Optimal dose finding of garenoxacin based on population pharmacokinetics/pharmacodynamics and Monte Carlo simulation

Yusuke Tanigawara, Kenji Nozawa, Hisatsugu Tsuda

研究成果: Article査読

17 被引用数 (Scopus)


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 (fAUC 0-24/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 fAUC 0-24/MIC ratio was a significant variable that predicted clinical response (p∈=∈0.0164). Of all subjects, 92.4% reached the target value of fAUC 0-24/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 (AUC 0-24 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.

ジャーナルEuropean Journal of Clinical Pharmacology
出版ステータスPublished - 2012 1

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)

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