1.华东理工大学 化学与分子工程学院,上海 200237
2.广东药科大学 广东省代谢病中西医结合研究中心(中医药研究所),广东 广州 510006
3.国家药品监督管理局药品快速检验技术重点实验室(广东省药品检验所), 广东 广州 510663
4.上海甘泓生物医学科技有限公司,上海 200131
肖雪,博士,副研究员,研究方向:中药质量研究、药品快检与过程分析,E-mail:erxiaohappy@163.com
章弘扬,博士,副教授,研究方向:LC-MS复杂体系分析新方法,E-mail:hongyang_zhang@ecust.edu.cn
收稿:2025-03-04,
修回:2025-04-12,
网络出版:2025-08-04,
纸质出版:2025-12-15
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李奕晓,陈苏微,周淳,胡坪,肖雪,章弘扬.基于UPLC-Q-TOF-MS/MS与自动解析算法的3种抗病毒药物快速筛检[J].分析测试学报,2025,44(12):2462-2469.
LI Yi-xiao,CHEN Su-wei,ZHOU Chun,HU Ping,XIAO Xue,ZHANG Hong-yang.Screening and Detection of Three Antiviral Drugs Based on UPLC-Q-TOF-MS/MS and Automatic Interpretation Algorithm[J].Journal of Instrumental Analysis,2025,44(12):2462-2469.
李奕晓,陈苏微,周淳,胡坪,肖雪,章弘扬.基于UPLC-Q-TOF-MS/MS与自动解析算法的3种抗病毒药物快速筛检[J].分析测试学报,2025,44(12):2462-2469. DOI: 10.12452/j.fxcsxb.250304144.
LI Yi-xiao,CHEN Su-wei,ZHOU Chun,HU Ping,XIAO Xue,ZHANG Hong-yang.Screening and Detection of Three Antiviral Drugs Based on UPLC-Q-TOF-MS/MS and Automatic Interpretation Algorithm[J].Journal of Instrumental Analysis,2025,44(12):2462-2469. DOI: 10.12452/j.fxcsxb.250304144.
该研究基于超高效液相色谱-四极杆-飞行时间串联质谱(UPLC-Q-TOF-MS/MS)技术建立了奈玛特韦、利托纳韦和奥司他韦的快速分析方法,对上述3种抗病毒药物进行了二级质谱碎裂机理精细分析。通过机器学习构建的自动解析算法实现了标样非依赖性鉴定,即使在血清1%加标水平下仍有100%检出率,对低丰度碎片离子表现出足够的识别能力。在模型测试中,该系统能有效区分目标化合物与基质干扰物,展现出良好的特异性。采用该方法成功从实际药品中分离鉴定出奈玛特韦、利托纳韦和奥司他韦,匹配得分均高于85。该研究为抗病毒药物质量监控提供了新思路和技术支持。
This study developed a method for rapid analysis of nirmatrelvir,ritonavir and oseltamivir based on ultra-high performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) technique. The MS/MS fragmentation mechanisms for these three antiviral drugs were studied in detail. An automatic interpretation algorithm built by machine learning enables standard-independent identification,with 100% detection rate even at 1% spiked level in serum. It showed sufficient recognition ability for low-abundance fragment ions. The system could effectively distinguish target compounds from matrix interferences. It demonstrated good specificity in the model test. Using this method,nirmatrelvir,ritonavir,and oseltamivir were successfully separated and identified in real drug samples with matching scores all above 85. This study thus provides new ideal and technical support for the quality supervision of antiviral drugs.
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