Chronic Pseudomonas aeruginosa lung infections in cystic fibrosis (CF) represent one of the most treatment-refractory bacterial diseases, sustained by biofilm formation, metabolic dormancy, and adaptive antibiotic resistance evolution. While bacteriophage (phage) therapy has emerged as a promising alternative for multidrug-resistant (MDR) pathogens, clinical studies in CF have demonstrated transient reductions in bacterial burden without achieving complete eradication. This review integrates molecular, evolutionary, and immunological findings to explain the multifactorial barriers that limit phage therapeutic efficacy in chronic CF infections. We highlight three major obstacles: (i) bacterial dormancy and persistence within biofilms that restrict phage adsorption and replication; (ii) hypermutability and extensive genotypic diversification of CF-adapted P. aeruginosa, which accelerate phage resistance evolution and necessitate broad host-range coverage; and (iii) CF-specific immune constraints-including a dysfunctional innate immune system and phage-neutralizing humoral immunity-that reduce phage bioavailability and undermine sustained bacterial clearance. Emerging strategies to overcome these challenges include the discovery of dormant-targeting phages capable of replicating in metabolically quiescent cells, evolution-informed phage training to delay resistance evolution, and synthetic phage engineering approaches designed to disrupt biofilms and expand host-range coverage. In parallel, computational or artificial intelligence (AI)-guided frameworks for phage cocktail design and cystic fibrosis transmembrane conductance regulator (CFTR) modulator-mediated restoration of host immune function together offer a more integrated therapeutic paradigm that unites phage biology and host immune context. By unifying clinical outcomes with mechanistic, evolutionary, and immunological perspectives, this review outlines a next-generation framework for phage therapy in CF aimed at achieving more durable therapeutic outcomes.
Hwang et al. (Tue,) studied this question.