COPD (chronic obstructive pulmonary disease) is a heterogeneous disease associated with significant morbidity and mortality. Current diagnostic criteria based on the presence of fixed airflow obstruction and symptoms do not integrate the complex pathological changes occurring within lung, do not define different airway inflammatory patterns, nor do they define different physiological changes or differences in structure as can be defined by imaging. Over recent years, there has been interest in describing this heterogeneity and using this information to subgroup patients into COPD phenotypes. Most approaches to phenotyping have considered disease at a single scale and have not integrated information from different scales (e.g. organ–whole person, tissue–organ, cell–tissue and gene–cell) of disease to provide multi-dimensional phenotypes. Integration of disease biology with clinical expression is critical to improve understanding of this disease. When combined with biostatistical modelling, this information may lead to identification of new drug targets, new end points for clinical trials and targeted treatment for subgroups of COPD patients. It is hoped this will ultimately improve COPD outcomes and represent a move towards personalised medicine. In the present review, we will consider these aspects of multi-dimensional phenotyping in more detail.