Matching PBPK and NONMEM pharmacokinetics descriptions to understand and extrapolate - case study ciprofloxacin
S. Saleh(1), H. Staß(1), G. Ahr(1), R. Burghaus(1)
(1)Bayer Schering Pharma AG, Wuppertal, Germany.
Objectives: Ciprofloxacin is a member of the fluoroquinolone class of antibiotics. Ciprofloxacin is active against both Gram-positive and Gram-negative bacteria drug and it is first choice in the treatment of presumed or confirmed pneumonia secondary to Streptococcus pneumonia. Ciprofloxacin is applied to proven uncomplicated and complicated urinary tract infections. Being more than 20 years on the market available knowledge of ciprofloxacin was combined as a case study to elucidate the potential of PK modeling and simulation for the use in clinical development and PK/PD analysis.
Method: Data for approved oral, intravenous application and inhalation route were matched from several sources of clinical and preclinical studies. The basic techniques of NCA as well as compartmental analysis were complemented by population analysis in healthy volunteers as well as in patients. Basic understanding of model mechanism was collected regarding the oral absorption, systemic distribution as well as metabolic and excretory elimination. The descriptive view achieved by retrospective analysis described the data well and allowed suitable predictions (e.g. pediatrics). PB/PK was applied to better understand the physiological and pathophysiological behavior and to get knowledge about the drug exposure at the site of infection. Not only distribution to organs but also accumulation due to the presence of incorporating cells could be described.
Results: Applying PK knowledge from different evaluation and simulation tools joint perspective powerful instrument to predict therapeutic efficacy. The quantification of these processes led to the understanding, interpretation and prediction of ciprofloxacin plasma concentration-time profiles. The possibility to predict tissue concentration enabled model-based PK/PD predictions for populations of interest which can not covered by available clinical data.
Conclusion: When appropriate workflows can be established the different methods from the toolbox of pharmacokinetics complement retrospective analysis, physiological understanding and prospective simulations.