分析
计算机科学
大数据
自动化
可追溯性
工业4.0
云计算
数据科学
质量(理念)
预测分析
个性化
医药制造业
过程管理
风险分析(工程)
人工智能
工程类
软件工程
万维网
业务
数据挖掘
哲学
操作系统
认识论
生物
机械工程
生物信息学
作者
Reshma Kodumuru,S. Sarkar,Varun Parepally,Jignesh Chandarana
出处
期刊:Pharmaceutics
[MDPI AG]
日期:2025-02-22
卷期号:17 (3): 290-290
被引量:14
标识
DOI:10.3390/pharmaceutics17030290
摘要
Background: The integration of artificial intelligence (AI) with the internet of things (IoTs) represents a significant advancement in pharmaceutical manufacturing and effectively bridges the gap between digital and physical worlds. With AI algorithms integrated into IoTs sensors, there is an improvement in the production process and quality control for better overall efficiency. This integration facilitates enabling machine learning and deep learning for real-time analysis, predictive maintenance, and automation—continuously monitoring key manufacturing parameters. Objective: This paper reviews the current applications and potential impacts of integrating AI and the IoTs in concert with key enabling technologies like cloud computing and data analytics, within the pharmaceutical sector. Results: Applications discussed herein focus on industrial predictive analytics and quality, underpinned by case studies showing improvements in product quality and reductions in downtime. Yet, many challenges remain, including data integration and the ethical implications of AI-driven decisions, and most of all, regulatory compliance. This review also discusses recent trends, such as AI in drug discovery and blockchain for data traceability, with the intent to outline the future of autonomous pharmaceutical manufacturing. Conclusions: In the end, this review points to basic frameworks and applications that illustrate ways to overcome existing barriers to production with increased efficiency, personalization, and sustainability.
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