Study startup remains one of the most persistent bottlenecks in clinical development, with timelines driven by document assembly, site qualification, budget and contract negotiation, and regulatory submission preparation — all document-heavy, repetitive, and slow. This session maps AI capability against each stage of the startup lifecycle, distinguishing between mature applications available today and those still aspirational. We'll cover feasibility and site identification, protocol summarization for site-facing materials, essential document review and completeness checks, budget benchmarking, contract turnaround, and translation workflows for multi-country trials. Presenters will share measured results, including where cycle time actually improved and where the overhead of validation and review consumed the savings.

Takeaways

• Map AI use cases to specific study startup activities and their existing bottlenecks
• Distinguish proven applications from vendor claims still under development
• Establish baseline metrics so you can prove — or disprove — cycle time improvement