLOWE\HOLPLQDWLQJ¿[HGHIIHFWSDUDPHWHUV 7+(7$ RQHE\RQH
IURPWKHIXOOPRGHODQGE\FRQGXFWLQJDOLNHOLKRRGUDWLRWHVWRQWKHVLJQL¿FDQFHRILQFUHDVHLQ¨ 2%-LQWKLVPRGHOFRPSDUHGWRWKDWLQWKHIXOOPRGHO$OOLQVLJQL¿FDQW7+(7$VZHUHUHPRYHG
IURPWKHIXOOPRGHOIRURSWLPL]DWLRQWRWKH¿QDOPRGHO7KHFULWHULDIRUMXGJLQJWKHVLJQL¿FDQFH
RI ¨ 2%-ZDVVHWWREHDVLJQL¿FDQFHOHYHORIRUORZHULQDFFRUGDQFHZLWK;2 distribution.
7KHSRSXODWLRQSKDUPDFRNLQHWLFSDUDPHWHUVZHUHHVWLPDWHGXVLQJWKH¿QDOPRGHOHVWDEOLVKHG
in the above.
Model evaluation
7KHYDOLGLW\RIWKH¿QDOPRGHOZDVHYDOXDWHGRQWKHEDVLVRIWKHYDOLGLW\RIJRRGQHVVRI¿W
plots shown below:— Correlation between predicted concentrations based on population mean parameters(Cpred_mean) and observed concentrations in plasma (Cobs)

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Feb. 2014— Correlation between predicted concentrations based on Bayesian estimates (Cpred_indiv) andobserved concentrations in plasma (Cobs)— Distribution of predicted concentrations based on population mean parameters (Cpred_mean)and conditional weighted residuals (CWRES)%RRWVWDSYDOLGDWLRQZDVXVHGWRHYDOXDWHWKHYDOLGLW\DQGUREXVWQHVVRIWKH¿QDOPRGHO7ZR
hundred data sets ware reconstructed by resampling the subjects from the original dataset. SucFHVVIXOHVWLPDWLRQZDVGH¿QHGDVWKHQRUPDOFRPSOHWLRQRIERWKHVWLPDWLRQDQGFRYDULDQFHVWHSV
RI 1210(0 )RU HDFK SDUDPHWHU HVWLPDWH ZKHQ FDOFXODWLRQ ZDV ¿QDOL]HG ZLWKRXW HUURU WKHmean, standard error (SE), minimum value (Min), median value (Median), maximum value
0D[  DQG  WZRVLGHG FRQ¿GHQFH LQWHUYDO &,  LQ SHUFHQWDJH ZHUH FDOFXODWHG WR H[DPLQH
WKHLUVLPLODULW\WRWKHSDUDPHWHUHVWLPDWHVLQWKH¿QDOPRGHOResults
Demographic data
The demographic data of the subjects used for analysis are shown in Table 2, and the relationship among them are shown in Fig. 1. The data for analysis included gender, age (years),
body weight (WT; kg), creatinine clearance adjusted by body weight (Ccr; mL/min/kg) converted
from creatinine clearance (Ccr; mL/min) that was calculated with the Cockcroft-Gault method15)
from serum creatinine concentration (Scr; mg/dL), the country where a clinical trial was conducted (Japan or the USA), and formulation (FM; tablet or granule) of drug product. As for clinical trials conducted in Japan, the subjects were all Japanese. On the other hand, as for clinical
trial conducted in the USA, the subjects included Blacks, Caucasians, and Hispanics. The total
number of subjects enrolled were 287, among which 111 subjects were from studies conducted inJapan (72 subjects administered with tablets, and 39 subjects administered with granules) and 176
subjects from the study conducted in the USA (all administered with tablets). When categorized
by gender, there were 209 males and 78 females. The average dose was 3.75±1.85 mg/kg (mean±S.D.), and the minimum, median and maximum values of doses were 1.30, 3.60, and 8.47 mg/
kg, respectively. When the demographic data of the subjects were plotted, age was related with&FUDQG&FUWHQGHGWRGHFUHDVHZLWKDJH7KHUHZDVQRGH¿QLWHUHODWLRQVKLSVEHWZHHQJHQGHUDQG
patientsʼ demographic data (Fig. 1).
Plasma CDTR concentrations
The plasma concentrations of CDTR measured in all the clinical trials are shown in Fig. 2.
From the results, it was found that CDTR was eliminated mono-exponentially from the plasma.
Concerning a structure model, a model with or without lag time and a transit compartment
model for one-compartment model and two-compartment model were evaluated (data notFeb. 2014

