关键词: 大语言模型, 临床研发, 临床运营, 生物医药

Abstract:

In the modern medical field， enhancing clinical research and operational efficiency is crucial for accelerating drug development and reducing research and development （R&D） costs. Technological advancements in artificial intelligence are profoundly changing the traditional models of pharmaceutical R&D， with large language models， in particular， providing unprecedented support for this process. This study delves into the application of large language models in clinical R&D， including optimizing clinical trial design， enhancing clinical trial management， addressing patient-centered considerations， improving data processing efficiency， and accelerating drug approval and regulation. By leveraging natural language processing and machine learning technologies， tasks such as filling out case report forms and generating regulatory documents have been automated. This not only reduces the burden on teams but also expedites the entire drug development process from research to market， improving the efficiency of clinical trial studies. However， implementing these advanced high-tech solutions still faces challenges， such as privacy protection for patients and the complexity of implementing technologies. Therefore， the study proposes that the promotion of large language model applications in drug clinical R&D should be based on effective communication with regulatory authorities， guided by project outcomes， business needs， and patient welfare， providing valuable insights for the future application of large language models in drug clinical research and development.

Key words:  , Large language models； , Clinical research and development； , Clinical operation； , Biopharmaceuticals