Clinical Trials Protocol Authoring using LLMs
Morteza Maleki, SeyedAli Ghahari

TL;DR
This paper explores the use of GPT-4, a generative AI model, to automate and improve the development of clinical trial protocols, demonstrating enhanced efficiency and accuracy in protocol authoring.
Contribution
It introduces a novel methodology for integrating GPT-4 into clinical trial protocol development, addressing challenges in model selection and prompt engineering.
Findings
Increased efficiency in protocol creation
Enhanced accuracy and customization of protocols
Systematic handling of model and prompt challenges
Abstract
This report embarks on a mission to revolutionize clinical trial protocol development through the integration of advanced AI technologies. With a focus on leveraging the capabilities of generative AI, specifically GPT-4, this initiative aimed to streamline and enhance the efficiency and accuracy of clinical trial protocols. The methodology encompassed a detailed analysis and preparation of comprehensive drug and study level metadata, followed by the deployment of GPT-4 for automated protocol section generation. Results demonstrated a significant improvement in protocol authoring, highlighted by increases in efficiency, accuracy, and the customization of protocols to specific trial requirements. Challenges encountered during model selection and prompt engineering were systematically addressed, leading to refined methodologies that capitalized on the advanced text generation capabilities…
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Taxonomy
TopicsScientific Computing and Data Management · Semantic Web and Ontologies · Biomedical Text Mining and Ontologies
