The lungs of patients with Cystic Fibrosis (CF) are often chronically colonised by a plethora of microbial species, including the major CF pathogen Pseudomonas aeruginosa (P. aeruginosa). Herewith, when examining recalcitrant bacterial infections in CF, it is imperative to not only study pathogens in isolation, but rather, as part of ecological communities interacting at the species level. The successful invasion and robust virulence mechanisms of P. aeruginosa are influenced by members of the lung microbiome. Interspecies interactions can shape and often determine virulence evolution, mediated through synergistic and antagonistic behaviours. Moreover, species richness and composition act in concert to impact P. aeruginosa colonisation and may predict important clinical phenotypes – yet it is difficult in practice to tease apart the effects of diversity per se versus increased likelihood of encountering a key species at higher diversities. We use ecological framework to disentangle the effects that community richness and community composition have on colonisation resistance in the CF airways, and dissect how polymicrobial interactions shape P. aeruginosa virulence. By implementing a modified random partition design, we were able to identify members of an artificially assembled microbial community that affect P. aeruginosa invasion and virulence-associated secretions such as pyoverdine and pyocyanin. This work provides a novel way of understanding microbial interactions in a clinical context, by applying an ecological framework to artificially assembled communities. This will pave the way for future work applying this framework to more “natural” CF microbial assemblages that closely reflect different clinical statuses of the CF lung.