Article(id=1239250707862311047, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1239250701583446236, articleNumber=null, orderNo=null, doi=10.16155/j.0254-1793.2024.04.11, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1710345600000, revisedDateStr=2024-03-14, acceptedDate=null, acceptedDateStr=null, onlineDate=1773389992919, onlineDateStr=2026-03-13, pubDate=1714406400000, pubDateStr=2024-04-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773389992919, onlineIssueDateStr=2026-03-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773389992919, creator=13701087609, updateTime=1773389992919, updator=13701087609, issue=Issue{id=1239250701583446236, tenantId=1146029695717560320, journalId=1205117023404326918, year='2024', volume='44', issue='4', pageStart='553', pageEnd='736', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773389991422, creator=13701087609, updateTime=1773390513217, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1239252890213209050, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1239250701583446236, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1239252890213209051, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1239250701583446236, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=637, endPage=648, ext={EN=ArticleExt(id=1239250709586170000, articleId=1239250707862311047, tenantId=1146029695717560320, journalId=1205117023404326918, language=EN, title=Analysis of extractables in rubber with pseudotargeted metabolomics method*, columnId=1206272757852074373, journalTitle=Chinese Journal of Pharmaceutical Analysis, columnName=Safety Monitoring, runingTitle=null, highlight=null, articleAbstract=
Objective:

To perform a comprehensive analysis of extractables in rubber by pseudotargeted metabolomics.

Methods:

The quality control(QC) solutions and test solutions were prepared by extracting the six kinds of rubbers with water, pH 2.6 phosphate buffer, pH 9.18 phosphate buffer, and 15% ethanol solution, respectively. The QC solutions were detected by LC-30A ultra performance liquid chromatography-Q TOF-9030 mass spectrometer in ESI+/ESI- mode. The mobile phases were 0.1% formic acid-water and 0.1% formic acid-acetonitrile/0.05% ammonium-water and 0.05% ammonium -5% water-methanol. The separation chromatographic column was Waters Acquity BEH C8/HSS T3. TOF MS and MS/MS DDA scanning modes were used to detect the QC solutions. The scan results of QC solution were processed with MSConvert and MRM-Ion_Pair_Finder software to obtain MRM parameters. The extracts were detected by ExionLC UPLC-Qtrap6500+ mass spectrometer in ESI+/ESI- mode with the same mobile phase and column as before, and Scheduled-MRM scan mode was applied to detect the extracts.

Results:

The 1 399 unknown compounds and 116 known compounds were analyzed. By extraction solution, it was found that pH 9.18 phosphate buffer and 15% ethanol solution could extract more compounds, and 27 compounds with large differences in different extraction solutions were identified. By rubbers, the affinities of different rubbers were determined by 25 differences.

Conclusion:

In this study, the results of the extraction of six rubbers under four extracts are analyzed. There are differences between extracts under different extraction conditions. Analytical methods can be specifically developed for these key variables for quality control follow-up studies to ensure the stability and consistency of drug quality. The variables in different rubbers are also analyzed, which can be used to make a general class determination of unknown rubber samples.

, correspAuthors=Fang YAN, 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, authorCompany=null, fund=null, authors=null, authorsList=Hao-wen SHEN, Meng-qing XIAO, Hai-tao MENG, Xiang-yang LENG, Fang YAN), CN=ArticleExt(id=1239250714116018501, articleId=1239250707862311047, tenantId=1146029695717560320, journalId=1205117023404326918, language=CN, title=拟靶向代谢组学法分析胶塞中的可提取物*, columnId=1206272758036623764, journalTitle=药物分析杂志, columnName=安全监测, runingTitle=null, highlight=null, articleAbstract=
目的:

运用拟靶向代谢组学的方法对胶塞中的可提取物进行全面的分析。

方法:

以水、pH 2.6磷酸盐缓冲液、pH 9.18磷酸盐缓冲液、15%乙醇溶液分别对6种胶塞进行提取,制备质量控制(QC)溶液和供试品溶液。采用LC-30A超高效液相色谱仪-Q TOF-9030质谱ESI+/ESI-模式检测,使用Waters Acquity BEH C8/HSS T3色谱柱,以含0.1%甲酸的水-含0.1%甲酸的乙腈/含0.05%碳酸氢铵的水-含0.05%碳酸氢铵和5%水的甲醇作为流动相,运用TOF MS-和MS/MS DDA扫描模式对QC溶液进行检测。用MSConvert及MRM-Ion_Pair_Finder软件处理QC溶液的扫描结果,获得MRM参数。用ExionLC超高效液相色谱仪-Qtrap6500+质谱ESI+/ESI-模式检测,流动相和色谱柱同前,运用Scheduled-MRM扫描模式对提取液进行检测。

结果:

对1 399个未知物和116个已知物进行了分析,按提取液分类,发现pH 9.18磷酸盐缓冲液和15%乙醇溶液能提取出较多的化合物,找出了27个在不同提取液中差异较大的化合物;按胶塞分类,通过25个差异物,判断了不同胶塞的亲缘关系。

结论:

本研究对6种胶塞在4种提取物下的提取结果进行了分析。在不同的提取条件下,提取物之间存在差异。针对这些重点差异物可以专门制定分析方法进行质控跟踪研究,以确保药物质量的稳定和一致性。同时也分析了不同胶塞中的差异物,可以用来对未知胶塞样本进行大致的类别判断。

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** Tel:13851786026;E-mail:
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Tel:13801591267;E-mail:

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companyId=1239250714770330000, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=5.School of Pharmacy, China Pharmaceutical University, Nanjing 211198, China), AuthorCompanyExt(id=1239250714782912914, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, companyId=1239250714770330000, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=5.中国药科大学药学院,南京 211198)])], figs=[ArticleFig(id=1239250719400841855, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.1, caption=Overview of the pseudotargeted metabolomics method development, figureFileSmall=PRVFceVKzKJKbwOlMeNOxQ==, figureFileBig=vw876qfujWkrrtl1dkbiUg==, tableContent=null), ArticleFig(id=1239250719497310856, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图1, caption=拟靶向分析流程, figureFileSmall=PRVFceVKzKJKbwOlMeNOxQ==, figureFileBig=vw876qfujWkrrtl1dkbiUg==, tableContent=null), ArticleFig(id=1239250719862215317, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.2, caption=PCA score plot of unknown ion pair results(A) and PCA score plot of known ion pair results(B) (the figure in the upper right corner indicates different extraction solutions), figureFileSmall=qtffTMjLgN/bDz3XcbXFcw==, figureFileBig=POupeMePevQa+LgEA7IS1g==, tableContent=null), ArticleFig(id=1239250719962878623, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图2, caption=未知离子对结果的PCA图(A)和已知离子对结果的PCA图(B)(图中右上角数字表示不同提取溶液), figureFileSmall=qtffTMjLgN/bDz3XcbXFcw==, figureFileBig=POupeMePevQa+LgEA7IS1g==, tableContent=null), ArticleFig(id=1239250720080319140, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.3, caption=PLS-DA score plot of known ion pair results(A) and verification results(B), figureFileSmall=Jq0rKUGBlGSz6LcxDwOa7A==, figureFileBig=KnirZx3hOYXLvlR3sY+ZNw==, tableContent=null), ArticleFig(id=1239250720189371050, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图3, caption=已知离子对结果的PLS-DA图(A)和验证结果(B), figureFileSmall=Jq0rKUGBlGSz6LcxDwOa7A==, figureFileBig=KnirZx3hOYXLvlR3sY+ZNw==, tableContent=null), ArticleFig(id=1239250720281645744, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.4, caption=VIP score(A) and loading plot(B), figureFileSmall=P8J/HkU+UDrWWz4oq8QflA==, figureFileBig=8U24bUslpjg5Rhb4nnAbiA==, tableContent=null), ArticleFig(id=1239250720365531831, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图4, caption=VIP得分图(A)和载荷图(B), figureFileSmall=P8J/HkU+UDrWWz4oq8QflA==, figureFileBig=8U24bUslpjg5Rhb4nnAbiA==, tableContent=null), ArticleFig(id=1239250720453612220, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.5, caption=Heatmap, figureFileSmall=lg8WGQxXjFmctYUhW/wo3w==, figureFileBig=D5gB3pZ+alOM7A/v3l+k0g==, tableContent=null), ArticleFig(id=1239250720558469824, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图5, caption=热图, figureFileSmall=lg8WGQxXjFmctYUhW/wo3w==, figureFileBig=D5gB3pZ+alOM7A/v3l+k0g==, tableContent=null), ArticleFig(id=1239250720654938823, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.6, caption=Correlation heatmap, figureFileSmall=KpmqFbWA/FmKHihUFSl4SA==, figureFileBig=6Halz+hRMdp27kavCU3nRg==, tableContent=null), ArticleFig(id=1239250720763990729, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图6, caption=相关性热图, figureFileSmall=KpmqFbWA/FmKHihUFSl4SA==, figureFileBig=6Halz+hRMdp27kavCU3nRg==, tableContent=null), ArticleFig(id=1239250720898208465, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.7, caption=PCA score plot of different rubbers(A) and heatmap of different rubbers(B), figureFileSmall=8XcLqm0WVpPpfURcvuruQg==, figureFileBig=jqdtf+45WU3JNiKVrmd/eA==, tableContent=null), ArticleFig(id=1239250721061786329, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图7, caption=不同胶塞的PCA图(A)和不同胶塞的热图(B), figureFileSmall=8XcLqm0WVpPpfURcvuruQg==, figureFileBig=jqdtf+45WU3JNiKVrmd/eA==, tableContent=null), ArticleFig(id=1239250721179226846, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.8, caption=OPLS-DA score plot of two types of rubbers(A) and S-plot of two types of rubbers(B), figureFileSmall=jEO/qQ2LaWwNDaYRr26Lpg==, figureFileBig=aiGCrAqlIfICdNpJqHiKxw==, tableContent=null), ArticleFig(id=1239250721254724321, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图8, caption=两大类胶塞的OPLS-DA图(A)和S-plot图(B), figureFileSmall=jEO/qQ2LaWwNDaYRr26Lpg==, figureFileBig=aiGCrAqlIfICdNpJqHiKxw==, tableContent=null), ArticleFig(id=1239250721359581926, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Fig.9, caption=Volcano plot of the difference between the two types of rubbers, figureFileSmall=sPtJnkz2kXVEqxCSaGJRfg==, figureFileBig=2DOfyKETckorecPO+wE9ng==, tableContent=null), ArticleFig(id=1239250721481216750, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=图9, caption=两大类胶塞中差异物的火山图, figureFileSmall=sPtJnkz2kXVEqxCSaGJRfg==, figureFileBig=2DOfyKETckorecPO+wE9ng==, tableContent=null), ArticleFig(id=1239250722974388980, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Tab.1, caption=

UHPLC-MS gradient for positive ion mode

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时间
(time)/min
流速
(flow rate)/(mL·min-1
流动相比例(ratio of mobile phase)/%
流动相
(mobile phase) A
流动相
(mobile phase) B
00.35955
10.35955
240.350100
280.350100
28.10.35955
300.35955
), ArticleFig(id=1239250723100218107, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=表1, caption=

离子模式的梯度程序

, figureFileSmall=null, figureFileBig=null, tableContent=
时间
(time)/min
流速
(flow rate)/(mL·min-1
流动相比例(ratio of mobile phase)/%
流动相
(mobile phase) A
流动相
(mobile phase) B
00.35955
10.35955
240.350100
280.350100
28.10.35955
300.35955
), ArticleFig(id=1239250723184104193, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Tab.2, caption=

