Beyond Automation: Transforming Clinical Trial Delivery Through Structured Information, Human Expertise, And Intelligent Workflows

Two decades of standardization, configurable platforms, and automation have not removed the weeks or months that study startup often takes.

This paper locates the bottleneck in information flow: protocol intent is translated again and again, and each translation invites rework, inconsistency, and downstream risk. It argues for treating the protocol as a structured knowledge asset rather than a static document, and for redesigning workflows around that shift. Along the way, it covers an RTSM requirements example the authors caution is a proof point and not a universal benchmark, the lifecycle stages where AI applies, a five-level maturity model, and the governance that makes scale credible. It also includes an executive perspective from Nagaraja Srivatsan, CEO of Endpoint Clinical.

Read the paper to see where your own workflows repeat the same interpretation.