Artificial intelligence (AI) is rapidly transforming clinical development, helping biopharma organizations address growing pressures to deliver studies faster, improve efficiency, and reduce costs while maintaining regulatory quality. While hundreds of AI use cases have emerged across the drug development lifecycle, only a subset is delivering measurable business value and return on investment.

In this webinar, Cytel experts will explore AI applications delivering tangible impact across biometrics and R&D, from data management and document automation to statistical programming. They will also examine the emerging challenge of AI inference economics, as advanced reasoning models significantly increase token consumption and the cost of scaling AI.

Key Topics 

• Current state of AI for clinical development — where AI is generating tangible ROI across biometrics and clinical development today
• Why inference costs and token efficiency matter for organizations seeking to scale AI sustainably
• A hybrid AI framework for automated SDTM, ADaM, and Tables, Listings, and Figures (TLFs) generation, designed specifically for regulated clinical programming
• How token-efficient AI frameworks can enable scalable, auditable, and economically sustainable clinical programming
• The potential evolution from independent double programming toward a model of clinical programmer–AI collaboration

Speakers

• Manuel Cossio – Director, Head of AI Solutions, Real-World Evidence, Value, and Access
• Nicolas Rouillé– Vice President, Applied AI, Biometrics