Article(id=1322624503948104372, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322624482217415197, articleNumber=null, orderNo=null, doi=10.20251/j.cnki.1003-3734.2026.19.009, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1777305600000, receivedDateStr=2026-04-28, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793267854916, onlineDateStr=2026-10-29, pubDate=1791993600000, pubDateStr=2026-10-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793267854916, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793267854916, creator=13701087609, updateTime=1793267854916, updator=13701087609, issue=Issue{id=1322624482217415197, tenantId=1146029695717560320, journalId=1235980733773295621, year='2026', volume='35', issue='19', pageStart='2017', pageEnd='2128', issueExtLink='null', onlineDate='null', pubDate='1791993600000', pubDateStr='2026-10-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1793267849735, creator='13701087609', updateTime=1793268229475, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322626075042100008, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322624482217415197, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322626075046294313, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322624482217415197, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2082, endPage=2089, ext={EN=ArticleExt(id=1322624504103293621, articleId=1322624503948104372, tenantId=1146029695717560320, journalId=1235980733773295621, language=EN, title=Architecture design and application exploration of an intelligent quality control system for new traditional chinese medicine drug clinical trials from an institutional perspective, columnId=null, journalTitle=Chinese Journal of New Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=

AbstractIn response to the limitations of the traditional quality control (QC) model for clinical trials of new traditional Chinese medicine (TCM) drugs, this paper explores the construction of a full-process intelligent QC system centered on artificial intelligence (AI) technology. From the perspective of clinical trial institutions, by integrating currently relatively mature AI technologies, this paper proactively plans QC application scenarios for clinical trials of new TCM drugs and proposes an intelligent QC system architecture covering the entire process before, during, and after the trial. It focuses on elaborating the framework, module composition, main functions, key technical features, and implementation pathways of the intelligent QC system, including data security, management of drugs and biospecimens, protocol evaluation and start-up preparation, intelligent screening and recruitment, risk monitoring and early warning, data governance and quality assessment, and knowledge accumulation and mining. The clinical trial QC system deeply integrated with AI technology can enable institutions to achieve a paradigm shift in QC, shifting from passive response to active prevention and from post-hoc verification to real-time monitoring, thereby improving the quality and efficiency of clinical trials.

, authors=Wan-zhong SHI1, Yi-hui HU1, Yi-chen ZHOU1, Xi-yi ZHANG1, Cheng-bin XU1, Ping XU1, Liu YANG2, Lei-lei ZHU1, *, Wei-an YUAN1, *, authorsList=Wan-zhong SHI, Yi-hui HU, Yi-chen ZHOU, Xi-yi ZHANG, Cheng-bin XU, Ping XU, Liu YANG, Lei-lei ZHU, Wei-an YUAN, authorCompany=null, correspAuthors=Lei-lei ZHU, Wei-an YUAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322624504392700598, articleId=1322624503948104372, tenantId=1146029695717560320, journalId=1235980733773295621, language=CN, title=基于机构视角的中药新药临床试验智能质控系统架构设计与应用探索, columnId=1236331741447778310, journalTitle=中国新药杂志, columnName=药物临床试验规范与进展专栏, runingTitle=null, highlight=null, articleAbstract=

针对中药新药临床试验传统质控模式的局限,探索以人工智能(artificial intelligence, AI)技术为核心的全流程智能化质控系统的构建。基于临床试验机构视角,通过整合目前相对成熟的AI技术,前瞻性地规划面向中药新药临床试验的质控应用场景,提出了智能质控系统架构,覆盖“试验前-试验中-试验后”全流程。重点阐述了智能质控系统框架、模块组成、主要功能、关键技术特点与实现路径,涵盖数据安全、药物与生物样本管理、方案评估与启动准备、智能筛选与招募、风险监控与预警、数据治理和质量评估、知识沉淀与挖掘等环节。深度融合AI技术的临床试验质控系统,可助力机构实现从被动响应到主动预防、从事后核查到实时监控的质控范式转变,提升临床试验质量与效率。

, authors=史万忠1, 胡薏慧1, 周一辰1, 张习艺1, 徐铖斌1, 徐平1, 羊柳2, 朱蕾蕾1, *, 元唯安1, *, authorsList=史万忠, 胡薏慧, 周一辰, 张习艺, 徐铖斌, 徐平, 羊柳, 朱蕾蕾, 元唯安, authorCompany=null, correspAuthors=朱蕾蕾, 元唯安, authorNote=

史万忠,男,博士,主任药师,研究方向:中药制剂与临床评价。E-mail:。

, correspAuthorsNote=

*

朱蕾蕾,女,博士,主任医师,研究方向:中药新药临床研究。E-mail:。

*

元唯安,男,博士,主任医师,研究方向:中药新药临床评价。E-mail:。
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史万忠,男,博士,主任药师,研究方向:中药制剂与临床评价。E-mail:。

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基于机构视角的中药新药临床试验智能质控系统架构设计与应用探索
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史万忠 1 , 胡薏慧 1 , 周一辰 1 , 张习艺 1 , 徐铖斌 1 , 徐平 1 , 羊柳 2 , 朱蕾蕾 1, * , 元唯安 1, *
中国新药杂志 | 药物临床试验规范与进展专栏 2026,35(19): 2082-2089
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中国新药杂志 |药物临床试验规范与进展专栏 2026 , 35 (19) : 2082 -2089
基于机构视角的中药新药临床试验智能质控系统架构设计与应用探索
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史万忠1 , 胡薏慧1, 周一辰1, 张习艺1, 徐铖斌1, 徐平1, 羊柳2, 朱蕾蕾1, * , 元唯安1, *
作者信息
  • 1上海中医药大学附属曙光医院,上海 201203
  • 2美科健康科技(上海)有限公司,上海 200062
通讯作者:

*

朱蕾蕾,女,博士,主任医师,研究方向:中药新药临床研究。E-mail:。

*

元唯安,男,博士,主任医师,研究方向:中药新药临床评价。E-mail:。
作者简介:

史万忠,男,博士,主任药师,研究方向:中药制剂与临床评价。E-mail:。

Architecture design and application exploration of an intelligent quality control system for new traditional chinese medicine drug clinical trials from an institutional perspective
Wan-zhong SHI1 , Yi-hui HU1, Yi-chen ZHOU1, Xi-yi ZHANG1, Cheng-bin XU1, Ping XU1, Liu YANG2, Lei-lei ZHU1, * , Wei-an YUAN1, *
Affiliations
  • 1 Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
  • 2 Medcare Health Technology (Shanghai) Co., Ltd., Shanghai 200062, China
出版时间: 2026-10-15 doi: 10.20251/j.cnki.1003-3734.2026.19.009
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针对中药新药临床试验传统质控模式的局限,探索以人工智能(artificial intelligence, AI)技术为核心的全流程智能化质控系统的构建。基于临床试验机构视角,通过整合目前相对成熟的AI技术,前瞻性地规划面向中药新药临床试验的质控应用场景,提出了智能质控系统架构,覆盖“试验前-试验中-试验后”全流程。重点阐述了智能质控系统框架、模块组成、主要功能、关键技术特点与实现路径,涵盖数据安全、药物与生物样本管理、方案评估与启动准备、智能筛选与招募、风险监控与预警、数据治理和质量评估、知识沉淀与挖掘等环节。深度融合AI技术的临床试验质控系统,可助力机构实现从被动响应到主动预防、从事后核查到实时监控的质控范式转变,提升临床试验质量与效率。

中药新药  /  临床试验  /  质量控制  /  人工智能  /  全流程管理

AbstractIn response to the limitations of the traditional quality control (QC) model for clinical trials of new traditional Chinese medicine (TCM) drugs, this paper explores the construction of a full-process intelligent QC system centered on artificial intelligence (AI) technology. From the perspective of clinical trial institutions, by integrating currently relatively mature AI technologies, this paper proactively plans QC application scenarios for clinical trials of new TCM drugs and proposes an intelligent QC system architecture covering the entire process before, during, and after the trial. It focuses on elaborating the framework, module composition, main functions, key technical features, and implementation pathways of the intelligent QC system, including data security, management of drugs and biospecimens, protocol evaluation and start-up preparation, intelligent screening and recruitment, risk monitoring and early warning, data governance and quality assessment, and knowledge accumulation and mining. The clinical trial QC system deeply integrated with AI technology can enable institutions to achieve a paradigm shift in QC, shifting from passive response to active prevention and from post-hoc verification to real-time monitoring, thereby improving the quality and efficiency of clinical trials.

new traditional chinese medicine drugs  /  clinical trials  /  quality control  /  artificial intelligence  /  whole-process management
史万忠, 胡薏慧, 周一辰, 张习艺, 徐铖斌, 徐平, 羊柳, 朱蕾蕾, 元唯安. 基于机构视角的中药新药临床试验智能质控系统架构设计与应用探索. 中国新药杂志, 2026 , 35 (19) : 2082 -2089 . DOI: 10.20251/j.cnki.1003-3734.2026.19.009
Wan-zhong SHI, Yi-hui HU, Yi-chen ZHOU, Xi-yi ZHANG, Cheng-bin XU, Ping XU, Liu YANG, Lei-lei ZHU, Wei-an YUAN. Architecture design and application exploration of an intelligent quality control system for new traditional chinese medicine drug clinical trials from an institutional perspective[J]. Chinese Journal of New Drugs, 2026 , 35 (19) : 2082 -2089 . DOI: 10.20251/j.cnki.1003-3734.2026.19.009
  • 上海市卫生健康委员会智慧医疗专项研究资助项目(2025ZHYL037)
  • 国家重点研发计划中医药现代化专项资助项目(2025YFC3507902)
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2026年第35卷第19期
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doi: 10.20251/j.cnki.1003-3734.2026.19.009
  • 接收时间:2026-04-28
  • 首发时间:2026-10-29
  • 出版时间:2026-10-15
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  • 收稿日期:2026-04-28
基金
上海市卫生健康委员会智慧医疗专项研究资助项目(2025ZHYL037)
国家重点研发计划中医药现代化专项资助项目(2025YFC3507902)
作者信息
    1上海中医药大学附属曙光医院,上海 201203
    2美科健康科技(上海)有限公司,上海 200062

通讯作者:

*

朱蕾蕾,女,博士,主任医师,研究方向:中药新药临床研究。E-mail:。

*

元唯安,男,博士,主任医师,研究方向:中药新药临床评价。E-mail:。
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https://castjournals.cast.org.cn/joweb/zgxyzz/CN/10.20251/j.cnki.1003-3734.2026.19.009
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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