Generative AI in Clinical Trials: “Applications in Protocol Design, Data Management and Medical Writing”

Abstract

Generative artificial intelligence (Gen AI), especially large language models (LLMs), is increasingly being examined to improve the efficiency of clinical trials. Clinical trials include complex tasks such as protocol development, data management, documentation and medical writing. This review examines the developing applications of Gen AI and LLMs in clinical trials, with a primary focus on protocol design, data management, and medical writing. In protocol design, Gen AI can support protocol drafting, optimization, development of eligibility criteria and assessment of trial characteristics. In data management, artificial intelligence (AI) can help with data cleaning, processing, coding, identification of inconsistencies and automation of routine processes. Gen AI also supports medical writing through literature review, summarization, document drafting, data analysis and preparation of clinical and regulatory documentation. These applications supports the clinical trials by processing the complex clinical information to decrease the workload, improve efficiency. Although they cause limitations like hallucinations, inaccurate outputs, algorithmic bias, limited generalizability, data privacy and security risks, and over dependence on AI generated information. Regulatory and ethical considerations, including accountability, audit trails, data protection, and validation, are also essential. Overall, Gen AI can support clinical trial tasks, but it should remain as an assistive technology with appropriate human oversight, professional review, validation and adherence to regulatory and ethical requirements.