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55（ 55 ）Table 2. Demographic data of the subjects

FM: formulation

Fig. 1. Relationships in patient demographic data

shown). Considering the presence or absence of the convergence of calculations in NONMEM
DQGWKH2%-YDOXHDRQHFRPSDUWPHQWPRGHOZLWK¿UVWRUGHUDEVRUSWLRQDQGODJWLPHZDVFRQsidered the most suitable structure model for population pharmacokinetic analysis of CTDR-PI.
Population pharmacokinetic analysis
Population mean parameters obtained in the basic model were as follows: ka (hr−1)＝1.04,
CL/F (L/hr/kg)＝0.337, Vd/F (L/kg)＝0.67, Tlag (hr)＝0.89, interindividual variability: Ȧ (ka)＝56（ 56 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

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Feb. 2014)LJ  3ODVPDFRQFHQWUDWLRQWLPHSUR¿OHVRIFHIGLWRUHQGHWHUPLQHGLQDOOWKHFOLQLFDOWULDOVThe plasma concentrations of cefditoren obtained from healthy adult subjects, elderlies, and subjects with renal
dysfunction (287 subjects) after oral administration of cefditoren pivoxil (1.30〜8.47 mg/kg).

84.0%, Ȧ (CL/F)＝46.6%, Ȧ (Vd/F)＝29.4%, intraindividual residual variability: ı＝0.465 ȝg/mL.
Interindividual variability of Tlag was not estimated.
$FFRUGLQJWRJRRGQHVVRI¿WSORWVREWDLQHGLQWKHEDVLFPRGHOREVHUYHGSODVPDFRQFHQWUDtions coincided relatively well with individual estimates calculated from population mean parameters, and such individual estimates and CWRES were almost equally distributed in the upper andlower sides with the distribution centered around zero (data not shown). When Bayesian estimates for pharmacokinetic parameters (ka, CL/F, Vd/F) and demographic data (age, WT, Ccr,
gender) were plotted, the following tendencies were noted: a negative correlation between Bayesian estimate of ka and age, a negative correlation between Bayesian estimate of CL/F and age,
and a positive correlation between Bayesian estimate of CL/F and Ccr. In addition, a negative
correlation was found between Bayesian estimate of Vd/F and WT (Fig. 3-A). On the other hand,
WKHUHZDVQRGH¿QLWHJHQGHUGLIIHUHQFHLQWKHGHPRJUDSKLFGDWD )LJ% 
The development process of the full model is shown in Table 3.
As Step 1, likelihood ratio test where each subjectsʼ demographic data is sequentially included as a covariate into pharmacokinetic parameter, with reference to the results of plotting in
the basic model, was repeated to construct an additive model. Based on the plots of the Bayesianestimates of pharmacokinetic parameters versus the demographic data (Fig. 3) as well as generalknowledge on the relationship between Ccr and CL/F, CL/F was considered to have leveled offalong with an increase in Ccr.
Therefore, as Step 2, a switch point for Ccr (0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5 mL/min/kg)
was introduced into the model selected in Step 1 for investigation. As a result, ΔOBJ was foundWR EH WKH ODUJHVW DQG PRVW VLJQL¿FDQW S＜0.01, drgree of freedom(df)＝2, likelihood ratio test)Feb. 2014

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57（ 57 ）Fig. 3. Relationship between demographic data (A: Age, WT and Ccr, B: Gender) and unnormalized apparent pharmacokinetic parameters (ka, CL/F and Vd/F) of cefditoren
estimated by Bayesian method using the basic model
B: IQR; interquartile range, Dotted line; median, solid line; average, Box＝25 and 75th percentile.

