制药工业
范式转换
药物发现
设计质量
质量(理念)
控制(管理)
风险分析(工程)
医药制造业
药物开发
业务
计算机科学
制造工程
药品
数据科学
生化工程
工程类
人工智能
营销
药理学
医学
化学
新产品开发
哲学
认识论
生物化学
作者
Kampanart Huanbutta,Kanokporn Burapapadh,Pakorn Kraisit,Pornsak Sriamornsak,Thittaporn Ganokratanaa,Kittipat Suwanpitak,Tanikan Sangnim
标识
DOI:10.1016/j.ejps.2024.106938
摘要
The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceutical industry, ushering in a paradigm shift across various domains, including drug discovery, formulation development, manufacturing, quality control, and post-market surveillance. This comprehensive review examines the multifaceted impact of AI-driven technologies on all stages of the pharmaceutical life cycle. It discusses the application of machine learning algorithms, data analytics, and predictive modeling to accelerate drug discovery processes, optimize formulation development, enhance manufacturing efficiency, ensure stringent quality control measures, and revolutionize post-market surveillance methodologies. By describing the advancements, challenges, and future prospects of harnessing AI in the pharmaceutical landscape, this review offers valuable insights into the evolving dynamics of drug development and regulatory practices in the era of AI-driven innovation.
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