This research demonstrates how Retrieval-Augmented Generation (RAG) can transform the creation of complex clinical trial documents, reducing time and costs while maintaining quality.

• Improved efficiency and consistency in drafting clinical trial protocols and related documents
• LLM-generated documents passed expert review and met regulatory standards
• Implementation reduced document creation time by up to 70% compared to traditional methods
• Established a framework for validation that ensures AI-generated content meets medical and ethical requirements

This breakthrough has significant implications for pharmaceutical research, potentially accelerating the clinical trial process while maintaining scientific rigor and regulatory compliance.

From RAGs to riches: Utilizing large language models to write documents for clinical trials