UHPLC-MS gradient for nagative ion mode

, figureFileSmall=null, figureFileBig=null, tableContent=
时间
(time)/min
流速
(flow rate)/(mL·min-1
流动相比例(ratio of mobile phase)/%
流动相
(mobile phase) C
流动相
(mobile phase) D
00.35982
10.35982
180.350100
220.350100
22.10.35982
250.35982
), ArticleFig(id=1239250723259601673, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=表2, caption=

负离子模式的梯度程序

, figureFileSmall=null, figureFileBig=null, tableContent=
时间
(time)/min
流速
(flow rate)/(mL·min-1
流动相比例(ratio of mobile phase)/%
流动相
(mobile phase) C
流动相
(mobile phase) D
00.35982
10.35982
180.350100
220.350100
22.10.35982
250.35982
), ArticleFig(id=1239250723381236494, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Tab.3, caption=

Different compounds in different extraction solvents

, figureFileSmall=null, figureFileBig=null, tableContent=
No.化合物
(compound)
VIP值
(VIP score)
No.化合物
(compound)
VIP值
(VIP score)
1PEG9-(CH2)11-CH3-NH41.929 715PEG12-(CH2)11-CH3-NH41.434 2
2PEG14-(CH2)11-CH3-NH41.906 816PEG6-(CH2)11-CH3-NH41.390 2
3PEG13-Ph-(CH2)8-CH3-NH41.670 417Didodecyl 3,3-sulphinylbispropionate1.350 9
4PEG13-(CH2)12-CH3-NH41.663 818PEG6-(CH2)17-CH3-NH41.344 7
5PEG14-(CH2)12-CH3-NH41.660 319PPG9-NH41.344 1
6PEG11-(CH2)11-CH3-NH41.624 120PEG12-(CH2)13-CH3-NH41.315 1
7PEG7-(CH2)11-CH3-NH41.613 821PPG13-NH41.266 1
8PEG8-(CH2)11-CH3-NH41.587222Nylon 66 degradant -2581.254 2
9PEG12-Ph-(CH2)8-CH3-NH41.556 823PEG8-(CH2)12-CH3-NH41.222 8
10PEG10-(CH2)12-CH3-NH41.505 924PEG12-(CH2)17-CH3-NH41.219 4
11PEG9-(CH2)12-CH3-NH41.501 725Butyl benzyl phthalate1.217 6
12PET Acyclic Trimer-H1.474 626PEG7-(CH2)12-CH3-NH41.204 9
13PEG14-Ph-(CH2)8-CH3-NH41.455 727PEG14-(CH2)13-CH3-NH41.203 3
143,5-di-tert-butyl-4-hydroxybenzaldehyde BHT-CHO1.450 8
), ArticleFig(id=1239250723469316885, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=表3, caption=

不同提取溶液中的差异化合物

, figureFileSmall=null, figureFileBig=null, tableContent=
No.化合物
(compound)
VIP值
(VIP score)
No.化合物
(compound)
VIP值
(VIP score)
1PEG9-(CH2)11-CH3-NH41.929 715PEG12-(CH2)11-CH3-NH41.434 2
2PEG14-(CH2)11-CH3-NH41.906 816PEG6-(CH2)11-CH3-NH41.390 2
3PEG13-Ph-(CH2)8-CH3-NH41.670 417Didodecyl 3,3-sulphinylbispropionate1.350 9
4PEG13-(CH2)12-CH3-NH41.663 818PEG6-(CH2)17-CH3-NH41.344 7
5PEG14-(CH2)12-CH3-NH41.660 319PPG9-NH41.344 1
6PEG11-(CH2)11-CH3-NH41.624 120PEG12-(CH2)13-CH3-NH41.315 1
7PEG7-(CH2)11-CH3-NH41.613 821PPG13-NH41.266 1
8PEG8-(CH2)11-CH3-NH41.587222Nylon 66 degradant -2581.254 2
9PEG12-Ph-(CH2)8-CH3-NH41.556 823PEG8-(CH2)12-CH3-NH41.222 8
10PEG10-(CH2)12-CH3-NH41.505 924PEG12-(CH2)17-CH3-NH41.219 4
11PEG9-(CH2)12-CH3-NH41.501 725Butyl benzyl phthalate1.217 6
12PET Acyclic Trimer-H1.474 626PEG7-(CH2)12-CH3-NH41.204 9
13PEG14-Ph-(CH2)8-CH3-NH41.455 727PEG14-(CH2)13-CH3-NH41.203 3
143,5-di-tert-butyl-4-hydroxybenzaldehyde BHT-CHO1.450 8
), ArticleFig(id=1239250723553202971, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=EN, label=Tab.4, caption=

Difference between the two kinds of rubbers

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 (compound)FClog2(FC)raw.pval-log10p
PEG7-(CH2)17-CH3-NH40.111 93-3.159 36.18×10-1615.209
PEG6-(CH2)17-CH3-NH40.125 05-2.999 45.92×10-1312.227
PEG8-(CH2)12-CH3-NH40.242 57-2.043 54.53×10-1110.344
PEG12-(CH2)12-CH3-NH40.268 58-1.896 61.86×10-109.730 9
PPG13-NH40.309 23-1.693 23.45×10-109.462 4
PEG13-(CH2)12-CH3-NH40.294 85-1.761 95.29×10-109.276 8
PEG11-(CH2)12-CH3-NH40.239 1-2.064 36.21×10-109.207 1
PEG4-CH2COOH-NH42.276 41.186 76.76×10-109.169 8
PEG10-(CH2)12-CH3-NH40.302 87-1.723 26.95×10-109.157 8
PEG9-(CH2)11-CH3-NH4784.19.614 94.56×10-98.341 2
PEG6-CH3-NH40.403 3-1.310 16.40×10-98.194 1
PEG14-(CH2)12-CH3-NH40.330 48-1.597 41.41×10-87.850 4
PEG9-(CH2)12-CH3-NH40.238 14-2.070 11.75×10-87.757 8
Butyl benzyl phthalate2.627 11.393 52.26×10-65.646
PEG11-(CH2)11-CH3-NH4263.268.040 36.51×10-65.186 6
PEG7-(CH2)12-CH3-NH40.035 907-4.799 61.24×10-54.906 4
Nylon 66 degradant-2592.280 31.189 21.62×10-54.789 8
Didodecyl 3,3-sulphinylbispropionate0.438 87-1.188 10.001 212.917 1
PEG4-(CH2)11-CH3-NH48.295 23.052 30.002 8042.552 3
Linoleic acid-H3.244 11.697 80.005 0442.297 2
PEG12-(CH2)11-CH3-NH412.2073.609 70.009 9932.000 3
PEG10-(CH2)13-CH3-NH465.6176.0360.011 6961.932
3,5-di-tert-butyl-4-hydroxybenzaldehyde BHT-CHO2.599 71.378 40.019 3321.713 7
PEG6-(CH2)11-CH3-NH43.961 81.986 20.026 2871.580 3
PEG11-(CH2)13-CH3-NH427.8394.7990.042 9641.366 9
), ArticleFig(id=1239250723645477664, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1239250707862311047, language=CN, label=表4, caption=