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Table 3. Covariate model building

1) Reference model2) Ȥ2-test (df=1): ΔOBJ＞3.84 (p＜0.05), Ȥ2-test (df=2): ΔOBJ＞5.99 (p＜ 161RWVLJQL¿FDQW)RUZDUGFULWHULDS＜
0.05, Backward criteria: p＜0.001
3) FM: 0=tablet, FM: 1=granule

Table 4. Population pharmacokinetic parameters of cefditoren pivoxil

FM: 0=tablet, FM: 1=granule

when a switch point for Ccr at 1.25 mL/min/kg was included in CL/F .
As Step 3, when the effect of product form (FM: formulation) on each pharmacokinetic paUDPHWHUZDVH[DPLQHGLQWKHDERYHPHQWLRQHGPRGHO7ODJZDVWKHRQHPRVWO\LQÀXHQFHG S＜
0.001, df＝1, likelihood ratio test). Additionally, the effect of the clinical trial location on eachFeb. 2014

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59（ 59 ）)LJ  *RRGQHVVRI¿W SORWV IRU WKH ¿QDO SRSXODWLRQ SKDUPDFRNLQHWLF PRGHO IRU FHIGLWRUHQ
pivoxil
A: Population predicted concentrations versus observed concentrations.
B: Individual predicted concentrations versus observed concentrations.
C: Population predicted concentrations versus conditional weighted residual.

SKDUPDFRNLQHWLFSDUDPHWHUZDVH[DPLQHGZKLFKUHVXOWHGLQQRVLJQL¿FDQWHIIHFWRQDQ\RIWKH
pharmacokinetic parameters (full model).
Since there was no gender difference in the subjectsʼ demographic data, gender difference
was not examined (Fig. 3-B).
Finally a reduced model was developed on the basis of the full model, and ΔOBJ was deterPLQHG DJDLQVW WKH IXOO PRGHO$V D UHVXOW D FRHI¿FLHQW RI DJH ș  ZDV QRW VLJQL¿FDQW DJDLQVW
7ODJZKLFKZDVWKHQH[FOXGHGWRSURGXFHWKH¿QDOPRGHO 7DEOH 

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Table 5. Results of the bootstrap analysis

Criterion for success of calculation: “Minimization successful” only
Successful rate of calculation=86% (172/200)

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Model evaluation*RRGQHVVRI¿WSORWVREWDLQHGLQWKH¿QDOPRGHODUHVKRZQLQ)LJFeb. 2014

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61（ 61 ）Observed plasma concentrations were coincided well with the individual estimates calculated from Bayesian estimates, t and the individual estimates calculated from the population mean
parameters and CWRES were almost equally distributed in the upper and lower sides with the
distribution centered around zero. The results of model validation using bootstrap method areshown in Table 5. Eighty-six percentage of calculations (172 runs out of 200 runs) completed
successfully. Mean value or median value of each parameter calculated by the bootstrap method
ZDVVLPLODUWRWKHSDUDPHWHUHVWLPDWHVIURPWKH¿QDOPRGHO ¿QDOHVWLPDWHV 7KH¿QDOHVWLPDWHV
IRUDOOWKHSDUDPHWHUVZHUHZLWKLQWKHUDQJHRIHPSLULFDOFRQ¿GHQFHLQWHUYDOVREWDLQHGIURPthe bootstrap method. Accordingly, the population pharmacokinetic parameters shown in Table 4
were judged to be appropriate.

Discussion
Population pharmacokinetic parameters of CDTR-PI were determined using plasma CDTR
concentrations (2864 points) when CDTR-PI was orally administered to 287 subjects at 1.3〜
8.5 mg/kg after meals. The location where a clinical trial was conducted did not affect any of thepharmacokinetic parameters.
This model showed lowered ka (absorption rate) of CDTR-PI with age. In general, the intesWLQDO SODVPD ÀRZ YROXPH DQG JDVWURLQWHVWLQDO PRWLOLW\ DUH GHFUHDVHG LQ WKH HOGHUO\16〜21), which
may result in lowered absorption rate. The physicochemical properties of CDTR-PI itself, however, can be a causative factor as well. The solubility of CDTR-PI in water has been reported to
be as low as ca. 80 μg/mL22). In addition, the solubility of CDTR-PI is relatively high in theacidic region (pH1〜2), while it is lowered to 1/10〜1/100 at pH3 or higher23). Since gastric pH
in the elderly is generally higher than that in young adults16), the solubility of CDTR-PI in thestomach may get lowered with age. The relationship between gastric pH and absorbance was examined in an in vivo study using dogs, which showed decreases in both the absorbed amount andabsorption rate along with an increase in pH24). Moreover, a clinical trial revealed that concomitant use of CDTR-PI with antacid tablets lowered the absorbed amount and absorption rate of thiscompound12),WLVDOVRNQRZQWKDWWKHYROXPHRIJDVWULFPXFRVDOÀXLGGHFUHDVHVZLWKDJH16), andthus the solubility of CDTR-PI may become lowered with age due to the factors of pH and watercontents. It would contribute to lowered absorption rate of CDTR-PI. Finally, the population
pharmacokinetic analysis results were considered not to be contradictory to the discussion mentioned in the above.
Next, Ccr affected CL/F of CDTR, and CL/F was reduced along with decreased Ccr (deterioration of the renal function) in this model. These results seem to be reasonable, since CDTR-PI
is mainly excreted via the kidney25). When the renal function was within the normal range (Ccr＞
1.25 mL/min/kg), the effect of Ccr was rather mild. The renal function is known to deteriorate62（ 62 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

