Asthma is a heterogeneous chronic respiratory disease driven by diverse inflammatory pathways that vary across patients. The recognition of distinct molecular endotypes has led to the development of targeted biologic therapies that have transformed the management of moderate-to-severe asthma. However, selecting the most appropriate biologic therapy for each patient remains challenging. Health providers often rely on trial-and-error approaches that may delay disease control, increase costs, and expose patients to unnecessary side effects. Biomarkers are key to precision asthma care, as they provide objective measures of underlying disease mechanisms. Established biomarkers such as blood eosinophil count, fractional exhaled nitric oxide, and serum total immunoglobulin E are important for identifying type 2-high asthma. Sputum biomarkers offer direct insight into airway inflammation, but their use is limited by technical complexity and availability across centers. Emerging biomarkers, including proteomic, transcriptomic, metabolomic, and genomic biomarkers, show promise in further refining biologic therapy selection. In addition, digital biomarkers derived from electronic health records, wearable devices, and artificial intelligence-based algorithms offer new opportunities to capture real-world changes in disease and treatment response. Non-medical drivers of health, particularly socioeconomic factors, are increasingly recognized as modifiers of biologic effectiveness and may also be helpful in selecting biologic therapies. This review summarizes the existing evidence on established and emerging biomarkers used to guide biologic therapy selection in asthma. Integrating multiple biomarkers will be essential to improve biological selection, monitor response, and ultimately achieve the goal of remission in asthma.
Chiarella et al. (Wed,) studied this question.