Automated development of an LC-MS/MS method for measuring multiple vitamin D metabolites using MUSCLE software
Automated development of an LC-MS/MS method for measuring multiple vitamin D metabolites using MUSCLE software
复制标题
DOI：
10.1039/c7ay00550d
复制
发表时间：
2017-05-14
影响因子：
3.1
通讯作者：
Hewison, Martin
中科院分区：
文献类型：
--
作者：
Jenkinson, Carl;Bradbury, James;Hewison, Martin
手动开发液相色谱串联质谱（LC-MS/MS）方法是分析实验室中的限速步骤，特别是如果几种化合物具有相同的多反应监测（MRM）转换。本研究描述了通过闭环实验（MUSCLE）软件的多平台无偏光谱优化的应用，以自动开发LC-MS/MS方法来测量维生素D的多种代谢物。与手动开发的方法相同的化合物的比较，用于评估肌肉在改善方法参数的有效性。LC和MS参数范围在MUSCLE中设定，其在全自动200个样品序列期间优化了方法。可视化脚本在每次样品运行后改变方法参数，而闭环多目标优化方法在整个序列中确定最佳仪器参数，以提高灵敏度和运行时间。使用MUSCLE开发的优化样品运行将10种代谢物的分析时间从8.2分钟缩短到6.2分钟。这是通过增加移动的相中的初始甲醇浓度和增加运行中有机移动的相的改变梯度来实现的。然而，MS参数不能进一步优化，以提高分析物的灵敏度超过手动优化，虽然在大多数情况下，肌肉证实了手动优化的条件。每种开发方法之间的比较表明，方法之间没有显着的分析物偏倚。MUSCLE已被证明可以自动化并提高多分析物维生素D LC-MS/MS方法的通量。该软件的使用可以应用于需要快速自动化方法开发的行业，如临床和制药实验室。
Manual development of liquid chromatography tandem-mass spectrometry (LC-MS/MS) methods is a rate limiting step in analytical laboratories, particularly if several compounds have the same multiple reaction monitoring (MRM) transitions. This study describes the application of Multi-platform Unbiased optimisation of Spectrometry via Closed-Loop Experimentation (MUSCLE) software to automate the development of an LC-MS/MS method to measure multiple metabolites of vitamin D. Comparison with a manually developed method for the same compounds was used to evaluate the effectiveness of MUSCLE in improving method parameters. LC and MS parameter ranges were set up in MUSCLE, which optimised the method during a fully-automated 200 sample sequence. Visual scripts altered method parameters after each sample run while a closed-loop multi-objective optimisation approach identified optimum instrument parameters throughout the sequence to improve sensitivity and run time. The optimised sample run developed using MUSCLE shortened analysis time for 10 metabolites from 8.2 minutes to 6.2 minutes. This was achieved by increased initial methanol concentration in the mobile phase and an altered gradient that increased the in-run organic mobile phase. However, MS parameters could not be optimised further to improve analyte sensitivity over manual optimisation, although in most cases MUSCLE confirmed the manually optimised conditions. Comparison between each of the developed methods showed no significant analyte bias between methods. MUSCLE has been shown here to automate and improve the throughput of a multiple analyte vitamin D LC-MS/MS method. Utilisation of this software could be applied to industries requiring fast automated method development such as clinical and pharmaceutical laboratories.