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159（ 19 ）Population pharmacokinetics of itraconazole inJapanese patients with invasive fungal peritonitis
YUKA YAMAGISHI*, YUKIHIRO HAMADA, MAO HAGIHARA
and HIROSHIGE MIKAMO
Department of Infection Control and Prevention,
Aichi Medical University Hospital(Received for publication March 30, 2013)

Severely ill patients are frequently at risk of developing fungal infection.
Itraconazole (ITCZ), a triazole antifungal agent, is used for the treatment ofcandidiasis, aspergillosis, cryptococcosis. Correlation of pharmacokinetic andpharmacodynamic (PK-PD) parameters with the in vivo bactericidal action of
antimicrobial agents has progressed markedly in recent years. However, the optimal
dosage of antifungal agents based on PK-PD properties has not been clearly
established. In this study, we performed a population pharmacokinetic analysis of
ITCZ after infusion or oral administration of ITCZ in Japanese 51 patients withfungal infections. The population pharmacokinetic analysis was performed using
NONMEM software. The population mean clearance (CL; liter/h) was estimated as
5.15−0.0673×(Age−62) L/h, the population mean volume of distribution (V; liter)
was determined as 878L and the bioavailability (F) was determined as 0.665.

Introduction
7KH FOLQLFDO HI¿FDF\ DQG VDIHW\ RI LQWUDYHQRXV LWUDFRQD]ROH ,7&=  ZHUH VXJJHVWHG LQ WKHmanagement of proven and presumed candidiasis including Candida glabrata in non-neutropenic
patients1). Since the 1990ʼs, in the area of antimicrobial research, rapid advances have been madein both pharmacokinetic (PK) studies, including maximum blood concentration (Cmax), area under
the plasma concentration-time curve (AUC), and elimination half-life (t1/2), and pharmacodynamic (PD) studies, including minimum inhibitory concentration (MIC) and time-killing curve.
Such advances have greatly contributed to the development of proper therapies for infections andthe development and marketing of novel antimicrobial agents. One notable achievement in this
DUHDZDVWKHLGHQWL¿FDWLRQRI3.3' parameters correlated with in vivo bactericidal actions of an-

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timicrobial agents, such as Cmax/MIC or AUC0〜24 h0,& IRU DPLQRJO\FRVLGHV DQG ÀXRURTXLQRlones, and the percentage ratio of time above MIC to dosing interval (%t＞MIC) for ȕ-lactams 2).
These parameters have enabled prediction of the therapeutic effects of certain antimicrobial
agent to some degree, based on pharmacokinetic characteristics as represented by parameterssuch as Cmax, AUC, and t1/2, which are calculated from mean blood concentrations, and pharmacodynamic characteristics represented by parameters such as breakpoint value, MIC50, andMIC90.
2QWKHRWKHUKDQGLQWKH¿HOGRIDQWLIXQJDOUHVHDUFKHYDOXDWLRQRIWKHRSWLPDOGRVDJHEDVHG
RQ3.3'KDV\HWWREHVXI¿FLHQWO\HVWDEOLVKHG/OUIE et al.3)¿UVWH[DPLQHGWKHLPSDFWRIÀXFRQazole dose fractionation and demonstrated that similar outcomes were observed whether the dose
was administered as a single bolus or as two or three smaller doses. These observations suggest
WKDWWKHWUHDWPHQWRXWFRPHLVDIIHFWHGE\QRWWKHGRVLQJLQWHUYDOEXWE\$8&$IWHUWKLVFRQ¿Umation, ANDES et al.LQYHVWLJDWHGWKHUHODWLRQVKLSEHWZHHQHI¿FDF\DQG3.3'SDUDPHWHURIDQWLfungal drugs by dose fractionation studies4〜9). These studies considered the importance of the$8&0,&SDUDPHWHUIRUWULD]ROHV ÀXFRQD]ROHDQGUDYXFRQD]ROH 4,8). Conversely, the importance
RIWKHSHDN0,&SDUDPHWHUKDVEHHQFRQ¿UPHGIRUSRO\HQHDQGHFKLQRFDQGLQ6,7). In the investigaWLRQVZLWKÀXF\WRVLQHW＞0,&ZDVWKHSDUDPHWHUPRVWFORVHO\DVVRFLDWHGZLWKHI¿FDF\5). Data
from these in vivo studies can be used to examine relationships between outcome and parameterby expressing each dosing regimen as a pharmacodynamic parameter. However, compared to antibiotics, optimal dosage based on PK-PD of antifungal agents has not been applied to clinical
SUDFWLFHDQGKDV\HWWREHVXI¿FLHQWO\UHSRUWHG,7&=FRYHUVDEURDGDQWLIXQJDOVSHFWUXPLQFOXGing non-albicans Candida and Aspergillus spp., and is effective for tissue transition as well as
being affordable9〜13)7KLVDJHQWLVZHOOWROHUDWHGDQGKLJKO\HI¿FDFLRXVDVWKHPDLQPHWDEROLWH
hydroxy-itraconazole, also displays considerable antifungal activity. In particular, intravenous
formulation of ITCZ could be used in a wide range of patient populations, including those withsevere infectious complications or requiring intensive care, thanks to the improved bioavailability.
ITCZ have three type formula, capsule, solution, and injection. However, little information isavailable about the population pharmacokinetic (PPK) of ITCZ. In an effort to meet this need, we
performed the clinical study reported here to obtain the PK parameters for ITCZ.

