School of Pharmacy, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo 192-0392, Japan.
School of Pharmacy, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo 192-0392, Japan.
J Chromatogr A. 2020 Feb 8;1612:460644. doi: 10.1016/j.chroma.2019.460644. Epub 2019 Oct 21.
This paper presents a basic model of an automated system for predicting the detection limit and precision profile (plot of relative standard deviation (RSD) of measurements against concentration) in chromatography. The fundamental assumption is that the major source of response errors at low sample concentrations is background noise and at high concentrations, it is the volumes injected into an HPLC system by a sample injector. The noise is approximated by the mixed random processes of the first order autoregressive process AR(1) and white noise. The research procedures are: (1) the description of the standard deviation (SD) of measurements in terms of the parameters of the mixed random processes; (2) the algorithm for the parameter estimation of the mixed processes from actual background noise; (3) the mathematical distinction between noise and signal in a chromatogram. When compounds are chromatographically separated, each obtained signal is given the detection limit and precision profile on laboratory-made software. A file of a chromatogram is the only requirement for the theoretical prediction of measurement uncertainty and therefore the repeated measurements of real samples can be dispensed with. The theoretically predicted RSDs are verified by comparing them with the statistical RSDs obtained by repeated measurements. Signal shapes on noise are illustrated at the detection limit and quantitation limit, the signal-to-noise ratios of which are close to the widely adopted values, 3 and 10, respectively.
本文提出了一个自动化系统的基本模型,用于预测色谱法中的检测限和精密度曲线(即相对标准偏差(RSD)与浓度的关系图)。该模型的基本假设是,在低样品浓度下,响应误差的主要来源是背景噪声,而在高浓度下,则是样品进样器注入 HPLC 系统的体积。噪声近似为由一阶自回归过程 AR(1)和白噪声混合的随机过程。研究步骤如下:(1)用混合随机过程的参数描述测量的标准偏差(SD);(2)从实际背景噪声中估算混合过程的参数;(3)在色谱图中区分噪声和信号。当化合物在色谱上分离时,每个获得的信号都在实验室自制的软件上给出检测限和精密度曲线。理论预测测量不确定度只需要一个色谱图文件,因此可以省去对实际样品的重复测量。通过将理论预测的 RSD 与通过重复测量获得的统计 RSD 进行比较,验证了其预测结果。在检测限和定量限处,展示了噪声上的信号形状,其信噪比分别接近广泛采用的值 3 和 10。