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中药制药过程大数据平台建设及应用

徐芳芳 韩蕾 闫逸伦 王扬 张欣 王团结 王振中 章晨峰 肖伟

分析测试学报2026,Vol.45Issue(6):1196-1203,8.
分析测试学报2026,Vol.45Issue(6):1196-1203,8.DOI:10.12452/j.fxcsxb.26022805

中药制药过程大数据平台建设及应用

Construction and Application of Big Data Platform for Traditional Chinese Medicine Pharmaceutical Process

徐芳芳 1韩蕾 1闫逸伦 1王扬 1张欣 1王团结 1王振中 1章晨峰 2肖伟1

作者信息

  • 1. 中药制药过程控制与智能制造技术全国重点实验室(江苏康缘药业股份有限公司),江苏 连云港 222047
  • 2. 江苏省海洋药物和现代中药创制重点实验室,江苏 连云港 222047
  • 折叠

摘要

Abstract

At present,the construction of big data platforms for traditional Chinese medicine(TCM)pharmaceutical processes faces prominent challenges,including insufficient data standard-ization,inadequate technology integration,and weak security support.A scientific and rational core technical architecture and key links are critical to improving the quality of platform construction.This study took the construction of big data platform for TCM pharmaceutical processes as the research ob-ject,explored the core points and practical paths of platform construction,deeply analyzed its core technical architecture and key construction links,and summarized its practical effects in four core application areas of perception monitoring,process control,intelligent decision-making and quality traceability.It clarified the core role of the platform in integrating full-process data resources and re-leasing the value of data elements,aiming to provide theoretical references and practical experience for promoting the high-quality construction of big data platforms for TCM pharmaceutical processes and accelerating the precision and intelligent development of the pharmaceutical process control for traditional Chinese medicine.

关键词

中药制药/大数据平台/过程控制/质量追溯

Key words

traditional Chinese medicine manufacturing/big data platform/process control/qual-ity traceability

分类

化学化工

引用本文复制引用

徐芳芳,韩蕾,闫逸伦,王扬,张欣,王团结,王振中,章晨峰,肖伟..中药制药过程大数据平台建设及应用[J].分析测试学报,2026,45(6):1196-1203,8.

基金项目

国家长三角科技创新共同体联合攻关项目(2023CSJGG1700) (2023CSJGG1700)

中药制药过程控制与智能制造技术全国重点实验室定向课题(SKL2023D02003) (SKL2023D02003)

连云港市重点研发计划(CG2320) (CG2320)

分析测试学报

1004-4957

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