Severe-asthma biologic switching is exposing the eosinophil-driven phenotyping gap

Reading the signal

Severe asthma is treated by a panel of biologics targeting different points in the type-2 inflammation pathway: anti-IgE (omalizumab), anti-IL-5 and anti-IL-5R (mepolizumab, reslizumab, benralizumab), anti-IL-4R (dupilumab), anti-TSLP (tezepelumab). The class has been positioned in commercial conversations using simple cutoffs (eosinophil count, FeNO, IgE level) to define eligible patient populations.

Real-world switching data is showing the cutoffs are too simple:

• Patients with low blood eosinophils sometimes respond to anti-IL-5 agents because tissue eosinophil burden is not always reflected in blood counts
• Patients with high blood eosinophils sometimes fail anti-IL-5 because their disease has a non-eosinophil-driven component
• Mixed type-2-low and type-2-high phenotypes are common and are not well-served by the existing class positioning
• Tezepelumab, with its upstream mechanism, performs in patient profiles where the downstream class fails, and the patient identification for tezepelumab is not well-defined by any simple cutoff

The phenotype work to refine these patterns is now active in the field, with novel biomarkers (sputum eosinophils, exhaled nitric oxide, periostin, TSLP-pathway biomarkers) being evaluated as candidates to refine eligible-population definition.

Commercial implications

For sponsors of severe-asthma biologics in commercial life or in development:

1. Cutoff-based positioning is increasingly inadequate. The commercial conversation has to move beyond "eosinophil-high" or "eosinophil-low" to phenotype-stratified positioning that reflects the real biology.
2. Real-world cohort generation is decisive. Real-world cohorts that capture phenotype granularity (sputum eosinophils, FeNO trajectory, exacerbation history) are the asset that lets a sponsor defend a particular asset's positioning across patient profiles.
3. The next-generation pipeline design has to build on the more granular phenotype frame. Pipeline assets designed to a binary eosinophil cutoff face commercial friction the moment the field moves to a more granular frame.

What we are watching

• Phenotype-refinement work moving from research-grade biomarkers into routine clinical use
• Real-world cohort data on switching and what it tells us about which patient profile matches which biologic
• Late-stage pipeline assets with novel mechanisms (anti-CRTH2, JAK in respiratory, novel TSLP-pathway agents) and whether they are being designed to a more granular phenotype frame