• What defines a next-generation biomarker, and how are advances in multi-omics, imaging, liquid biopsies, single-cell sequencing, and spatial biology reshaping biomarker discovery?

• How can artificial intelligence and machine learning be used to integrate and interpret high-dimensional biological data to uncover meaningful disease signatures?

• What are the biggest challenges in translating complex biomarker datasets into actionable clinical insights, and how can organisations overcome them?

• How can next-generation biomarkers improve patient stratification, target identification, and clinical trial success across different therapeutic areas?

• What infrastructure, data quality standards, and cross-functional collaborations are required to realise the full potential of AI-driven biomarker discovery?