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with age in general, and the average GFR in
the subjects whose renal function is normal atrespective age is expressed in the following
equation26).

1) Ccr was assumed to be approximated by GFR2) Cmax at single administration
3) Cmax at steady state4) AUC 0–∞ at single administration=AUCĲ (AUC of the dosing interval at steady state) at repeated administration

Using this equation, GFR for each age
was calculated in the range from 25 to 85 years
old, and the population mean pharmacokinetic
parameters in case of body weight at 70 kg areshown in Table 6. GFR was assumed to be approximated by Ccr. Plasma concentrations of
CDTR after single or repeated oral administration of CDTR-PI at 1.5 mg/kg (ca. 100 mg/man) to adult subjects were simulated at eachage using the population mean parameters(Fig. 5-A, E). As a result, ka decreased withage in the absorption process, and CL/F decreased along with age-dependent degrease in
GFR in the elimination process. Vd/F was,however, constant regardless of age, and thus
T1/2 was prolonged. In other words, Cmax of
CDTR was decreased and AUC tended to increase with age after oral administration of
CDTR-PI to adult subjects with normal renal
function. On the other hand, when CDTR-PI
was administered repeatedly three times a day,the plasma CDTR concentration level reacheda steady state immediately after administration,and there was no accumulation at any age.
According to the population mean parameters of CDTR-PI obtained in this study, Ccr at
the age of 65 was decreased by 36% comparedto that at the age of 25; however there wasonly 11% decrease in the comparison of CL/F
7DEOH 7KLVLQGLFDWHVWKDWJORPHUXODU¿OWUD-

Table 6. Estimates of pharmacokinetic parameters

GFR (mL/min/1.73 cm3)＝−1.163×(Age)＋157.0

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63（ 63 ）Fig. 5. Simulated plasma concentrations of cefditoren after oral administration of cefditoren
pivoxil at 1.5 mg/kg (ca. 100 mg/man) to adult subjects at each age using the population
mean parameters
A; Single dose: 1.5 mg/kg (ca. 100 mg/man). Black bold solid line: Age: 25, WT: 70 kg, Ccr: 1.83 mL/min/kg. Black dashedline: Age: 45, WT: 70 kg, Ccr: 1.50 mL/min/kg. Gray bold solid line: Age: 65, WT: 70 kg, Ccr: 1.16 mL/min/kg. Black solidline: Age: 85, WT: 70 kg, Ccr: 0.83 mL/min/kg.
B; Single dose: 1.5 mg/kg (ca. 100 mg/man). Black bold solid line: Age: 25, WT: 70 kg, Ccr: 1.83 mL/min/kg. Black dashedline: 95% Confidence interval of plasma concentrations at 25 years old. Gray bold solid line: Age: 65, WT: 70 kg, Ccr:
1.16 mL/min/kg. Gray dashed line: 95% Confidence interval of plasma concentrations at 65 years old.
C; Single dose: 1.5 mg/kg (ca. 100 mg/man). Black bold solid line: 95% Confidence interval of plasma concentrations at
25 years old. Gray solid line: Plasma concentrations of simulated 100 subjects (Age: 25, WT: 70 kg, Ccr: 1.83 mL/min/kg).
D; Single dose: 1.5 mg/kg (ca. 100 mg/man). Black bold solid line: 95% Confidence interval of plasma concentrations at
65 years old. Gray solid line: Plasma concentrations of simulated 100 subjects (Age: 65, WT: 70 kg, Ccr: 1.16 mL/min/kg).
E; Repeated administration, 1.5 mg/kg (ca.100 mg/man) x 3 times/day. Black bold solid line: Age: 25, WT: 70 kg, Ccr:
1.83 mL/min/kg. Black dashed line: Age: 45, WT: 70 kg, Ccr: 1.50 mL/min/kg. Gray bold solid line: Age: 65, WT: 70 kg,
Ccr: 1.16 mL/min/kg. Black solid line: Age: 85, WT: 70 kg, Ccr: 0.83 mL/min/kg.

