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Clinical Trial
. 2012 Jan;68(1):39-53.
doi: 10.1007/s00228-011-1095-3. Epub 2011 Jul 28.

Optimal Dose Finding of Garenoxacin Based on Population Pharmacokinetics/Pharmacodynamics and Monte Carlo Simulation

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Free PMC article
Clinical Trial

Optimal Dose Finding of Garenoxacin Based on Population Pharmacokinetics/Pharmacodynamics and Monte Carlo Simulation

Yusuke Tanigawara et al. Eur J Clin Pharmacol. .
Free PMC article

Abstract

Purpose: Garenoxacin, a novel des-F(6)-quinolone, possesses potent antibacterial activity against infectious pathogens in the respiratory tract. Population pharmacokinetic/pharmacodynamic (PK/PD) modeling and Monte Carlo simulations were used to optimize garenoxacin dosage regimens.

Methods: At the end of phase II stage, the clinical dose of garenoxacin was predicted to be 400 mg once daily by the interim PK/PD analysis using phase I and phase II clinical data. The criteria used to determine an optimal dose were (1) the target attainment of the area under the unbound concentration-time curve divided by the minimum inhibitory concentration (fAUC₀₋₂₄/MIC ratio) and (2) the maintenance of a trough concentration above the mutant prevention concentration. In a confirmatory phase III study, garenoxacin was administered 400 mg once daily to 136 patients infected with mild or moderate chronic respiratory diseases.

Results: Logistic regression analysis showed that fAUC₀₋₂₄/MIC ratio was a significant variable that predicted clinical response (p = 0.0164). Of all subjects, 92.4% reached the target value of fAUC₀₋₂₄/MIC ratio > 30 h, and the clinical efficacy rate of this population was 91.8%. On the other hand, there was no significant relationship between exposure values (AUC₀₋₂₄ and maximum concentration) and the incidence of adverse events by the Mann-Whitney test.

Conclusions: The antimicrobial efficacy of the actual phase III study was consistent with the expectation from the Monte Carlo PD simulation. We were able to show that the optimal garenoxacin dosage regimens were successfully determined using prospective population PK/PD analysis and clinical trial simulations.

Figures

Fig. 1
Fig. 1
Plasma garenoxacin concentration versus time profile. Plotted symbols show the observed concentration data, and the lines show the results of visual predictive checks. For simulated data, the 5th, 50th, and 95th percentiles (from bottom to top) of the final model simulated data are displayed; for real data, the 5th, 50th, and 95th percentiles (from bottom to top) of the observed concentrations are displayed. These percentiles were set for the 400 mg dose, which is clinical standard dose
Fig. 2
Fig. 2
Influence of the covariates (renal function and body weight) on the plasma concentration–time curve from 0 to 24 h (AUC0−24) and peak plasma concentration (Cmax). Exposure values (AUC0−24 and Cmax) were simulated by the population mean parameters of the final model using the characteristics of 237 subjects. The simulation was made by varying one covariate within the particular range while all other covariates were kept at their mean value. CLCR Creatinine clearance
Fig. 3
Fig. 3
Monte Carlo simulation for reaching the target attainment [unbound AUC/minimum inhibitory concentration ratio (fAUC0−24/MIC) > 30 h] with various doses. Steady-state AUC0−24 was calculated using the interim population pharmacokinetics parameters of Model 2 in Table 3. The creatinine clearance was randomly simulated from the observed distribution of the patients real values (34.4−133.2 ml/min, n = 55). The AUC0−24 and MIC values were simulated for 10,000 putative cases to generate the fAUC0−24/MIC distribution for each pathogen. MSSA, MRSA Methicillin-sensitive and methicillin-resistant Staphylococcus aureus, PSSP, PISP, PRSP penicillin-sensitive, intermediately resistant, and highly resistance, respectively, strains of Streptococcus pneumoniae, VRE vancomycin-resistant enterococci, CIP ciprofloxacin
Fig. 4
Fig. 4
Monte Carlo simulation for reaching target mutant prevention concentration (MPC; 1 μg/ml) with various doses. Trough concentration was calculated using the interim population pharmacokinetics parameters of Model 2 in Table 3 and patient covariates randomly re-sampled from real CLCR values (34.4–133.2 ml/min, n = 55). Trough concentration was simulated for 1,000 putative cases, and the probability of reaching above MPC was calculated for various garenoxacin dosing regimens (doses of 100, 200, 250, 300, 350, 400, and 600 mg). The typical MPC value was <1 μg/ml for S. aureus, S. pneumoniae, and H. influenzae, including resistant strains
Fig. 5
Fig. 5
Logistic regression analysis of efficacy against all pathogens for the relationship between log fAUC0−24/MIC and clinical efficacy rate. Circles Split for fAUC0−24/MIC of garenoxacin as determined by the classification and regression tree (CART) analysis
Fig. 6
Fig. 6
Relationships between drug exposure values and the incidence of adverse events in 133 patients. AUC0−24 (left panel) and Cmax (right panel) of garenoxacin were obtained from each subject who received 400 mg dose

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