摘要
Abstract
In recent years,the rapid development of artificial intelligence(AI)technology,particularly large language models(LLMs),has brought new opportunities and challenges to the field of drug regulation.This paper,based on the preliminary practices of the Center for Information,NMPA,explores the fundamental considerations for applying LLMs in drug regulation and proposes an integrated construction framework and practical pathways.The article first analyzes the importance of three foundational elements:data,computing power,and algorithms,emphasizing the critical roles of data quality,computing cost,and algorithm suitability in model applications.Next,it proposes an integrated construction framework,suggesting collaborative efforts between national and provincial drug regulatory authorities to build a unified and scalable LLM application system that avoids redundant construction and resource waste.Finally,through a case study on the intelligent review of drug registration documents,the paper demonstrates the practical outcomes of LLM applications and envisions future developments in intelligent systems,safety measures,collaborative platforms,and personalized service development in drug regulation.关键词
药品监管/人工智能/大语言模型/一体化建设框架/实践案例Key words
drug regulation/artificial intelligence/large language model/integrated construction framework/case study分类
医药卫生
