Department of Manufacturing Pharmacy, College of Pharmacy, Rangsit University, Pathum Thani 12000, Thailand.
Thammasat University Research Unit in Smart Materials and Innovative Technology for Pharmaceutical Applications (SMIT-Pharm), Faculty of Pharmacy, Thammasat University, Pathumthani 12120, Thailand.
Eur J Pharm Sci. 2024 Dec 1;203:106938. doi: 10.1016/j.ejps.2024.106938. Epub 2024 Oct 16.
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.
人工智能(AI)的出现推动了制药行业的深刻变革,在药物发现、制剂开发、生产、质量控制和上市后监测等各个领域带来了范式转变。本综述全面考察了 AI 驱动技术对制药生命周期各个阶段的多方面影响。它讨论了机器学习算法、数据分析和预测建模在加速药物发现过程、优化制剂开发、提高生产效率、确保严格的质量控制措施以及彻底改变上市后监测方法方面的应用。通过描述在制药领域利用 AI 的进展、挑战和未来前景,本综述为 AI 驱动创新时代药物开发和监管实践的不断发展提供了有价值的见解。