I. Materials and Methods
Subjects
All of the patients admitted to Aichi Medical University Hospital who were treated with
ITCZ 51 injections changed to 36 oral for fungal infections and had blood samples taken to monitor ITCZ concentrations were included in the study. ITCZ was administered by infusion as a 40%

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161（ 21 ）hydroxypropyl-ȕ-cyclodextrin solution in water for injection. After an initial loading period lasting 2 days (200 mg every 12 h×4 times), 200mg ITCZ was infused as a maintenance dose for
60 min every 24 h in all patients. We are analyzed PPK of 236 plasmas ITCZ in 51 patientschanged to 36 oral patients. Relevant clinical background and laboratory data were collected at
appropriate intervals during the ITCZ treatment. We also excluded patients for whom the laboratory data needed for the present study was lacking.
Population pharmacokinetic modeling
The PPK analysis of ITCZ was performed using the non-linear mixed effect model (NONMEM®) software package, version 7.2.014)7KH¿UVWRUGHUFRQGLWLRQDOHVWLPDWLRQZLWKLQWHUDFWLRQ(FOCE-I) algorithm was used for parameter estimation. Conditional weighted residual (CWRES)
was used Bootstrap resampling15) was performed using the MULTTEST procedure of SAS software (SAS Institute Inc.). The concentration-time courses were described by use of a onecompartment model (in accordance with the available post-distribution phase data) with infusion or oral administration. Fixed- and random-effect parameters were estimated by use of the
NONMEM program. The basic pharmacokinetic parameters of clearance (CL), the volume of
distribution (V) and the bioavailability rate constant (F) corresponding to the proposed model
were determined for each patient.
,QWKH¿UVWSKDVHRIWKHDQDO\VLVDEDVLFPRGHOZLWKQRFRYDULDWHVRQ&/9RU)ZDVXVHG
Exponential inter-individual variability models were invoked for each CL and V. The residual
variability was determined by using an exponential error model or combined exponential and additive error model.
In the second phase of the analysis, several covariates were considered to improve the model
VLJQL¿FDQWO\LIWKHGHFUHDVHLQWKHREMHFWLYHIXQFWLRQYDOXH 2)9 ZDV＞3.84 (p＜0.05). The covariate with the greatest decrease in the OFV was added to the base model and the entire procedure was repeated until no further improvement could be obtained. All covariates (sex, age, bodyweight, height) that were included or selected were considered in view of their biological plausiELOLW\%DVLFJRRGQHVVRI¿WSORWVLQFOXGLQJSRSXODWLRQSUHGLFWLRQ 35(' DQGLQGLYLGXDOSUHGLFtions (IPRED) vs. observed concentrations (DV), as well as, conditional weighted residual&:5(6 YV35('DQGWLPHDIWHU¿UVWGRVHZHUHXVHGIRUPRGHOLQJGLDJQRVWLFSXUSRVHV7KH
VWDELOLW\DQGSHUIRUPDQFHRIWKH¿QDOSRSXODWLRQSKDUPDFRNLQHWLFPRGHOZHUHDVVHVVHGXVLQJDQ
internal validation method which involved non-parametric bootstrapping with re-sampling (n＝1000). The model for which the probability of a successful bootstrap run was more than 90% and
WKHSDUDPHWHUHVWLPDWHVZHUHFRPSDUDEOHZDVGH¿QHGDVWKHUREXVWPRGHO7KHPRGHOZDVMXGJHG
RQWKHEDVLVRIWKHJRRGQHVVRI¿WSORWVFRQ¿GHQFHLQWHUYDORIWKHSDUDPHWHUHVWLPDWHDQG
the likelihood ratio test.

