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Article(id=1240710436992110765, tenantId=1146029695717560320, journalId=1205117082300743687, issueId=1240710432898478399, articleNumber=null, orderNo=null, doi=10.14109/j.cnki.xyylc.2024.10.07, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1683475200000, receivedDateStr=2023-05-08, revisedDate=null, revisedDateStr=null, acceptedDate=1711900800000, acceptedDateStr=2024-04-01, onlineDate=1773738019464, onlineDateStr=2026-03-17, pubDate=1729785600000, pubDateStr=2024-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773738019464, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773738019464, creator=13701087609, updateTime=1773738019464, updator=13701087609, issue=Issue{id=1240710432898478399, tenantId=1146029695717560320, journalId=1205117082300743687, year='2024', volume='43', issue='10', pageStart='721', pageEnd='800', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773738018488, creator=13701087609, updateTime=1773738214158, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240711253669237259, tenantId=1146029695717560320, journalId=1205117082300743687, issueId=1240710432898478399, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240711253669237260, tenantId=1146029695717560320, journalId=1205117082300743687, issueId=1240710432898478399, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=765, endPage=771, ext={EN=ArticleExt(id=1240710437579313329, articleId=1240710436992110765, tenantId=1146029695717560320, journalId=1205117082300743687, language=EN, title=Analysis of development and hotspot of global drug regulatory science research based on CiteSpace, columnId=1207314215644270693, journalTitle=Chinese Journal of New Drugs and Clinical Remedies, columnName=Policy and Management, runingTitle=null, highlight=null, articleAbstract=
AIM

To explore the research hotspots and development trends of global drug regulatory science, and to provide reference for promoting the sustainable development of drug regulatory science in China.

METHODS

The literatures related to drug regulatory science published from 1991 to 2023 was searched from Web of Science database, and the contents of time distribution, author, institution, country / region and keywords were analyzed by CiteSpace 5.8.R3.

RESULTS

A total of 540 papers were included, and the annual number of published papers showed a stable growth trend. Foreign regulatory scientific research started early, and now it has formed a relatively complete regulatory scientific development system, and formed a relatively close cooperative relations among countries and institutions. Drug regulatory science research has evolved from an initial stage to a stage of refined research around new tools, standards, and methods; research hotspots include drug development, risk assessment, biomarkers, etc.

CONCLUSION

China’s drug regulatory authorities can increase policy guidance, strengthen basic theoretical research and applied capacity building, promote interdisciplinary joint research, and build a multidisciplinary academic exchange platform in order to accelerate the development of drug regulatory science.

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目的

探析全球药品监管科学的研究热点和发展趋势，为推动我国药品监管科学持续发展提供参考。

方法

在Web of Science核心合集数据库中检索1991—2023年发表的药品监管科学的相关文献，应用CiteSpace 5.8.R3软件对纳入文献从时间分布、作者、机构、国家/地区、关键词等方面进行可视化分析。

结果

共纳入540篇文献，各年度发文量整体呈稳定增长趋势。国外药品监管科学研究起步较早，现已形成较为完善的监管科学发展体系，各国及机构间形成了较为紧密的合作关系。药品监管科学研究已从初始阶段发展到围绕新工具、新标准、新方法的细化研究阶段，研究热点包括药物研发、风险评估、生物标志物等。

结论

我国药品监管部门可加大政策引导，加强基础理论研究和应用能力建设，推动跨学科联合研究，构建多学科学术交流平台，以促进药品监管科学创新发展。

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孟光兴
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舒奎，男，硕士在读，主要从事社会与管理药学研究，Phn: 86-760-8820-7911，E-mail:

孟光兴，男，教授，硕士生导师，硕士，主要从事社会与管理药学研究，Phn: 86-760-8820-7911，E-mail:

