Speakers
Christoph Hornik, MD, PhD, MPH
Duke Clinical Research Institute
Moulik Shah
Founder and CEO
Maxis AI
Keywords
Agentic AI; Clinical Research; Clinical Trials; Chatbot; AI Training
Key Points
- Project Loom is a proof-of-concept study aimed at evaluating agentic artificial intelligence (AI) workflows end-to-end. The research team utilized pre-built agents with specific roles: writer, reviewer, builder, recruiter, and reporter. The agents were assembled on one platform to execute the trial. Human oversight took place at each step.
- The agents were successful in 4 out of 5 operational domains and completed the work in 182 working hours. The presenters outlined several changes that they are making in response to failures in eligibility screening, chatbot hand-offs, and others.
- The presenters concluded that end-to-end agentic AI execution is feasible and fast. This technology is meant to empower researchers and expedite their work, not to replace them. Training and testing of AI agents and workflows will be critical.
Discussion Themes
Document drafting, case report form generation, and backend data extraction are considered ready for live use today under human review. Direct participant-facing interactions and patient safety monitoring are viewed as the highest-risk areas requiring further refinement and testing.
The platform operates within institutional firewalls using strict role-based access control, bounded scopes of execution, and an observability layer that tracks every computation and handoff.
Resolving the EHR identification and screening issues is technically feasible by profiling unstructured clinical text alongside structured data and extending formal handoff contracts to third-party tools.
The term "Project" signifies that the system is an evolving, iterative initiative rather than a static commercial product.