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Evaluation of clinical response
The subject were patients of critical care department, 18 years old or older, who received adiagnosis as invasive fungal peritonitis according to the “Guidelines for the Diagnosis/Treatmentof Deep Mycosis in 2007” 16). Clinical response was determined at the end of therapy by the phyVLFLDQVLQFKDUJHDQGWKHQFRQ¿UPHGE\WKHH[SHUWV3DWLHQWUHVSRQVHWRWKHUDS\ZDVFODVVL¿HGDV
IROORZV&OLQLFDORXWFRPHVZHUHFODVVL¿HGDVHLWKHUFXUH HUDGLFDWLRQGXULQJWUHDWPHQWRIWKHRUganism from specimens and/or decreased ȕ-(1,3)-D-glucan value and improvement in clinicalsymptoms) or failure (no change, an increase in the amount of organism in specimens, increased
ȕ-(1,3)-D-glucan value, and a lack of improvement in clinical symptoms).
Susceptibility testing
Antifungal susceptibility testing of isolates of Candida species was performed in exact accordance with the reference broth microdilution method described by the CLSI (Clinical and Laboratory Standards Institute), document M27-A317). Standard powders of ITCZ (Janssen Research
Foundation, Beerse, Belgium) were obtained from the manufacturer and diluted in distilled wateror dimethyl sulfoxide. Frozen microdilution panels, containing serial two-fold dilutions made in
RPMI 1640 medium (Invitrogen, Tokyo, Japan) buffered to pH 7.0 with 0.165 M MOPS buffer(Wako Pure Chemical Industries, Osaka, Japan) for ITCZ were prepared in a single lot at the laboratory of BML Incorporation (Tokyo, Japan), and stored at −80°C until use. Final concentrations of ITCZ were 0.016–16 ȝJP/7KH¿QDOFRQFHQWUDWLRQRIWKHVROYHQWGLGQRWH[FHHGLQ
any of the wells. Drug-free growth control wells and drug- and yeast-free sterility check wells
ZHUHLQFOXGHG7KH0,&IRU,7&=ZDVGH¿QHGDVWKHORZHVWFRQFHQWUDWLRQVKRZLQJLQKLELtion of growth compared with the drug-free control. Approval for this trial was received from theClinical Research and Ethics Committee of the SRNJ. Number of the SRNJ is 0001.

II. Results
The PPK analysis was performed using data 236 plasma ITCZ concentrations collected from
51 adult patients. The plot of time versus total plasma ITCZ concentration is shown in Fig. 1. Descriptive statistics are presented in Table 1. The pharmacokinetics of ITCZ was well-describedusing the one-compartment model, which included the inter-individual variability of CL and V.
Residual variability was modeled using exponential error. In the covariates selection, CL was inÀXHQFHGE\DJHDQG9KDGQRVWDWLVWLFDOO\VLJQL¿FDQWFRYDULDWH7KH¿QDOPRGHODQGLWVSDUDPHWHU
estimates are shown in Table 2 and Eq. 1.

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163（ 23 ）)LJ  3ORWRIWRWDOSODVPDFRQFHQWUDWLRQVRILWUDFRQD]ROHDIWHU¿UVWGRVHLQSDWLHQWVTable 1. Demographic of population pharmacokinetics in patients.

CL＝[șCL＋(Age−62)×ș age(CL)]*eȘCLV2＝șV2*eȘV2

(1)

F＝șF
7KH JRRGQHVVRI¿W SORWV RI WKH ¿QDO PRGHO DUH VKRZQ LQ )LJ  7KH FRQFHQWUDWLRQV SUHdicted using the model and the individual predicted concentrations were consistent with the obVHUYHGFRQFHQWUDWLRQV7KHSORWVIRU&:5(6YV35('DQGWLPHDIWHU¿UVWGRVHSUHVHQWHGJRRG
distribution around 0. The results of the bootstrap validation are shown in Table 2. The successrate was 92.7%, and the estimated population values and the average of the bootstrap results werefairly consistent, which suggested good stability in parameter estimates.
Susceptibility to ITCZ
All 16 in 51 patients available isolates were tested for ITCZ susceptibility in this study, and164（ 24 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

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a. The population predicted concentrations versus the observed concentrations.
b. The individual predicted concentrations versus the observed concentrations.
c. The population predicted concentrations versus the conditional weighted residuals.
G7LPHDIWHU¿UVWGRVHYHUVXVWKHFRQGLWLRQDOZHLJKWHGUHVLGXDOVthe results are shown in Table 3. Data are reported as the MIC range in 4 species of Candida.
Clinical cure rate was 81.25% and the population comprised 13 responders and 3 non-responders.
Non-responders showed higher MICs.