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聚类编号轮廓值聚类名称关键词
#00.987regulatory science 监管科学真实世界数据、利益冲突、同行评审
#10.956drug regulatory science 药品监管科学效益风险评估、医院豁免、先进治疗药品
#20.944pharmacodynamics 药效学IMPACT研究、分析化学、定量药理学
#30.917cigarettes 烟草烟草监管科学、水烟、青少年
#40.823multivariate analysis 多变量分析药物设计、香精、决策树
#50.966linear non-threshold model线性非阈值模型冠心病、质量源于设计、免疫疗法
#60.994drug development 药物研发审批时间、突破性疗法、安全药理学
#70.931risk assessment 风险评估毒理基因组学、不确定性、变异检测
#80.957activation 激活定量、生物标志物开发、数字疗法
#90.942in vitro models 体外模型种族、生理药动学（PBPK）模型、药动学（DMPK）
#100.959systems biology 系统生物学生物制剂、细胞和基因治疗、机器学习
), ArticleFig(id=1240719595871457953, tenantId=1146029695717560320, journalId=1205117082300743687, articleId=1240710436992110765, language=CN, label=表1, caption=

药品监管科学研究文献的关键词聚类结果

, figureFileSmall=null, figureFileBig=null, tableContent=
聚类编号轮廓值聚类名称关键词
#00.987regulatory science 监管科学真实世界数据、利益冲突、同行评审
#10.956drug regulatory science 药品监管科学效益风险评估、医院豁免、先进治疗药品
#20.944pharmacodynamics 药效学IMPACT研究、分析化学、定量药理学
#30.917cigarettes 烟草烟草监管科学、水烟、青少年
#40.823multivariate analysis 多变量分析药物设计、香精、决策树
#50.966linear non-threshold model线性非阈值模型冠心病、质量源于设计、免疫疗法
#60.994drug development 药物研发审批时间、突破性疗法、安全药理学
#70.931risk assessment 风险评估毒理基因组学、不确定性、变异检测
#80.957activation 激活定量、生物标志物开发、数字疗法
#90.942in vitro models 体外模型种族、生理药动学（PBPK）模型、药动学（DMPK）
#100.959systems biology 系统生物学生物制剂、细胞和基因治疗、机器学习
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基于CiteSpace的全球药品监管科学研究发展脉络与热点分析
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舒奎 1 , 孟光兴 1, 2
中国新药与临床杂志 | 政策与管理 2024,43(10): 765-771
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中国新药与临床杂志 | 政策与管理 2024, 43(10): 765-771
基于CiteSpace的全球药品监管科学研究发展脉络与热点分析
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舒奎1 , 孟光兴1, 2
作者信息
  • 1.广东药科大学医药商学院，广东 广州　510006
  • 2.国家药品监督管理局 药物警戒技术研究与评价重点实验室，广东 中山　528400

    • 舒奎，男，硕士在读，主要从事社会与管理药学研究，Phn: 86-760-8820-7911，E-mail:

    孟光兴，男，教授，硕士生导师，硕士，主要从事社会与管理药学研究，Phn: 86-760-8820-7911，E-mail:

通讯作者:

孟光兴
Analysis of development and hotspot of global drug regulatory science research based on CiteSpace
Kui SHU1 , Guang-xing MENG1, 2
Affiliations
  • 1.School of Pharmaceutical Business, Guangdong Pharmaceutical University, Guangzhou GUANGDONG 510006, China
  • 2.NMPA Key Laboratory for Technology Research and Evaluation of Pharmacovigilance, Zhongshan GUANGDONG 528400, China
出版时间: 2024-10-25 doi: 10.14109/j.cnki.xyylc.2024.10.07
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摘要
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目的

探析全球药品监管科学的研究热点和发展趋势，为推动我国药品监管科学持续发展提供参考。

方法

在Web of Science核心合集数据库中检索1991—2023年发表的药品监管科学的相关文献，应用CiteSpace 5.8.R3软件对纳入文献从时间分布、作者、机构、国家/地区、关键词等方面进行可视化分析。

结果

共纳入540篇文献，各年度发文量整体呈稳定增长趋势。国外药品监管科学研究起步较早，现已形成较为完善的监管科学发展体系，各国及机构间形成了较为紧密的合作关系。药品监管科学研究已从初始阶段发展到围绕新工具、新标准、新方法的细化研究阶段，研究热点包括药物研发、风险评估、生物标志物等。

结论

我国药品监管部门可加大政策引导，加强基础理论研究和应用能力建设，推动跨学科联合研究，构建多学科学术交流平台，以促进药品监管科学创新发展。

监管科学  /  文献计量学  /  知识图谱  /  数据可视化  /  组织和管理
AIM

To explore the research hotspots and development trends of global drug regulatory science, and to provide reference for promoting the sustainable development of drug regulatory science in China.