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Feb. 2014tion is not largely involved in the renal excretion of CDTR, and instead active transport systems
such as secretion play a role27). Actually, the results of clinical trial on CDTR-PI in concomitant
use of probenecid suggested an involvement of secretion in the renal excretion of CDTR11, 25).
That is, CL/F of CDTR is affected by the factor of age in adult subjects with normal renal funcWLRQVEXWWKHGHJUHHRIVXFKLQÀXHQFHPD\EHPLQRU2QWKHRWKHUKDQGLQDFOLQLFDOWULDOZKHUH
the effect of age on pharmacokinetics was examined after oral administration of CDTR-PI, both
Cmax and AUC of CDTR were reportedly increased with age8, 28). This is because the renal clearance (CLr) in the elderly subjects aged 65 or higher was 3.2 L/hr, which was 24% lower than
4.2 L/hr in young adult subjects aged between 25 and 40. This elderly subject group included
those with renal dysfunction (personal communications), whose decrease in CL/F was so largethat the impact of decreased CL/F on the increase in Cmax obviously exceeded the effect of agedependent decrease in ka.
Next, Monte Carlo simulation was repeated 100 times on the basis of the plasma concentraWLRQSUR¿OHV )LJ$ VLPXODWHGIURPWKHSRSXODWLRQPHDQSDUDPHWHUVLQWKHVXEMHFWVDJHGDWand 65 years as well as interindividual variability determined in population analysis. Fig. 5-B, C,'VKRZWKHSODVPDFRQFHQWUDWLRQSUR¿OHVDQGHPSLULFDOFRQ¿GHQFHLQWHUYDORIVXFKVXEMHFWV$V D UHVXOW WKH SODVPD FRQFHQWUDWLRQ SUR¿OHV DW ERWK DJH JURXSV ODUJHO\ RYHUODSSHG ZLWKHDFKRWKHU7KHHPSLULFDOFRQ¿GHQFHLQWHUYDOIRU&max was 1.07〜4.29 for the age of 25 and0.40〜IRUWKHDJHRI7KHHPSLULFDOFRQ¿GHQFHLQWHUYDOIRU$8&ZDV〜31.15
for the age of 25 and 2.37〜41.22 for the age of 65, indicating the estimates were also largely
overlapping with each other. This suggests that Cmax and AUC are likely to be affected by age;
however the plasma concentrations of CDTR after oral administration of CDTR-PI in both age
groups may be comparable when you consider interindividual variations. Accordingly, it was
judged there would be no need of dosage adjustment depending on ages in oral administration of
CDTR-PI to adult subjects with normal renal function based on the fact that CL/F of CDTR is notlargely affected by the age as well as the interindividual variability of plasma concentrations.

Conclusion
Population pharmacokinetic parameters of CDTR-PI were obtained using plasma CDTR
concentrations for oral administration of CDTR-PI after meals to adult subjects.
6LJQL¿FDQWFRYDULDWHVIRU&'753,ND&/)9G)DQG7ODJZHUHDJH&FU:7DQGIRUPXlation (tablet or granule), respectively.
The ka decreased with age, CL/F increased with increasing Ccr and Vd/F decreased with increasing WT. In addition, the Tlag depends on formulation of CDTR-PI and the lag time in absorption of the tablet was longer than that of the granule.
As mentioned above, we could obtain the population mean parameters of CDTR-PI together

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65（ 65 ）with interindividual variability and intraindividual residual variability after oral administration of
CDTR-PI to adult subjects. In the future, this information will enable us to simulate the plasma
concentrations of CDTR in subjects with various demographic backgrounds, which contributes to
IXWXUHH[DPLQDWLRQRIWKHHI¿FDF\DQGVDIHW\RI&'753,&RQÀLFWRILQWHUHVWThis work was sponsored by Meiji Seika Pharma Co., Ltd. KAYOKO MATSUMOTO, NOBUO
SATO, NAYU MITOMI, YOSHIHISA SHITARA and SHIGEKI SHIBASAKI are employees of Meiji Seika
3KDUPD7KHDXWKRUVGHFODUHWKDWWKH\KDYHQRFRQÀLFWRILQWHUHVWReferences
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