Mechanism-based pharmacokinetic/pharmacodynamic modelling and meta-analysis to address challenges in antibiotic therapy for specific patient populations

The emergence of antibiotic-resistant bacteria is a major global challenge. Especially in patients with life-threating infections (e.g., critically ill patients with augmented renal clearance and patients with cystic fibrosis), the poor effectiveness of monotherapies has necessitated the use of combination antibiotic regimens to reduce risk of treatment failure. In this context, innovative approaches to maximise efficacy and minimise resistance emergence are essential. Thus, this thesis combines evidence from in vitro static and dynamic experiments, mechanism-based modelling, Monte Carlo simulations, and meta-analysis to provide insights into optimisation of antibiotic combination therapies that maximise bacterial killing and suppress the emergence of resistance.