Fast gradient elution reversed-phase liquid chromatography with diode-array detection as a high-throughput screening method for drugs of abuse. II. Data analysis.
Fast gradient elution reversed-phase liquid chromatography with diode-array detection as a high-throughput screening method for drugs of abuse. II. Data analysis.
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快速梯度洗脱反相液相色谱与二极管阵列检测作为滥用药物的高通量筛选方法。
DOI：
10.1016/j.chroma.2006.10.024
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Carr,PeterW
中科院分区：
文献类型：
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作者：
Porter,SarahEG;Stoll,DwightR;Paek,Changyub;Rutan,SarahC;Carr,PeterW
在本研究的第一部分中，我们建立了一种基于快速梯度洗脱液相色谱-二极管阵列光谱检测（LC-DAD）的生物样品滥用药物检测方法。在这部分工作中，我们将靶因子分析（TFA）的化学计量学方法应用于色谱。该算法基于谱库识别色谱图中存在的目标化合物，分解近共洗脱成分，并区分具有相似谱的药物。利用DAD提供的光谱数据解决高度重叠峰的能力是本方法与传统库搜索方法的区别所在。在考虑保留指数和谱因子的情况下，库的平均列表长度（MLL）为1.255，判别能力为0.997。该算法比较了与未知样品具有毒理学相关性的47种不同化合物的文库，并根据光谱和保留指数匹配确定哪些化合物存在。校正保留指数的识别，而不是原始保留时间的应用补偿长期和柱到柱的保留时间的变化，并允许使用单一的光谱和保留数据库。利用训练数据集建立该方法的搜索和识别参数。使用70张色谱图的验证数据集计算该方法的灵敏度（正确识别阳性）和特异性（正确识别阴性），分别为92%和94%。
In Part I of this work, we developed a method for the detection of drugs of abuse in biological samples based on fast gradient elution liquid-chromatography coupled with diode array spectroscopic detection (LC-DAD). In this part of the work, we apply the chemometric method of target factor analysis (TFA) to the chromatograms. This algorithm identifies the target compounds present in chromatograms based on a spectral library, resolves nearly co-eluting components, and differentiates between drugs with similar spectra. The ability to resolve highly overlapped peaks using the spectral data afforded by the DAD is what distinguishes the present method from conventional library searching methods. Our library has a mean list length (MLL) of 1.255 and a discriminating power of 0.997 when both retention index and spectral factors are considered. The algorithm compares a library of 47 different compounds of toxicological relevance to unknown samples and identifies which compounds are present based on spectral and retention index matching. The application of a corrected retention index for identification rather than raw retention times compensates for long-term and column-to-column retention time shifts and allows for the use of a single library of spectral and retention data. Training data sets were used to establish the search and identification parameters of the method. A validation data set of 70 chromatograms was used to calculate the sensitivity (correct identification of positives) and specificity (correct identification of negatives) of the method, which were found to be 92% and 94%, respectively.