摘要
Abstract
The U.S.Food and Drug Administration's(FDA)regulatory focus on pharmaceuticals and medical devices has gradually shifted from the traditional emphasis on pre-market approval to post-market supervision covering the entire product lifecycle.This shift shows a trend from a reductionist approach to the advantages of a holistic methodology.The FDA was the first federal agency to experiment with artificial intelligence(AI),including deep learning(DL).In recent years,while approving a growing number of products that incorporate AI,the FDA has also experimented with using AI for internal purposes—such as recruiting external experts,launching open challenge initiatives and pilot programs for the industry.The rapid development of AI has accelerated the FDA's regulatory paradigm transformation.Furthermore,the regulation of pharmaceuticals and medical devices also faces uncertainties,and the FDA's exploration in these areas can offer valuable insights for other government agencies seeking to apply similar technologies.This paper summarizes the role and development trends of AI-assisted regulatory paradigm transformation at the FDA,based on its specific practices,to provide references for other regulatory agencies in related fields.关键词
人工智能/范式转型/锁定算法/内部能力建设/不确定性/智慧数据Key words
artificial intelligence/paradigm transformation/locked algorithms/internal capacity development/uncertainties/smart data分类
药学