III. Discussion
This analysis has presented a PPK model that adequately describes the pharmacokinetics of
ITCZ in candidiasis. Although two-compartment models are used for many antibiotics with shortinfusions, a one-compartment model analysis was adopted in this study. The two-compartment
model is not important for clinical dosage regimens, as shown by the method of SAWCHUK-

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Table 3. The relationship between MIC of ITCZ against clinical isolates and clinical effect.

ZASKE18) for minimization of blood loss is critical. In this study, CL of ITCZ was adjusted for age.
CL is the most important factor in determining the daily dose of anti-fungal agents. The results of
WKHERRWVWUDSDQDO\VLVFRQ¿UPHGWKHUREXVWQHVVRIWKH¿QDOSDUDPHWHUHVWLPDWHVDQGWKHVWDQGDUGHUURUV IURP WKH FRYDULDQFH VWHS 7KH SRSXODWLRQ SDUDPHWHU HVWLPDWHV REWDLQHG IURP WKH ¿QDO
model and mean of the bootstrap replicates are very similar, and the standard errors were also
comparable. Therefore, a linear one-compartment model was population pharmacokinetic analyVLVRI,7&=EHFDXVHQRELDVZDVREVHUYHGLQWKHJRRGQHVVRI¿WSORWVREWDLQHGXVLQJ¿QDOPRGHO
7KHLPSRUWDQFHRIWKH$8&0,&SDUDPHWHUKDVEHHQFRQ¿UPHGRQERWKÀXFRQD]ROHDQGD
new triazole, ravuconazole4,8). These observations suggest that pharmacodynamic parameters asVRFLDWHGZLWKHI¿FDF\DUHVLPLODUZLWKLQWKHD]ROHFODVVDQWLIXQJDODJHQWVDVKDVEHHQGHVFULEHG
for various antibacterials. Thus, the rate and extent of fungal killing depends upon drug troughconcentration with these agents. This is very important and useful for dosing strategy to achieve
the highest possible dose without causing toxicity. However, the time-course of blood concentration and MIC of an antifungal agent against the infecting fungus actually exhibit different distri-June 2013

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167（ 27 ）butions depending on the individual case.
We calculated by PPK of AUC/MIC and Cmax/MIC, %t＞MIC, trough/MIC, PK-PD theory,
but we could not get a cut off value. In the future, there is a pressing need for antifungal therapies
to consider factors such as the risk of breakthrough fungal infections and breakpoints for antifungal agents based on PK-PD analyses.
According to document M27-S3 from the Clinical and Laboratory Standards Institute, aguideline widely used for MIC breakpoints of antifungal agents, the breakpoints for ITCZ are:
侑0.125 μg/mL, susceptibility (S); 0.25–0.5 μg/mL, susceptibility-dose/delivery dependent (SDD); and 侒1 μg/mL, resistance (R). In our study, however, an MIC of 4 μg/mL was observed in
non-responders, whereas an MIC of 2 μg/mL was observed in both responders and non-responders (Table 3). We also retrospectively reported the association of both antifungal susceptibility
MXGJHGE\&/6,EUHDNSRLQWVDQGFOLQLFDOHI¿FDF\LQSDWLHQWVZLWKLQYDVLYHIXQJDOSHULWRQLWLV
treated by injectable ITCZ. Clinical success and failure were obtained in cases of ITCZ MIC≦1 ȝg/mL and ≧4 ȝg/mL, respectively. We conclude we should re-consider CLSI breakpoints on
ITCZ9,19). In this results, we supported our study. Since the antifungal effects of azole antifungal
agents are dependent on MIC, the relationship between MIC and clinical effect was also investigated. MIC values were 0.125–2 for responders (n＝13), compared with 2–4 for non-responders(n＝3) (Table 3). Analysis of the relationship between MIC and clinical effect shows that, under
WKH0,&RIHI¿FDF\UDWHZDVDSSUR[LPDWHO\)RXUSDWLHQWVVKRZHG0,&VRIμg/mL. ThisUHVXOW LV FRPSDUDEOH ZLWK WKH FOLQLFDO HI¿FDF\ RI   RI  SDWLHQWV  REWDLQHG DJDLQVW
Candida spp. LVRODWHG IURP SHULWRQHDO ÀXLG VDPSOHV RI P\FRWLF SHULWRQLWLV SDWLHQWV UHFHLYLQJITCZ at 200 mg/day.
Based on our results, breakpoints for ITCZ should be considerded to: 侑1 μg/mL, S; 2 μg/mL,
S-DD; and 侒4 μg/mL, R. We will re-analyze PK-PD by this PPK for getting an appropriate
breakpoints.
Funding
This work was supported by Aichi Medical University Graduate School of Medicine.
Transparency declarations
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this article.

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