Airways diseases are complex and difficult to treat due to the heterogeneity of their etiology. Treatment is typically based on clinical characteristics, and best treatment practices may not necessarily be beneficial for individual patients. Better stratification and timing of medical interventions is possible by adopting an approach that utilizes biological information and disease biomarkers. The identification of differences between patient groups holds potential to improve treatment. This thesis has two main aims: further developing methods that explore the use of biomarkers in (chronic) airway diseases, and exploring the feasibility and application of strategies to collect real-world evidence in patients with severe asthma. Current most well-known biomarkers in chronic airways diseases have predictive value for treatment response to corticosteroid drugs, but their use is limited. We explored the ability of exhaled breath measurement to detect recent exacerbations in COPD and asthma patients using electronic nose (eNose) devices. The studies showed that exhaled breath analysis could identify COPD and asthma patients who recently had an exacerbation with high accuracy, suggesting a possible role in monitoring. In the second part, we found differences between eligibility criteria for anti-IL5 drug trial participation and registry data of patients who started this therapy, however 50% of OCS-dependent patients were able to reduce their dose to ≤5 mg prednisone per day. Within the SHARP consortium we found a large variation in characteristics and lifestyle-associated factors in different severe asthma registries across Europe. Suggesting the severe asthma population and their treatment are heterogenous across Europe and diagnosis in clinical practice differs across countries.