两大类胶塞中差异物

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 (compound)FClog2(FC)raw.pval-log10p
PEG7-(CH2)17-CH3-NH40.111 93-3.159 36.18×10-1615.209
PEG6-(CH2)17-CH3-NH40.125 05-2.999 45.92×10-1312.227
PEG8-(CH2)12-CH3-NH40.242 57-2.043 54.53×10-1110.344
PEG12-(CH2)12-CH3-NH40.268 58-1.896 61.86×10-109.730 9
PPG13-NH40.309 23-1.693 23.45×10-109.462 4
PEG13-(CH2)12-CH3-NH40.294 85-1.761 95.29×10-109.276 8
PEG11-(CH2)12-CH3-NH40.239 1-2.064 36.21×10-109.207 1
PEG4-CH2COOH-NH42.276 41.186 76.76×10-109.169 8
PEG10-(CH2)12-CH3-NH40.302 87-1.723 26.95×10-109.157 8
PEG9-(CH2)11-CH3-NH4784.19.614 94.56×10-98.341 2
PEG6-CH3-NH40.403 3-1.310 16.40×10-98.194 1
PEG14-(CH2)12-CH3-NH40.330 48-1.597 41.41×10-87.850 4
PEG9-(CH2)12-CH3-NH40.238 14-2.070 11.75×10-87.757 8
Butyl benzyl phthalate2.627 11.393 52.26×10-65.646
PEG11-(CH2)11-CH3-NH4263.268.040 36.51×10-65.186 6
PEG7-(CH2)12-CH3-NH40.035 907-4.799 61.24×10-54.906 4
Nylon 66 degradant-2592.280 31.189 21.62×10-54.789 8
Didodecyl 3,3-sulphinylbispropionate0.438 87-1.188 10.001 212.917 1
PEG4-(CH2)11-CH3-NH48.295 23.052 30.002 8042.552 3
Linoleic acid-H3.244 11.697 80.005 0442.297 2
PEG12-(CH2)11-CH3-NH412.2073.609 70.009 9932.000 3
PEG10-(CH2)13-CH3-NH465.6176.0360.011 6961.932
3,5-di-tert-butyl-4-hydroxybenzaldehyde BHT-CHO2.599 71.378 40.019 3321.713 7
PEG6-(CH2)11-CH3-NH43.961 81.986 20.026 2871.580 3
PEG11-(CH2)13-CH3-NH427.8394.7990.042 9641.366 9
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拟靶向代谢组学法分析胶塞中的可提取物*
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沈好文 1, 2, 5 , 肖梦晴 3 , 孟海涛 4 , 冷向阳 3 , 严方 5, **
药物分析杂志 | 安全监测 2024,44(4): 637-648
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药物分析杂志 | 安全监测 2024, 44(4): 637-648
拟靶向代谢组学法分析胶塞中的可提取物*
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沈好文1, 2, 5 , 肖梦晴3, 孟海涛4, 冷向阳3, 严方5, **
作者信息
  • 1.江苏省医疗器械检验所,南京 210019
  • 2.国家药品监督管理局药品包装材料与药物相容性研究重点实验室,南京 210019
  • 3.上海爱博才思分析仪器有限公司,上海 200050
  • 4.岛津企业管理(中国)有限公司,上海 200233
  • 5.中国药科大学药学院,南京 211198
  • Tel:13801591267;E-mail:

通讯作者:

** Tel:13851786026;E-mail:
Analysis of extractables in rubber with pseudotargeted metabolomics method*
Hao-wen SHEN1, 2, 5 , Meng-qing XIAO3, Hai-tao MENG4, Xiang-yang LENG3, Fang YAN5, **
Affiliations
  • 1.Jiangsu Institute of Medical Device Testing, Nanjing 210019, China
  • 2.Key Laboratory of Pharmaceutical Packaging Materials and Compatibility Technologyo of NMPA, Nanjing 210019, China
  • 3.Sciex China Co., Ltd., Shanghai 200050, China
  • 4.Shimadzu (China) Co., Ltd., Shanghai 200233, China
  • 5.School of Pharmacy, China Pharmaceutical University, Nanjing 211198, China
出版时间: 2024-04-30 doi: 10.16155/j.0254-1793.2024.04.11
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目的:

运用拟靶向代谢组学的方法对胶塞中的可提取物进行全面的分析。

方法:

以水、pH 2.6磷酸盐缓冲液、pH 9.18磷酸盐缓冲液、15%乙醇溶液分别对6种胶塞进行提取,制备质量控制(QC)溶液和供试品溶液。采用LC-30A超高效液相色谱仪-Q TOF-9030质谱ESI+/ESI-模式检测,使用Waters Acquity BEH C8/HSS T3色谱柱,以含0.1%甲酸的水-含0.1%甲酸的乙腈/含0.05%碳酸氢铵的水-含0.05%碳酸氢铵和5%水的甲醇作为流动相,运用TOF MS-和MS/MS DDA扫描模式对QC溶液进行检测。用MSConvert及MRM-Ion_Pair_Finder软件处理QC溶液的扫描结果,获得MRM参数。用ExionLC超高效液相色谱仪-Qtrap6500+质谱ESI+/ESI-模式检测,流动相和色谱柱同前,运用Scheduled-MRM扫描模式对提取液进行检测。

结果:

对1 399个未知物和116个已知物进行了分析,按提取液分类,发现pH 9.18磷酸盐缓冲液和15%乙醇溶液能提取出较多的化合物,找出了27个在不同提取液中差异较大的化合物;按胶塞分类,通过25个差异物,判断了不同胶塞的亲缘关系。

结论:

本研究对6种胶塞在4种提取物下的提取结果进行了分析。在不同的提取条件下,提取物之间存在差异。针对这些重点差异物可以专门制定分析方法进行质控跟踪研究,以确保药物质量的稳定和一致性。同时也分析了不同胶塞中的差异物,可以用来对未知胶塞样本进行大致的类别判断。

胶塞  /  拟靶向代谢组学  /  可提取物  /  液质联用  /  重点差异物  /  质量控制  /  类别判断
Objective:

To perform a comprehensive analysis of extractables in rubber by pseudotargeted metabolomics.

Methods:

The quality control(QC) solutions and test solutions were prepared by extracting the six kinds of rubbers with water, pH 2.6 phosphate buffer, pH 9.18 phosphate buffer, and 15% ethanol solution, respectively. The QC solutions were detected by LC-30A ultra performance liquid chromatography-Q TOF-9030 mass spectrometer in ESI+/ESI- mode. The mobile phases were 0.1% formic acid-water and 0.1% formic acid-acetonitrile/0.05% ammonium-water and 0.05% ammonium -5% water-methanol. The separation chromatographic column was Waters Acquity BEH C8/HSS T3. TOF MS and MS/MS DDA scanning modes were used to detect the QC solutions. The scan results of QC solution were processed with MSConvert and MRM-Ion_Pair_Finder software to obtain MRM parameters. The extracts were detected by ExionLC UPLC-Qtrap6500+ mass spectrometer in ESI+/ESI- mode with the same mobile phase and column as before, and Scheduled-MRM scan mode was applied to detect the extracts.

Results:

The 1 399 unknown compounds and 116 known compounds were analyzed. By extraction solution, it was found that pH 9.18 phosphate buffer and 15% ethanol solution could extract more compounds, and 27 compounds with large differences in different extraction solutions were identified. By rubbers, the affinities of different rubbers were determined by 25 differences.

Conclusion:

In this study, the results of the extraction of six rubbers under four extracts are analyzed. There are differences between extracts under different extraction conditions. Analytical methods can be specifically developed for these key variables for quality control follow-up studies to ensure the stability and consistency of drug quality. The variables in different rubbers are also analyzed, which can be used to make a general class determination of unknown rubber samples.

