Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as the results of a complex interaction between various genetic, environmental and life-style factors. Several investigations in last years have been performed to better define such interactions but the identification of resulting phenotypes is still somewhat difficult, and may result in inadequate assessment and management of COPD (usually solely based on the severity of airflow-limitation (FEV1). In this new scenario, the management of COPD has been drove towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (including also advanced functional genomic-assay) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for new drugs development). Therefore, according to the emerging "systems/network medicine", COPD shall be framed considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively-characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized, and participatory ("P4-medicine"). It clearly emerges as in the next future, new opportunities could be provided for clinical research on rare COPD-patterns, and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SM-approaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.