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Transforming clinical trials: the emerging roles of large language models

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 application...

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Detalles Bibliográficos
Autores principales: Ghim, Jong-Lyul, Ahn, Sangzin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Clinical Pharmacology and Therapeutics 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10551746/
https://www.ncbi.nlm.nih.gov/pubmed/37810626
http://dx.doi.org/10.12793/tcp.2023.31.e16
Descripción
Sumario: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.