Model-Based Drug Development in Pulmonary Delivery: Pharmacokinetic Analysis of Novel Drug Candidates for Treatment of Pseudomonas aeruginosa Lung Infection

摘要

Antibiotic resistance is a major public health threat worldwide. In particular, about 80% of cystic fibrosis patients have chronic Pseudomonas aeruginosa (PA) lung infection resistant to many current antibiotics. We are therefore developing a novel class of antivirulence agents, quorum sensing inhibitors (QSIs), which inhibit biofilm formation and sensitize PA to antibiotic treatments. For respiratory conditions, targeted delivery to the lung could achieve higher local concentrations with reduced risk of adverse systemic events. In this study, we report the pharmacokinetics of 3 prototype QSIs after pulmonary delivery, and the simultaneous analysis of the drug concentration-time profiles from bronchoalveolar lavage, lung homogenate and plasma samples, using a pharmacometric modeling approach. In addition to facilitating the direct comparison and selection of drug candidates, the developed model was used for dosing simulation studies to predict in vivo exposure following different dosing scenarios. The results show that systemic clearance has limited impact on local drug exposure in the lung after pulmonary delivery. Therefore, we suggest that novel QSIs designed for pulmonary delivery as targeted treatments for respiratory conditions should ideally have a long residence time in the lung for local efficacy with rapid clearance after systemic absorption for reduced risk of systemic adverse events.