Leveraging ChatGPT to Streamline Clinical Trial Data Administration: Balancing Efficiency with Ethical Responsibility
Year: 2025
Type: article
Abstract: Clinical trials are critical for advancing medical knowledge and developing new treatments, yet they often involve substantial administrative burdens that can impede progress and reduce efficiency. Effective clinical trial data management requires seamless participant engagement, accurate data collection, strict regulatory compliance, and coordinated efforts among multidisciplinary teams. These demands can strain resources and lead to workflow inefficiencies. This research paper explores the potential of large language models (LLMs), such as ChatGPT, to enhance clinical coordination by optimizing administrative processes in clinical trials. We assess the model's applications in streamlining standard operating procedures (SOPs), clinical data management, automating documentation, and supporting regulatory compliance. To ensure responsible implementation, we also examine key challenges related to ethical considerations, data biases, and safety concerns, while proposing strategies for mitigating these risks. Our findings indicate that integrating AI-driven solutions like ChatGPT can significantly improve operational efficiency, reduce administrative workloads, and allow clinical trial teams to dedicate more time to patient care and scientific inquiry. By leveraging AI responsibly, we can make clinical research more agile, adaptive, and focused on advancing medical innovation.
DOI: 10.47912/jscdm.438
Authors: Amrita Ghosh, Caroline J Huang
Institution: Stanford University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7083014400