Considerations for Big Data management in pharmaceutical manufacturing

被引:1
作者
Das, Jayanti [1 ]
Fisher, Adam C. [1 ]
Hughey, Lisa [1 ]
O'Connor, Thomas F. [1 ]
Pai, Vidya [1 ]
Soto, Cinque [2 ]
Wan, John [1 ]
机构
[1] US FDA, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
[2] US FDA, Ctr Biol Evaluat & Res, Silver Spring, MD 20993 USA
关键词
Compendex;
D O I
10.1016/j.coche.2024.101051
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Big Data technologies are advancing the manufacturing of drug and biological products. Such technologies include innovative software and computational methods for data storage, mining, and analytics. Increasingly vast, complex data sets are being produced by advanced manufacturing processes and sensors for statistical analysis and decision-making. Implementing Big Data technologies, however, can introduce new challenges for organizations in areas of data generation, architecture, and security. Big Data management includes implementing robust storage, complex data integration, and state-of-the-art analysis software. Upholding data integrity and security might require designing a modernized risk-based framework plan for the organization. Once these challenges are successfully addressed, the incorporation of Big Data technologies into pharmaceutical manufacturing is expected to enable more efficient production, lower costs, and greater quality control, resulting in a stronger global pharmaceutical supply chain.
引用
收藏
页数:13
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