Chronic respiratory infection is the primary driver of mortality in individuals with cystic fibrosis (CF). Existing drug screening models utilised in preclinical antimicrobial development are unable to mimic the complex CF respiratory environment. Consequently, antimicrobials showing promising activity in preclinical models often fail to translate through to clinical efficacy in people with CF. Model systems used in CF anti-infective drug discovery and development range from antimicrobial susceptibility testing in nutrient broth, through to 2D and 3D in vitro tissue culture systems and in vivo models. No single model fully recapitulates every key aspect of the CF lung. To improve the outcomes of people with CF (PwCF) it is necessary to develop a set of preclinical models that collectively recapitulate the CF respiratory environment to a high degree of accuracy. Models must be validated for their ability to mimic aspects of the CF lung and associated lung infection, through evaluation of biomarkers that can also be assessed following treatment in the clinic. This will give preclinical models greater predictive power for identification of antimicrobials with clinical efficacy. The landscape of CF is changing, with the advent of modulator therapies that correct the function of the CFTR protein, while antivirulence drugs and phage therapy are emerging alternative treatments to chronic infection. This review discusses the challenges faced in current antimicrobial development pipelines, including the advantages and disadvantages of current preclinical models and the impact of emerging treatments.
Keywords: Pseudomonas aeruginosa; antimicrobial development; cystic fibrosis; host-pathogen interactions; infection models; therapeutics.