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

How clinical operations teams are using natural language and Artificial Intelligence (AI) to accelerate clinical study site strategies

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

Amy Spaziani
Senior Director, Clinical Feasibility
Parexel

Jeffrey Brown, PhD
Chief Scientific Officer
TriNetX

Sierra Luciano
Director, Clinical Study Feasibility & Analytics
TriNetX