METHODS

The literatures related to drug regulatory science published from 1991 to 2023 was searched from Web of Science database, and the contents of time distribution, author, institution, country / region and keywords were analyzed by CiteSpace 5.8.R3.

RESULTS

A total of 540 papers were included, and the annual number of published papers showed a stable growth trend. Foreign regulatory scientific research started early, and now it has formed a relatively complete regulatory scientific development system, and formed a relatively close cooperative relations among countries and institutions. Drug regulatory science research has evolved from an initial stage to a stage of refined research around new tools, standards, and methods; research hotspots include drug development, risk assessment, biomarkers, etc.

CONCLUSION

China’s drug regulatory authorities can increase policy guidance, strengthen basic theoretical research and applied capacity building, promote interdisciplinary joint research, and build a multidisciplinary academic exchange platform in order to accelerate the development of drug regulatory science.

regulatory science  /  bibliometrics  /  knowledge graph  /  data visualization  /  organization and administration
舒奎, 孟光兴. 基于CiteSpace的全球药品监管科学研究发展脉络与热点分析. 中国新药与临床杂志, 2024 , 43 (10) : 765 -771 . DOI: 10.14109/j.cnki.xyylc.2024.10.07
Kui SHU, Guang-xing MENG. Analysis of development and hotspot of global drug regulatory science research based on CiteSpace[J]. Chinese Journal of New Drugs and Clinical Remedies, 2024 , 43 (10) : 765 -771 . DOI: 10.14109/j.cnki.xyylc.2024.10.07
正文
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监管科学是一门以监管活动及其规律为研究对象，以提升监管工作质量和效率为目标，以监管工具、标准和方法创新为重点的新科学[1]。1990年，美国Jasanoff教授对监管科学进行了深入阐述，认为其是一门交叉学科[2]。近年来，监管科学受到以美国食品和药物管理局（Food and Drug Administration，FDA）为代表的各国药品监管部门的高度关注[3]。自2004年以来，FDA发布多份白皮书总结了其既往的药品监管策略，进一步推动了监管科学的发展。2018年，欧洲药品管理局（European Medicines Agency，EMA）也开始收集利益相关者有关EMA监管科学战略的意见[4]，并于2020年正式发布《面向2025年的EMA监管科学战略》。2019年4月30日，我国国家药品监督管理局也启动了中国药品监管科学行动计划，开始系统开展药品、医疗器械、化妆品监管科学研究，目前已初步形成具有中国特色的监管科学研究发展模式[5]。本研究运用CiteSpace 5.8.R3软件对药品监管科学领域的研究现状、研究热点、发展脉络及研究趋势进行可视化分析，以期为推动我国药品监管科学的研究和发展提供参考。
