化学
吞吐量
产量(工程)
色谱法
设计质量
工艺工程
杂质
立体选择性
领域(数学)
组合化学
计算机科学
催化作用
有机化学
电信
工程类
物理化学
数学
粒径
冶金
材料科学
纯数学
无线
作者
Alexandre Goyon,Colin Masui,Lauren E. Sirois,Chong Han,Peter Yehl,Francis Gosselin,Kelly Zhang
出处
期刊:Analytical Chemistry
[American Chemical Society]
日期:2020-11-03
卷期号:92 (22): 15187-15193
被引量:11
标识
DOI:10.1021/acs.analchem.0c03754
摘要
Automated high-throughput experimentation (HTE) is a powerful tool for scientists to explore and optimize chemical transformations by simultaneously screening yield, stereoselectivity, and impurity profiles. To analyze the HTE samples, high-throughput analysis (HTA) platforms must be fast, accurate, generic, and specific at the same time. A large amount of high-quality data is critical for the success of machine learning models in the era of big data. Conventional chiral liquid chromatography–mass spectrometry (LC/MS) HTE methods are hampered by compound co-eluting, possible ion suppression, and limited chiral column lifetime in the presence of crude reaction mixtures or complex sample matrices. To overcome these limitations, a generic and fast achiral–chiral heart-cutting two-dimensional (2D)-LC method has been developed to determine both the yield and stereoselectivity of chemical transformations within a 10 min run time. Successful implementation of the 2D-LC HTA platform in a routine drug development environment was achieved for real-world project support, with the analysis so far of over 2000 reaction mixtures prepared in the 96-well plate format. Excellent performance of the method was demonstrated by relative standard deviation (RSD) lower than 0.83% for the 1D and 2D retention times, and determination coefficients higher than 0.99. The presented HTA 2D-LC platform has had a significant impact on drug development by analyzing the HTE samples rapidly with unambiguous peak tracking and providing a robust approach for accurately generating a large amount of high-quality data in a short time.
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