Process analytical technologies and self-optimization algorithms in automated pharmaceutical continuous manufacturing

被引：0

作者：

Peiwen Liu ^{[1
]}

Hui Jin ^{[1
]}

Yan Chen ^{[1
]}

Derong Wang ^{[1
]}

Haohui Yan ^{[1
]}

Mingzhao Wu ^{[1
]}

Fang Zhao ^{[2
]}

Weiping Zhu ^{[1
,3
]}

机构：

[1] State Key Laboratory of Bioreactor Engineering, Shanghai Key Laboratory of Chemical Biology, School of Pharmacy, East China University of Science and Technology

[2] State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology

[3] Engineering Research Center of Pharmaceutical Process Chemistry, Ministry of Education, School of Pharmacy, East China University of Science and Technology

来源：

ChineseChemicalLetters | 2024年 / 35卷 / 03期

关键词：

D O I：

暂无

中图分类号：

TQ460.6 [制药工艺];

学科分类号：

1007 ;

摘要：

The pharmaceutical industry is now paying increased attention to continuous manufacturing. While the revolution to continuous and automated manufacturing is deepening in most of the top pharma companies in the world, the advancement of automated pharmaceutical continuous manufacturing in China is relatively slow due to some key challenges including the lack of knowledge on the related technologies and shortage of qualified personnels. In this review, emphasis is given to two of the crucial technologies in automated pharmaceutical continuous manufacturing, i.e., process analytical technology(PAT) and self-optimizing algorithm. Research work published in recent 5 years employing advanced PAT tools and self-optimization algorithms is introduced, which represents the great progress that has been made in automated pharmaceutical continuous manufacturing.

引用

页码：116 / 124

页数：9

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