AI- and ML-Driven Analysis of Site Performance in Clinical Trials

About this session

I'll share how AI and ML can enhance clinical trial site selection through a transparent, data-driven framework that evolves with every stage of the process. Topics covered include: Multi-source data integration: AI harmonises internal, external, commercial, clinical, real-world, and ad hoc data into a unified analytical catalogue; Interpretable modelling: Glass-box models, not black boxes, transparently rank sites, enabling stakeholders to understand and trust the outputs; Iterative refinement: Feasibility outreach data is fed back into the model, dynamically updating site rankings; and Actionable insights: Bridging predictive analytics with ground-truth site intelligence for better-informed decisions.

Speaker

• CM

  Clara Cali Mella

  Data Strategy Lead · Bayer AG

  Speaker