一个系统优化的两剂量差异化策略,集成稳定同位素跟踪和质量转移缺陷过,以减少基于高分辨率质谱的药物代谢物概况的错误阳性
Chang-Te Lin1, Yi-Shiou Chiou2, Ji-Rui Yang3
1Department of Urology, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi City, 60002, Taiwan.
Talanta
|March 3, 2026
概括
这项研究优化了使用稳定同位素追踪 (SIT) 和质量转移缺陷过 (MSDF) 的药物代谢物检测工作流. 改进的方法提高了代谢物识别的准确性,即使没有参考标准.
科学领域:
- 药理学 药理学是指药理学的学科.
- 分析化学 分析化学
- 代谢学 代谢学 代谢学
背景情况:
- 药物代谢物识别对于药物开发至关重要.
- 代谢学方法面临诸如高错误阳性率和缺乏参考标准等挑战.
- 稳定同位素追踪 (SIT) 和质量转移缺陷过 (MSDF) 提供了潜在的解决方案.
研究的目的:
- 优化数据处理工作流程,以改善药物代谢物检测和确认.
- 将两剂量差异化策略与SIT和MSDF整合起来.
- 为缺乏真正的参考标准的代谢物识别策略提供指导.
主要方法:
- 系统地优化数据处理工作流程.
- 两剂量差异化策略与稳定同位素追踪 (SIT) 和质量转移缺陷波器 (MSDF) 的整合.
- 使用同位素标记 (D0 / D3) 化合物和MS / MS碎片化用于代谢物确认.
主要成果:
- 总共有56个西尔代纳菲尔相关代谢物特征被假定地检测和证实.
- 与混合设置相比,分开的化设置产生了更多的代谢物特征.
- 确定了最佳分析参数:MSDF<0.12Da,保留时间宽容0.2分钟,以及三个配对样本.
结论:
- 开发的工作流是强大的,可扩展的,用于全面的药物代谢物概况.
- 实验设计,特别是避免混合同位素,对于基于SIT的代谢学至关重要.
- 本书为优化代谢物识别而没有真正的参考标准提供了实际指导.
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