Suppr超能文献

使用基于芯片的纳米电喷雾串联质谱法验证符合法规的宽动态范围生物分析测定法。

Validating regulatory-compliant wide dynamic range bioanalytical assays using chip-based nanoelectrospray tandem mass spectrometry.

作者信息

Wickremsinhe Enaksha R, Ackermann Bradley L, Chaudhary Ajai K

机构信息

Lilly Research Laboratories, Lilly Corporate Center, Eli Lilly and Company, Indianapolis, IN 46285, USA.

出版信息

Rapid Commun Mass Spectrom. 2005;19(1):47-56. doi: 10.1002/rcm.1747.

Abstract

Automated chip-based infusion nanoelectrospray ionization coupled to tandem mass spectrometry (nanoESI-MS/MS) was used to validate a bioanalytical assay conforming to United States Food and Drug Administration (FDA) regulatory guidelines and Good Laboratory Practices (GLP). Reboxetine was used as the analyte fortified in dog plasma along with an analog internal standard (IS). The best nanoESI response for reboxetine was observed with 90% acetonitrile (ACN)/water without any mobile phase modifiers. The analyte and IS were extracted from dog plasma samples by liquid-liquid extraction (LLE). The supernatant was concentrated to dryness and redissolved in 90% ACN/water for nanoESI. Selected reaction monitoring (SRM) data were collected for all samples to generate ion current profiles with a base width of approximately 20 s. Selectivity experiments showed no interferences in blank plasma samples. Interferences as a result of in-source collision-induced dissociation of metabolites were not an issue due to the previously documented metabolism of reboxetine. Matrix suppression was evaluated across multiple lots of dog plasma as well as over different animal species (rabbit, rat, mouse) and different anticoagulants (heparin, EDTA). Matrix suppression ranged from approximately 30-60% across the different lots, species etc.; however, in all instances, the analyte and the IS were suppressed by similar amounts, suggesting the similarity in ionization properties between the two. A three-batch validation was performed (each batch consisting of four different concentrations, six replicates of each concentration) and demonstrated inter-assay accuracy (% relative error; RE) of less than +/-8% and an inter-assay precision (% relative standard deviation; RSD) of less than 7%, thus meeting regulatory guidelines. A comparison of analyses by nanoESI-MS/MS and liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) showed that nanoESI-MS/MS had a greater slope for the calibration standard curve compared to LC/MS/MS, indicating greater sensitivity for the former technique. It is also noteworthy that the amount of sample infused during nanoESI-MS/MS was approximately 80-fold less compared to the amount of sample injected during LC/MS/MS. The absence of carryover (attributed to the lack of a common fluid path) in the nanoESI technique enabled the extension of the assay linear dynamic range to 500,000-fold, and the possibility of analyzing samples in a single batch without the need for re-analysis of samples with high concentrations. This technology offers the possibility for increased throughput for studies supporting drug development by providing fast data turnaround for assays conforming to regulatory guidelines and GLPs.

摘要

基于芯片的自动进样纳米电喷雾电离串联质谱法(nanoESI-MS/MS)用于验证一项符合美国食品药品监督管理局(FDA)监管指南和良好实验室规范(GLP)的生物分析方法。以瑞波西汀作为分析物,与一种类似物内标(IS)一起加入犬血浆中进行强化。在不添加任何流动相改性剂的90%乙腈(ACN)/水体系中观察到瑞波西汀的纳米电喷雾响应最佳。通过液液萃取(LLE)从犬血浆样品中提取分析物和内标。将上清液浓缩至干,再用90% ACN/水重新溶解用于纳米电喷雾分析。对所有样品收集选择反应监测(SRM)数据,以生成基线宽度约为20秒的离子电流图谱。选择性实验表明空白血浆样品中无干扰。由于瑞波西汀先前已记录的代谢情况,代谢物的源内碰撞诱导解离产生的干扰不是问题。对多批犬血浆以及不同动物物种(兔、大鼠、小鼠)和不同抗凝剂(肝素、乙二胺四乙酸)评估了基质抑制情况。不同批次、物种等的基质抑制范围约为30 - 60%;然而,在所有情况下,分析物和内标受到的抑制程度相似,表明两者的电离性质相似。进行了三批次验证(每批次由四个不同浓度组成,每个浓度六个重复),结果显示批间准确度(%相对误差;RE)小于±8%,批间精密度(%相对标准偏差;RSD)小于7%,从而符合监管指南。纳米电喷雾串联质谱法(nanoESI-MS/MS)与液相色谱串联质谱法(LC/MS/MS)的分析比较表明,与LC/MS/MS相比,纳米电喷雾串联质谱法校准标准曲线的斜率更大,表明该技术灵敏度更高。还值得注意的是,纳米电喷雾串联质谱法进样的样品量比液相色谱串联质谱法进样的样品量少约80倍。纳米电喷雾技术不存在残留(归因于缺乏共同的流体路径),这使得该分析方法的线性动态范围扩展至500,000倍,并且有可能在单一批次中分析样品,而无需对高浓度样品进行重新分析。该技术通过为符合监管指南和良好实验室规范的分析提供快速的数据周转,为支持药物研发的研究提高通量提供了可能性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验