rubber  /  pseudotargeted metabolomics  /  extractable  /  liquid chromatography-tandem mass spectrometry  /  key differential substances  /  quality control  /  class determination
沈好文, 肖梦晴, 孟海涛, 冷向阳, 严方. 拟靶向代谢组学法分析胶塞中的可提取物*. 药物分析杂志, 2024 , 44 (4) : 637 -648 . DOI: 10.16155/j.0254-1793.2024.04.11
Hao-wen SHEN, Meng-qing XIAO, Hai-tao MENG, Xiang-yang LENG, Fang YAN. Analysis of extractables in rubber with pseudotargeted metabolomics method*[J]. Chinese Journal of Pharmaceutical Analysis, 2024 , 44 (4) : 637 -648 . DOI: 10.16155/j.0254-1793.2024.04.11
胶塞是药品包装材料的重要组成部分之一,在包装系统中有着重要的作用。胶塞的质量、安全性、使用性能以及与药品之间的相容性对药品有着十分重要的影响。其性能好坏,直接影响着药品质量和用药的安全[1-2]
药品与胶塞长期接触后,由于胶塞的原辅料、配方及生产工艺不同,可能导致不恰当的材料引起内部成分的迁移,吸附药品活性成分甚至发生化学反应,使药物失效,有的还会对人体产生严重的副作用[2]。胶塞常用于注射剂的包装,由于注射液给药后直接进入人体,如果其存在质量或相容性问题,后果将会更加严重[3]
为此,国家食品药品监督管理局于2004年发布了《直接接触药品的包装用材料和容器管理办法》[4],2012年发布了《化学药品注射剂与塑料包装材料相容性研究技术指导原则》[5],2015年发布了《化学药品注射剂与药用玻璃包装容器相容性研究技术指导原则(试行)》[6],2018年发布了《化学药品与弹性体密封件相容性研究技术指导原则(试行)》[7]等一系列规定及指导原则,以保证用药的安全性、有效性和均一性。在国际上,欧洲药品管理局(European Medicine Agency,EMA)、美国食品药品管理局(Food and Drug Administration,FDA)、USP通则<381><1381><1663><1664>[8]等对药包材也制定了一系列的要求。
胶塞通常由生胶和助剂组成,常见助剂有抗氧剂、硫化剂、促进剂、活化剂、增塑剂、填充剂、着色剂等[9]。由于助剂众多,成分复杂,在可提取物研究中存在很多困难,主要有3个问题:①过多成分,含量也各不相同,给半定量测定带来很多困难;②众多成分不利于比较不同厂家、不同类型、不同提取条件获得的可提取物的区别以及安全性评价;③绝大多数可提取物没有对照品,鉴定和定量都难以实现。
目前,现有研究通常是基于某些特定的化合物的分析,尚未看到有从全局的角度对胶塞中的可提取物进行分析和评价的研究。这显然对于药品的安全监管是不利的,也不符合《化学药品与弹性体密封件相容性研究技术指导原则(试行)》的要求,本研究从全局入手,分析可提取物中的全部物质,寻找不同来源及提取、浸出条件带来的差异,对含量变化显著的物质进行重点监控,从而对胶塞的质量以及与药物的相容性做出安全性评价。
为了完成此项工作,本研究引入代谢组学(metabonomics/metabolomics)的思路进行分析。代谢组学是效仿基因组学和蛋白质组学的研究思想,对生物体内所有代谢物进行定量分析,并寻找代谢物与生理病理变化的相对关系的研究方式[10]。传统的代谢组学主要分为非靶向(non-targeted metabolomics)和靶向(targeted metabolomics)分析策略,前者一般使用高分辨质谱获得丰富的代谢物信息,但存在数据复杂、重复性差、线性范围窄等缺点[11-13];后者一般使用三重四极杆质谱,数据质量有很大提高,但通常只检测已知代谢物,覆盖度低[14-16]。中国科学院大连化学物理研究所的许国旺研究员结合以上2种方法,开发了一种新的名为拟靶向代谢组学 (pseudotargeted metabolomics)[17]的方法。该方法结合了非靶向的高覆盖、全扫描精确分子量定性和靶向的多反应监测(MRM)精确量化的优点,可以对大量的未知化合物进行快速的定性定量分析。本研究将运用此方法运对胶塞提取物进行分析。
LC-30A+QTOF-9030液质联用仪(岛津公司),ExionLC-Qtrap6500+液质联用仪(Sciex公司),3870ELV蒸汽灭菌锅(Tuttnauer公司),MS205DU十万分之一电子分析天平(Mettler Toledo公司)。
质谱纯甲醇、质谱纯乙腈、色谱纯乙腈购自Thermo Fisher公司,色谱纯碳酸氢铵购自Sigma-Aldrlch公司,pH 2.6磷酸盐缓冲液、pH 9.18磷酸盐缓冲液购自Mettler Toledo公司,水为本实验室自制超纯水。
注射液用覆盖四氟乙烯/六氟丙烯的共聚膜氯化丁基橡胶塞(16号样品)、注射用冷冻干燥用聚对二甲苯镀膜溴化丁基橡胶塞(17号样品)、注射液用乙烯-四氟乙烯共聚物覆膜卤化丁基橡胶塞(溴化)(18号样品)、注射用冷冻干燥用乙烯-四氟乙烯共聚物覆膜卤化丁基橡胶塞(氯化)(19号样品)、注射用冷冻干燥用乙烯-四氟乙烯共聚物覆膜卤化丁基橡胶塞(溴化)(20号样品)、注射液用乙烯-四氟乙烯共聚物覆膜卤化丁基橡胶塞(氯化)(21号样品)。
水(1号提取溶液)、pH 2.6磷酸盐缓冲液(2号提取溶液)、pH 9.18磷酸盐缓冲液(3号提取溶液)、15%乙醇溶液(4号提取溶液)。
取“1.2”项下各胶塞,剪碎,混合,置具盖聚四氟乙烯瓶中,以0.6 g·mL-1的浓度加入水-pH 2.6磷酸盐缓冲液-pH 9.18磷酸盐缓冲液-15%乙醇溶液混合溶液(1∶1∶1∶1),密封后放入蒸汽灭菌器(121 ℃)中加热30 min,取出后用0.22 μm滤膜过滤,取滤液作为QC溶液。同时不加样品同此操作,制得QC空白液。
取“1.2”项下各胶塞,剪碎,分别置具盖聚四氟乙烯瓶中,以0.2 g·mL-1的浓度分别加入水、pH 2.6磷酸盐缓冲液、pH 9.18磷酸盐缓冲液、15%乙醇溶液,密封后放入蒸汽灭菌器(121 ℃)中加热30 min,取出后用0.22 μm滤膜过滤,取滤液作为供试品溶液。同时不加样品同此操作,制得阴性样品溶液。
