Enabling efficient drug development of antibiotic therapy against multi-resistant pathogens: Establishment of a modelling framework for translating response from rabbits to patients

The overall purpose of this 4-year project is to develop a strategy enabling the clinical development of antimicrobial therapy against serious infections caused by multi-drug resistant (MDR) bacteria.

We will develop a model-based methodology that translates antibacterial efficacy information from a rabbit pulmonary infection model, recapitulating clinical disease progression, to patients with serious lung infections.

We anticipate that we can characterize the antibiotic effects, interplays between biomarkers and disease severity with mathematical models where parameters are scaled between species.

The approach will allow for a reduced number of patients in clinical trials investigating new treatments against difficult-to-treat pathogensWe will take on this challenge by developing a data-driven non-linear mixed effects modelling translational framework which will support outcome predictions relying on rabbit data and limited clinical study data.

In the development we will focus on ceftazidime-avibactam (CZA) treatment in pnemonia infections caused by carbapenem-resistant Klebsiella pneumoiae bacteria.

The framework will be evaluated on other treatments and difficult-to-treat pathogens and be applied to identify optimized dosing strategies for CZA in pneumonia.

Clinical trial simulations will be employed to explore the possibility to reduce the quantity of clinical efficacy data given various degree of exposure-response information from rabbit pulmonary infection studies.