Disease heterogeneity as a barrier to reliable biomarker development in CNS therapeutics
10 Sept 2026
Biomarkers
- Biological diversity across patients complicates biomarker discovery, validation, and clinical translation, limiting reproducibility across studies.
- Integrating multimodal biomarkers (fluid, imaging, digital, and molecular) can improve patient stratification and better capture disease biology.
- Biomarkers should evolve throughout development, supporting target engagement, dose selection, proof-of-mechanism, patient enrichment, and disease monitoring from Phase I through pivotal trials.
- High-quality biospecimens and harmonized analytical workflows are essential for generating reproducible, regulatory-grade biomarker data.
- AI-driven data integration and longitudinal analyses offer new opportunities to identify disease subtypes and enable precision medicine approaches in CNS disorders.
