Chronic inflammatory pulmonary diseases such as COPD and asthma are highly prevalent and associated with a major health burden worldwide. Despite a wealth of biologic and clinical information on normal and pathologic airway structure and function, the primary causes and mechanisms of disease remain to a large extent unknown, preventing the development of more efficient diagnosis and treatment. We propose to overcome these limitations through an integrative systems biology research strategy designed to identify the functional and regulatory pathways that play central roles in respiratory pathophysiology, starting with severe asthma. This approach relies on global genome, transcriptome, proteome, and metabolome data sets collected in cross-sectional patient cohorts with high-throughput measurement platforms and integrated with biologic and clinical data to inform predictive multiscale models ranging from the molecular to the organ levels. Working hypotheses formulated on the mechanisms and pathways involved in various disease states are tested through perturbation experiments using model simulation combined with targeted and global technologies in cellular and animal models. The responses observed are compared with those predicted by the initial models, which are refined to account better for the results. Novel perturbation experiments are designed and tested both computationally and experimentally to arbitrate between competing hypotheses. The process is iterated until the derived knowledge allows a better classification and subphenotyping of severe asthma using complex biomarkers, which will facilitate the development of novel diagnostic and therapeutic interventions targeting multiple components of the molecular and cellular pathways involved. This can be tested and validated in prospective clinical trials.