Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease, both at the clinical and biological level. However, COPD is still diagnosed and treated according to simple clinical measures (level of airflow limitation, symptoms, and frequency of previous exacerbations). To address this clinical and biological complexity and to move towards precision medicine in COPD, we need to integrate (bioinformatics) and interpret (clinical science) the vast amount of high-throughput information that existing technology provides (systems biology and network medicine) so diagnosis, stratification, and treatment of patients with COPD can occur on the basis of their pathobiological mechanism (ie, endotypes). Therefore, this Series paper discusses a possible new taxonomy of COPD, the role of endotypes and associated biomarkers and phenotypes, the gaps (and opportunities) in existing knowledge of COPD pathobiology, how systems biology and network medicine can improve understanding of the disease and help to identify relevant endotypes and their specific biomarkers, and how endotypes and their biomarkers can improve the precision, effectiveness, and safety of the treatment of patients with COPD.