资料与方法
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数据来源
以Web of Science（WOS）核心合集数据库作为文献来源，通过主题、篇名、关键词等多种模式对监管科学研究文献进行检索，关键词为“regulatory science”。考虑到我国药品监管科学目前处于起步阶段，本研究将文献语种限制为英文，学科领域限制为医药，检索时间设为1991年1月1日—2023年5月31日（后补充检索至2023年12月31日）。排除新闻报道、征稿启事等非研究型文献，与主题明显不符的文献，以及重复文献后，将文献作者、标题、摘要、关键词和发表年份等信息以纯文本文件格式导出，并转化为CiteSpace 5.8.R3可处理的数据格式。
研究方法
应用可视化工具CiteSpace 5.8.R3，从文献发文量、作者、机构、国家/地区、关键词等维度对收集到的文献进行分析，绘制可视化图谱。相关参数设定如下：由于最早的一篇文献发表于1997年，因此本研究将时间设置为1997—2023年，时间切片（years per slice）设置为1；选择“Pathfinder”“Pruning sliced networks”“Pruning the merged network”进行网络图谱裁剪；其余参数均为默认值。
结果
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纳入文献的时间分布特征
本研究共检索到596篇文献，按照纳入与排除标准筛选并剔除重复文献后，最终纳入文献540篇。其中，药品监管研究领域的第1篇文献于1997年在Food and Drug Law Journal发表，之后该领域的文献发文量总体呈上升趋势，特别是2010年之后，该领域的年度发文量大幅增长，表明从这一时期开始，研究人员开始重视该领域的发展。这可能是因为，美国FDA于2010年2月首次以《推进公共健康的监管科学》（Advancing Regulatory Science for Public Health）的报告形式提出了监管科学的基本架构。因此，纵观该领域相关文献发表的时间分布及相关研究的发展进程，可将该领域的相关研究分为两个阶段：第一阶段为2010年以前，为监管科学发展的初始阶段，相关文献发文量较少，年平均发文量仅为2.5篇，且大部分文献都是从宏观层面对监管科学进行探索，强调监管决策的科学性在监管流程和实践中的重要性；第二阶段为2010年以后，随着FDA监管科学架构的提出，国际上对监管科学也日益重视，各国学者围绕新工具、新标准、新方法，对监管科学展开了细化研究，使得该领域的发文量快速增长且保持较高增速。各年度发文量见图1。
研究主体分析
1　作者合作分析
作者合作网络体现了各研究学者在其研究领域中的贡献大小和彼此间的合作关系。每个节点代表1位作者，节点间的连线代表作者间存在合作关系，连线颜色和粗细分别反映了合作时间及合作次数，节点年轮最外圈的颜色越深代表该节点的中介中心性越高。本研究绘制的药品监管科学研究的作者合作网络图谱见图2。图中共有549个节点，934条连线，网络密度值为0.006。由图2可知，该领域的研究学者数量较多，但作者间的合作较少，大部分研究者都是独立进行或仅开展了小规模合作。该领域发文量最多的是ISSAM（6篇）和YOSHIAKI（6篇）。其中，ISSAM的团队对生物标志物在新药研发、建模和仿真模型在药物研发和监管中的应用提出了前瞻性的见解[6, 7]；YOSHIAKI的团队主要从药品监管的角度探讨了药物基因组学在指导药物开发过程中的挑战以及真实世界数据在药物安全性评估中的应用[8, 9]。其次，是以NEIL为中心的团队，该团队主要关注不同监管机构在新药研发中的风险评估以及监管决策的质量[10]。除此之外，其他学者还在结构化数据管理、生物治疗等领域进行了探索研究。
2　机构合作分析
