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KMID : 1038020230310030131
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Translational and Clinical Pharmacology
2023 Volume.31 No. 3 p.131 ~ p.138
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ransforming clinical trials: the emerging roles of large language models
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Ghim Jong-Lyul
Ahn Sang-Zin
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Abstract
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Clinical trials are essential for medical research, but they often face challenges in matching patients to trials and planning. Large language models (LLMs) offer a promising solution, signaling a transformative shift in the field of clinical trials. This review explores the multifaceted applications of LLMs within clinical trials, focusing on five main areas expected to be implemented in the near future: enhancing patient-trial matching, streamlining clinical trial planning, analyzing free text narratives for coding and classification, assisting in technical writing tasks, and providing cognizant consent via LLM-powered chatbots. While the application of LLMs is promising, it poses challenges such as accuracy validation and legal concerns. The convergence of LLMs with clinical trials has the potential to revolutionize the efficiency of clinical trials, paving the way for innovative methodologies and enhancing patient engagement. However, this development requires careful consideration and investment to overcome potential hurdles.
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KEYWORD
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Clinical Trial, Natural Language Processing, Artificial Intelligence, Informed Consent, Medical Writing
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FullTexts / Linksout information
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Listed journal information
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