Study start-up timelines have been increasing at a rapid rate. This session looks at underlying factors contributing to longer start-up durations and presents new data characterizing the inefficient process translating clinical trial protocols and related information into template source documents, study plans, and support materials. Implications of the results and opportunities and solutions to improve start-up efficiency, speed, and quality will be discussed.

Sponsored by: The Moveable Middle: Turning 'Maybe' Patients into Reliable Enrollment 

Most feasibility models treat patients as either in or out, willing or not. In practice, the largest group sits between: patients who say "possibly, depending on the details," conditionally willing but ultimately decisive for whether a site hits its enrollment targets. This session focuses on that moveable middle: Who they are, what actually moves them, and why standard feasibility data has no way to see them. Using an AI-powered, behavioral science-designed research engine that pairs quantitative scale with the intuition of a skilled qualitative interviewer, we'll show how behavioral evidence identifies the specific barriers holding conditionally-willing patients back, and what it takes to convert them. Drawing on a real clinical trial protocol as a case study, we'll walk through how this approach quantified the moveable middle, surfaced the protocol elements driving hesitation within it, and translated into concrete, actionable changes in site strategy and patient outreach.