研究机构合作网络图谱见图3。图中共有429个节点，923条连线，网络密度值为0.011。监管科学研究机构主要有FDA、EMA、乌得勒支大学（Utrecht University）、关键路径研究所（Critical Path Institute）、杜克大学（Duke University）等，主要分布在欧美发达国家，且呈现出药品监管部门、高等院校、科研机构、行业协会、制药企业共同参与的良性发展局面，并形成了相对紧密的合作关系。进一步分析文献可以发现，国外较早涉及监管科学研究的机构有美国密西根大学（University of Michigan）、加拿大阿尔伯塔大学（University of Alberta）等，这些研究主要讨论了基于生物药剂学分类系统的生物利用度和生物等效性在简化和改进药物审批过程中的最新发展和未来趋势[11]。杜克大学 、克利夫兰医学中心（Cleveland Clinic）、FDA等机构在生物标志物的开发和评估方面展开了讨论[12]；EMA、英国药品和健康产品管理局（Medicines and Healthcare Products Regulatory Agency）等在纳米药物的开发和监管方面展开了合作[13]；而赛诺菲（Sanofi）、阿斯利康（AstraZeneca）等制药企业则研究了定量框架和监管科学在儿科药物开发中的作用，并将继续在儿科药物开发领域开展合作[14]。
3　国家/地区合作分析
统计纳入文献的作者所在国家/地区可以发现，英文文献发文量排名前5位的分别为美国（316篇）、英格兰（95篇）、日本（58篇）、德国（52篇）、荷兰（44篇）。我国在药品监管科学研究方面起步较晚，但发展迅速，发文量为29篇，排第7位。国家/地区合作网络图谱见图4。图中共有84个节点，456条连线，网络密度值为0.131。从合作情况来看，美国的节点中心度最大（0.330），在整个研究网络中占据重要的位置，其在药品监管科学研究领域的成果最为显著，在该学科发展方面起引领作用，且与加拿大、英格兰、法国、比利时、澳大利亚、瑞士等国家/地区建立了相对紧密的合作关系。
其他节点中心度靠前的国家还有意大利（0.310）、澳大利亚（0.300）、葡萄牙（0.250）、加拿大（0.170）等。中国的节点中心度较低（0.110），合作对象有瑞士、印度、韩国、巴基斯坦、泰国等，尚缺乏与欧美地区学者的合作。
研究热点分析
1　关键词聚类分析
关键词是文章核心内容与主要思想的集中体现，对关键词进行可视化展示和频次分析，有助于系统而全面地把握该研究领域近年来的主要研究热点和研究现状。
对关键词进行聚类分析可体现出关键词关键节点和重要连线的结构特征。在关键词共现网络图谱的基础上，本研究采用对数似然率法（log-likelihood ratio，LLR）对关键词进行聚类分析，共得到11个关键词聚类，聚类Q值为0.723，>0.3，表明聚类结构显著，S值为0.877，>0.7，表明聚类结果令人信服[15]。11个聚类的具体信息见表1。
聚类#2为药效学。药效学主要研究药物对机体的作用效果及规律，近年来发展迅速。例如，VAIDYANATHAN等[16]从临床药理学角度比较了儿童和成人口服抗糖药的差异，探讨了儿童使用口服抗糖药的安全性和有效性。HUANG等[17]以案例分析的形式探讨了FDA临床药理学办公室通过建模优化和仿真模拟等方式在开展药品监管科学工作中所做的努力。聚类#3为烟草，在美国，烟草制品的监管也在FDA的管辖范围内，烟草制品的监管与药品一样受到《联邦食品、药品和化妆品法案》部分条款约束。聚类#6为药物研发。新工具、新方法在药物研发中发挥巨大作用，例如，PECK[18]回顾了药物开发和监管科学从起步阶段到如今发展为基于模型的定量科学的发展历程，重点介绍了药理学家MALCOLM在药品监管科学中作出的突出贡献；SEWELL等[19]探讨了3R原则在药物安全性评估中的应用价值。此外，FDA目前已开发了优先审评、突破性疗法、加速审批、快速通道4种新方法，改善和简化了药物临床审评审批流程，对部分公众急需药品从研发到上市的不同阶段提供了支持。聚类#7为风险评估。药品风险管理是一项持续的、贯穿药品全生命周期的工作，欧洲委员会科学委员会出版的《应对风险评估的新挑战》（Addressing the New Challenges for Risk Assessment）等指导文件均特别强调了利用分子和细胞生物学过程数据进行风险评估的优势和挑战。FDA于2007年9月颁布的《FDA修正案》（Food and Drug Administration Amendments Act，FDAAA），在“上市后研究与监测”部分增加了“505-1风险评估与监督策略（Risk Evaluation and Mitigation Strategies，REMS）”条款，授权FDA在必要情况下，可要求药品上市许可持有人提交REMS计划，以确保药物收益大于风险。此外，BROCKMEIER等[20]学者也就组学数据集（例如转录组学、代谢组学、脂质组学、蛋白质组学等）在不良结果途径框架内的具体作用展开了论述，以加快风险评估过程。聚类#9为体外模型。体外模型是药物开发和临床前研究的重要工具。