非靶向分析引用中科院大连化学物理研究所许国旺研究员的拟靶向代谢组学[17]的方法,在UHPLC-Q TOF MS系统完成,该系统由岛津公司的LC-30A超高效液相色谱仪和QTOF-9030质谱仪串联而成。
采用Waters Acquity BEH C8 column(100 mm×2.1 mm,1.7 μm)色谱柱,以含0.1%甲酸的水(A)-含0.1%甲酸的乙腈(B)为流动相,梯度程序见表1,柱温50 ℃,进样量5 μL。
采用电喷雾离子源(ESI源),以正离子模式进行检测,接口电压4.0 kV,接口温度300 ℃。脱溶剂管(DL)温度250 ℃、干燥气和加热气流速均设置为10 L·min-1。采用MS和MS/MS DDA采集模式,每个循环内进行1次一级母离子全扫描,并对信号响应前20的一级母离子进行二级子离子扫描。前体离子和产物离子的质荷比(m/z)扫描范围为50~1 250。CE值分别为15、30和45 V。
采用Waters Acquity HSS T3 column(100 mm×2.1 mm,1.8 μm)色谱柱,以含0.05%碳酸氢铵的水(C)-含0.05%碳酸氢铵和5%水的甲醇(D)为流动相,梯度程序见表2,柱温55 ℃,进样量5 μL。
采用电喷雾离子源(ESI源),以负离子模式进行检测,接口电压-3.5 kV,接口温度300 ℃。脱溶剂管(DL)温度250 ℃、干燥气和加热气流速均设置为10 L·min-1。采用MS和MS/MS DDA采集模式,每个循环内进行1次一级母离子全扫描,并对信号响应前20的一级母离子进行二级子离子扫描。前体离子和产物离子的质荷比(m/z)扫描范围为50~1 250。CE值分别为-15、-30和-45 V。
取“2.1”项下的QC溶液和QC空白液,分别按照“2.2.1”和“2.2.2”项下条件,进行测定。
将正离子模式下测得的数据文件导入MSDIAL软件,删除多余的同位素锋后进行峰对齐操作,生成峰表。将正离子模式下测得的数据文件导入MSConvert软件,转化成mgf文件。将峰表和mgf文件导入R语言程序MRM-Ion_Pair_Finder,获得正离子模式下的MRM离子对列表。同法操作获得负离子模式下的MRM离子对列表。
候选离子对验证方法来源同“2.2”项,在UHPLC-QqQ MS系统完成,该系统由Sciex公司的ExionLC超高效液相色谱仪和Sciex公司的Qtrap6500+三重四极杆质谱仪组成。
色谱条件同“2.2.1.1”,质谱条件采用电喷雾离子源(ESI源),以正离子模式进行检测,喷雾电压5.5 kV,离子源温度550 ℃。气帘气(curtain gas)、雾化气(gas 1)和干燥气(gas 2)分别设置为0.24、0.38和0.38 MPa。采用Scheduled-MRM模式进行扫描,MRM信息由“2.2.3”项下方法获得。
色谱条件同“2.2.2.1”,质谱条件采用电喷雾离子源(ESI源),以负离子模式进行检测,喷雾电压-4.5 kV,离子源温度550 ℃。气帘气(curtain gas)、雾化气(gas 1)和干燥气(gas 2)分别设置为0.24、0.38和0.38 MPa。采用Scheduled-MRM模式进行扫描,MRM信息由“2.2.3”项下方法获得。
建立拟靶向方法的工作流程如图1所示。
首先,按“2.1”项制备出供试品溶液和QC溶液。然后,将QC溶液注入UHPLC-Q TOF MS系统中,运用数据依赖型扫描获得所有化合物的一、二级质谱数据。以正离子模式为例,对QC溶液进行了3次扫描(CE值分别为15、30、45 V,其余参数不变)。通过对比同一物质在不同CE值扫描出的二级信号,选取强度最高的峰和此时的CE值作为MRM参数中的Q3和CE值,Q1则为此物质的一级质荷比。另外,由于此方法同时检测的MRM离子对较多,为保证数据质量,采用了动态MRM模式(dynamic MRM/Scheduled-MRM)。具体做法是将母离子的保留时间也添加至MRM参数列表中,这样仪器只在保留时间附近对该MRM离子对进行扫描,从而可以在1个分析周期内覆盖更多的化合物。本次研究在2个不同质谱平台检测时,色谱端硬件及软件条件完全一致,所以保证了保留时间的一致。以上工作由MSConvert及MRM-Ion_Pair_Finder软件完成[18]
按照“2.2.3”项下方法,获得待测物的MRM离子对,共计1 399个未知物,理论上覆盖了此方法能够检测出的全部物质。由于本方法的QC溶液浓度是供试品溶液的3倍,并且可以直接从化合物的一、二级质谱数据中获取MRM参数,相对传统方法能够获得更多的离子对信息。在上述离子对中,通过谱库搜索和人工解谱,共鉴定出116个已知物。与传统方法相比,该方法能够获得更多的备选物质[19-20]
按照“2.3”项下内容,使用UHPLC-QqQ MS系统对待测样品进行靶向检测,分别用扫描获得的未知和已知MRM离子对,并将得到的结果进行数据分析。
分别对已知和未知离子对的扫描结果,按不同提取溶液进行分组,取每个MRM通道的峰面积作为变量,通过主成分分析(PCA)技术进行分析,结果(图2)在空间上可明显区分,聚类趋势明显,说明在种类、数量和浓度方面具有显著差异。其中3号提取溶液和其他提取溶液距离较远,说明胶塞在碱性提取液的条件下的提取物与其他条件区别较大,值得重点关注。
由非监督模式PCA判别组别后,采用有监督模式的偏最小二乘法(PLS-DA)对进行数据分析(图3),可有效降低系统噪声的干扰,更易于找到各提取溶液间差异性萃取标志物。对已知离子对的结果经5次循环交互验证(5-fold cross-validation)得到的模型评价参数,本研究数据建立的PLS-DA模型的R2为0.993,Q2为0.765,说明该模型具有较好的拟合性和预测性。
本研究利用PLS-DA模型得到的VIP值来衡量各代谢物的对各组样本分类判别的影响强度和解释能力,并且通过载荷图帮助评估PLS-DA模型(图4),挖掘具有统计意义的差异性物质(表3)。统计分析参数设置VIP>1.2,P<0.05的为显著差异物质,共筛选出27个差异明显的化合物。
为进一步整体表征差异,不同提取溶液下的整体分布变化,进行了heat map热图分析(图5)。从结果可明显看出4号提取溶液(15%乙醇溶液)对PEG12-(CH2)11-CH3、PEG11-(CH2)11-CH3、PEG9-(CH2)11-CH3、PPG 11、PEG11-(CH2)14-CH3、PEG8-Ph-(CH2)8-CH3、PEG7-Ph-(CH2)8-CH3、PEG14-Ph-(CH2)8-CH3、PEG12-Ph-(CH2)8-CH3、PEG13-Ph-(CH2)8-CH3;采用3号提取溶液(pH 9.18磷酸盐缓冲液)则Nylon 66 degradant、PEG3-(CH2)8-CH3、PEG5、PEG10、PEG11、PEG6、PEG9、PEG7,PEG8、PEG12、PEG13更易于萃取。采用1号提取溶液(水)和2号提取溶液(pH 2.6磷酸盐缓冲液)则上述物质出现较少。为进一步探究不同化合物之间萃取关联性分析,进行了相关性热图分析(图6),由结果可知,PEG和烷烃化PEG呈负相关性,在提取溶液的选择上,烷基化PEG在4号溶液(15%乙醇溶液)更容易提取出,跟实际使用上相对应。
