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

Peiwen Liu ¹Hui Jin ¹Yan Chen ¹Derong Wang ¹Haohui Yan ¹Mingzhao Wu ¹Fang Zhao ²Weiping Zhu³

扫码查看

作者信息

1. State Key Laboratory of Bioreactor Engineering,Shanghai Key Laboratory of Chemical Biology,School of Pharmacy,East China University of Science and Technology,Shanghai 200237,China
2. State Key Laboratory of Chemical Engineering,School of Chemical Engineering,East China University of Science and Technology,Shanghai 200237,China
3. State Key Laboratory of Bioreactor Engineering,Shanghai Key Laboratory of Chemical Biology,School of Pharmacy,East China University of Science and Technology,Shanghai 200237,China;Engineering Research Center of Pharmaceutical Process Chemistry,Ministry of Education,School of Pharmacy,East China University of Science and Technology,Shanghai 200237,China
折叠

Abstract

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 compa-nies 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 technolo-gies 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.

Key words

Pharmaceutical continuous manufacturing/Automation/Process analytical technology/Self-optimization algorithm

引用本文复制引用

基金项目

国家自然科学基金(21808059)

国家自然科学基金(21878088)

国家自然科学基金(21476077)

Key Project of the Shanghai Science and Technology Committee(18DZ1112703)

出版年

2024

中国化学快报(英文版)

中国化学会

中国化学快报(英文版)

CSTPCD

影响因子：0.771

ISSN：1001-8417

参考文献量116

段落导航