例如，人源诱导型多能干细胞分化的心肌细胞（hiPSC-CM）已广泛应用于药物体外心脏毒性评价研究中，使用hiPSC-CM进行替代测定可给监管决策提供参考[21]；MARZI等[22]使用数字全息显微镜开展了聚合物纳米材料无标记体外细胞毒性试验的室间评价等。聚类#10为系统生物学。系统生物学是对复杂生物系统进行演算分析、数学分析和建模的学科，在预测疫苗接种人群的安全性和保护性等方面发挥着越来越重要的作用。例如，BLACK等[23]以新型冠状病毒疫苗为例，讨论了疫苗研发周期长与公众对疫苗的迫切需求之间的冲突，提出一系列利用新技术、灵活的临床试验设计及不断发展的药品监管科学手段以加速疫苗开发的设想。FDA也于2020年1月启动了医疗对策倡议（Medical Countermeasures Initiative），旨在为新型冠状病毒相关医疗产品的开发及FDA的审查提供方法。
2　关键词时区分析
关键词时区图谱不仅能够呈现某一领域的研究主题，还能直观地显示不同时间点的研究热点、主题转变以及主题间的关联。图5展示了1997—2023年关键词路径的演化过程，可以大致描述药品监管科学的演进脉络。
由图5可见，1997—2010年是药品监管科学发展的初始阶段，监管科学、药物安全、临床试验、药物研发等概念开始出现并产生了较强的影响力，但这一阶段的关键词以宏观概念为主。这一时期研究主题的出现一方面是相关政策引导的结果，另一方面也是药品监管科学发展的必然经过。2004年，FDA发布《创新/停滞：通往新医疗产品关键路径上的机遇与挑战》（Innovation/Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products）白皮书，将提升监管能力、提高监管科学现代化水平、促进新的监管科学路径建设确定为监管科学发展的目标和任务[24]。2006年，FDA发布名为 《关键路径机遇清单》（Critical Path Opportunities List）的后续报告，将“更好的评价工具”“简化的临床试验”“生物信息学的应用”“21世纪的产业化发展”“开发公众急需的产品”“特殊的高风险人群用产品”等内容列为优先发展目标[25]，临床试验、药动学、药物研发、精准医疗、体外实验等开始受到研究者的广泛关注。
2010年，FDA在《推进公共健康的监管科学》中首次提出了监管科学的基本架构。2011—2022年是监管科学的深化发展期，相关研究的主题向多元化与深层次发展，并开始从宏观理论层面转向微观层面，且注重不同层次研究间的联系。动物模型、先进疗法产品等概念相继兴起。2011年，FDA组织召开了第一届全球药品监管科学峰会，颁布了《促进FDA监管科学战略计划》（Advancing Regulatory Science at FDA:A Strategic Plan），大力推行以科学为基础的监管理念，并提出药品监管科学优先发展的8个领域，激活、生物标志物开发等内容成为当年的研究热点。例如，BOJA等[26]介绍了美国国家癌症研究所临床蛋白质组学肿瘤分析联盟和FDA在基于蛋白质的生物标志物分析验证中的差异，以推动不同机构间的监管趋同。2013年，FDA增加第九项推进监管科学战略计划——加强全球产品安全网[27]，安全性、风险/收益评估遂成为当年的研究热点。围绕药品安全性监管工作，不少学者开展了相关研究。例如，EICHLER等[28]讨论了监管风险规避对公共健康的影响，提出将患者偏好纳入监管决策、使用定量方法排除个人因素对监管决策的干扰等一系列建议，使监管机构实现风险/收益比的最佳平衡。2019年，真实世界研究开始兴起，真实世界证据（real world evidence，RWE）和真实世界数据（real world data，RWD）在支持药物开发和监管决策方面具有不可替代的作用，各国在RWE的定义、构成、范围和应用方面的差异使得RWE法规呈现出多样性的特点。现有RWE的大部分研究集中于如何有效利用RWE支持新药临床开发和评估、协助监管决策制定（药物警戒和上市后研究）[29]、评估临床治疗效果、如何有效地从RWD中得出RWE[30]等，而针对如何开发、使用RWD，以及药品监管机构如何使用RWE的研究较少。我国国家药品监督管理局于2019年启动了药品监管科学行动计划，聚焦细胞和基因治疗、再生医学、RWD支持临床评价研究、药械组合等前沿性、交叉性科学研究。其中，细胞和基因治疗是国内外生物医药产业未来发展的主要方向之一。欧盟将细胞和基因治疗产品（cell and gene therapy，CGT）列为先进治疗产品（advanced therapy medicinal products，ATMP），用于治疗有限或没有有效治疗手段的特定疾病，SALAZAR-FONTANA[31]通过评估ATMP/GCT面临的质量、非临床和临床监管风险，提出监管部门可尝试构建欧盟/美国联合监管策略。