包装系统中含胶塞的药品可以用以上结果进行质控。质控时,以不同时期的迁移药液为研究对象,可直接采用“2.3.1”及“2.3.2”项的色谱质谱条件,也可以在前述条件基础上删除多余的MRM离子对,只保留热图中的物质。重点关注在不同条件下上述物质的峰面积变化情况,并根据毒理学数据及实际情况确定允许的浓度范围。
对已知离子对的扫描结果,按不同胶塞进行分组,取每个MRM通道的峰面积作为变量,对样品进行PCA。结果显示在无监督情况下,16、17、19、21号胶塞和18、20号胶塞明显自然分为两大簇类,通过热图分析(图7)也可知,18、20号亲缘关系较近,16、19、21号亲缘关系较近。通过比对胶塞种类也可知,18和20号均为乙烯-四氟乙烯共聚物覆膜卤化丁基橡胶塞(溴化)、16、19、21均为氯化丁基橡胶,且17号溴化丁基橡胶和20和21号胶塞亲缘关系接近。
为进一步考察,将所有分析的胶塞分为两大类,16、17、19、21(Ⅰ类);18、20(Ⅱ类),采用监督模式的OPLS-DA进行数据分析。根据结果,在第一主成分轴上明显分开,说明Ⅰ类胶塞成分上明显区别于Ⅱ类胶塞。本研究数据建立的OPLS-DA模型的R2Y为0.806,R2Q均为0.781,说明该模型具有较好的拟合性和预测性(图8)。
为找出两大类胶塞间的潜在差异化学标志物,进行扩展统计分析得到S-plot图。利用OPLS-DA模型得到的VIP来衡量各提取化合物对各组样本分类判别的影响强度和解释能力。本实验中,设置统计分析VIP>1,|fold charge|>2,T test P<0.1认为具有显著差异,共筛选出25个物质(图9表4)。考虑到同类胶塞的组分、配方及工艺均有可能不同,这些差异物质直接对胶塞的分类进行判断可能会导致结果不准确,但可以结合其他信息进行辅助验证。
非靶向方法一般使用高分辨质谱,不需要对可能存在的化合物有太多了解,并且理论上可以检测所用方法可分析的所有化合物。通过全扫描可以获得可分析的化合物的质谱特征,但是非靶向方法的定量性能不如三重四极杆质谱中基于MRM的靶向方法。靶向方法使用三重四极杆质谱,通常用于验证阶段,可用于目标代谢物的绝对定量。一般需要非靶向的数据支撑或是根据现有文献报道确定目标化合物。另外,靶向方法需要对照品来确定要使用的MRM离子对。
以上2个方法均有不足之处,现在很多研究将二者结合起来以对目标物进行更加相对全面的分析和评价。但是,依然有不少问题需要解决,拟靶向方法就是一种具有更高灵敏度、更高特异性和出色定量能力的替代方法。
传统非靶向方法在对样品进行全扫描的过程中,由于硬件性能的限制,线性范围较窄,一般只有103的数量级。具体而言,就是对于低浓度化合物响应较差,容易检测不到;对于高浓度化合物很容易在检测器中达到饱和,无法反映出各样品之间真实的差异性。为解决这一问题,本研究用高分辨质谱对QC溶液进行了全扫描,这样就获得了所有化合物的一、二级架构,也保证了灵敏度。然后,通过一系列的数据转化,在三重四极杆质谱中对样品中每个目标化合物用MRM的方式进行了检测,并且进行比对。该方法使用的MRM离子对完全来自待分析的样品,不需要对照品,这样无疑具有更高的覆盖率和更广泛的适用性。三重四极杆质谱的线性范围通常可以达到107的数量级,这样可以同时兼顾待测物中的高低浓度的目标化合物,相比非靶向扫描能够获得更多的信息。此外,在大规模样品的分析中,来自拟靶向代谢组学的数据很容易校准和整合来自不同分析批次的数据,不需要像非靶向方法那样复杂的特征检测或峰对齐过程。
通过不同提取溶液和胶塞的考察,可以推测出以下结果:
①胶塞与中性和酸性提取液的反应较温和,提取物少。在药物存储时,如果药液的pH为中性或酸性,搭配使用胶塞相对安全。
②对于胶塞的提取研究,建议优先采用碱性和有机溶液进行提取,这样可以获得更多的提取物,使得研究内容更加丰富多样。
③提取物中含量较高的物质,可用于药品质控。通过检测迁移药液中这些物质的含量,再结合毒理学数据可以判断胶塞是否适合特定药物。
④在相同溶液条件下,不同种类的胶塞所提取出的物质存在差异。因此,在胶塞分类时,可以考虑这一因素作为辅助判断依据。
本研究采用了拟靶向代谢组学的方法,对6种胶塞在4种提取溶液下的提取结果进行了深入分析。经研究发现,在不同的提取条件下,提取物之间存在差异。针对这些差异较大的物质可以专门制定分析方法进行质控跟踪研究,以确保药物质量的稳定和一致性。
此外,本研究还对不同胶塞中的差异物进行了分析。这些差异物可以用来佐证胶塞的类别,从而可以更好地理解不同类型胶塞之间的差异。通过这些研究,可以为药物生产过程中的胶塞选择和优化提供有力支持,保障药品的安全。
  • *江苏省药品监督管理局药品监管科学科研计划课题(202222)
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doi: 10.16155/j.0254-1793.2024.04.11
  • 首发时间:2026-03-13
  • 出版时间:2024-04-30
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  • 修回日期:2024-03-14
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*江苏省药品监督管理局药品监管科学科研计划课题(202222)
作者信息
    1.江苏省医疗器械检验所,南京 210019
    2.国家药品监督管理局药品包装材料与药物相容性研究重点实验室,南京 210019
    3.上海爱博才思分析仪器有限公司,上海 200050
    4.岛津企业管理(中国)有限公司,上海 200233
    5.中国药科大学药学院,南京 211198

通讯作者:

** Tel:13851786026;E-mail:
参考文献
分享链接
https://castjournals.cast.org.cn/joweb/ywfxzz/CN/10.16155/j.0254-1793.2024.04.11
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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