From Protocol Draft to Confident Feasibility: Democratizing Study Design with AI

Clinical feasibility is evolving. Instead of validating assumptions after a protocol is written, leading teams are embedding feasibility earlier—using real-world data and AI to iteratively pressure-test eligibility criteria, optimize study design, and build more recruitable protocols. In this session, TriNetX and Parexel share a modern feasibility workflow designed for clinical operations teams, including non-medical users empowered through natural language and AI translation. You’ll see how protocol criteria can be translated into executable queries, how “what-if” iteration improves protocol quality, and how feasibility insights can inform site and country strategies—faster and with more confidence.

Speakers