2021年，我国国家药品监督管理局又发布了“中国药品监管科学行动计划第二批重点项目”，在总结首批重点项目实施情况的基础上，第二批重点项目包括了CGT的评价体系及方法研究，RWD支持中药、罕见病治疗药物、创新和临床急需医疗器械评价方法研究，纳米类创新药物和医疗器械的安全性、有效性和质量控制评价等10项研究。此外，近年来，随着机器学习、数据库等领域的发展，人工智能极大地促进了医药行业的发展。例如，BRERETON等[32]分析了人工智能和机器学习在辅助监管决策方面的发展现状，并提出了优化应用的思路。
讨论
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监管科学是一门多学科交叉的、研究范围和应用领域广泛的综合性学科。本文从文献计量学角度对药品监管科学领域的文献进行了可视化分析，结果发现，国外监管科学研究起步较早，现已形成较为完善的监管科学发展体系，各国家/地区及机构间形成了较为紧密的合作关系。分析发文量的时间分布与FDA等监管机构的政策发布时间之间的联系可以得出，政策对该领域的发展具有导向作用，一定程度上促进了该领域的快速发展和深入研究。因此，建议我国加大政策引导，鼓励多方合作，在药品监管科学行动计划下针对重点发展领域（CGT、纳米药物、医疗器械等）继续制定或补充更多技术指导原则，为我国药品监管科学发展提供政策保障。
不同机构间的交流合作有利于提升监管效率，节省监管资源。分析该领域的机构合作情况可知，欧美国家已在监管科学下的各个细分领域开展了合作，通过借鉴合作方的经验，可有效缩短与国际先进水平的差距。建议我国也应与各国监管科学研究的相关机构积极开展研究合作，并推动产业界、学术界和政府机构开展国内与国际合作，凝聚多方资源共同推进我国监管科学创新发展。
从关键词共现分析结果可知，国际监管科学研究热点集中在药物研发、风险评估、生物标志物等方面。其中，药物研发理念已由“以疾病为中心”转变为“以患者为中心”，药物筛选也由大量随机筛选转变为依赖生物信息技术的智能筛选。过去监管机构主要依靠定性方法作出收益/风险决策，而随着监管科学的发展，药品风险评估已经开始向结构化、定量化方向拓展。此外，获得官方认证的生物标志物可作为新药研发过程中的工具和评价标准，大大提高创新药研发效率和成功率。我国可根据目前药品监管中存在的短板，参考上述国外研究热点，加强基础理论研究和应用能力建设，推动跨学科联合研究，构建多学科学术交流平台，以推进我国药品监管科学向纵深发展。
基金
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  • 广东省科学技术厅2022年海外名师项目
  • 广东省药品监督管理局2022年科技创新项目(2022ZDZ06)
文献
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参考文献 引证文献
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2024年第43卷第10期
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doi: 10.14109/j.cnki.xyylc.2024.10.07
  • 接收时间：2023-05-08
  • 首发时间：2026-03-17
  • 出版时间：2024-10-25
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  • 收稿日期：2023-05-08
  • 录用日期：2024-04-01
基金
广东省科学技术厅2022年海外名师项目
广东省药品监督管理局2022年科技创新项目(2022ZDZ06)
作者信息
    1.广东药科大学医药商学院，广东 广州　510006
    2.国家药品监督管理局 药物警戒技术研究与评价重点实验室，广东 中山　528400

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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
species		 占总种数比例
Percentage of
total species (%)		 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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