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On-Line Process Control of Gradient Elution Liquid Chromatography

机译:梯度洗脱液相色谱在线过程控制

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摘要

The typical measure of the stability of analytical HPLC methods in the pharmaceutical laboratory is standards injected repeatedly throughout the sample sequence. To obtain improved control of the analysis and reduction of the number of standards and replicates, a novel approach to treat the analytical run as a process, where the chromatographic data is the product, is proposed. Thus, an alternative and continuous system suitability test procedure is described. This is obtained by continuous monitoring of several parameters of the chromatographic system such as pressure, temperature, and conductivity. The data are analyzed in real time with chemometrics to produce easily interpreted control charts. Gradient elution LC is extensively employed in pharmaceutical analysis. A gradient elution system is inherently dynamic due to the mobile-phase composition being changed during the chromatographic run. To handle the dynamics, suitable chemometric tools are needed. In this report, we extend the use of liquid chromatography process control (LCPC) to gradient elution LC by creating partial least-squares regression batch models of the data collected. The gradient elution LCPC system was evaluated by inducing disturbances, and it was shown to easily detect any real or simulated deviation.
机译:制药实验室中分析型HPLC方法稳定性的典型衡量标准是在整个样品序列中重复注入标准品。为了获得对分析的改进控制并减少标准品和重复样品的数量,提出了一种将分析运行作为一种过程的新方法,其中色谱数据是产品。因此,描述了替代的和连续的系统适用性测试过程。这是通过连续监控色谱系统的几个参数(例如压力,温度和电导率)而获得的。使用化学计量学对数据进行实时分析,以生成易于理解的控制图。梯度洗脱液相色谱广泛用于药物分析。梯度洗脱系统固有地是动态的,因为在色谱运行期间会改变流动相的组成。为了处理动力学,需要合适的化学计量工具。在本报告中,我们通过创建收集数据的部分最小二乘回归批处理模型,将液相色谱过程控制(LCPC)的使用扩展到梯度洗脱LC。通过诱导干扰对梯度洗脱LCPC系统进行了评估,结果表明它可以轻松检测出任何真实或模拟偏差。

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