Accelerating Recruitment Efforts in a Complex Small Cell Lung Cancer Study

Key Takeaways

• Recruitment barriers in Phase II SCLC were linked to complexity and limited visibility into where eligible patients were being treated.
• Real-world data enabled quantification of addressable patient pools and refined feasibility assumptions beyond traditional site outreach.
• Natural language processing supported more granular eligibility matching by extracting clinically relevant variables from unstructured data.
• Optimized site and patient selection concentrated resources on higher-probability enrollment pathways to accelerate recruitment timelines.