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Process Analytical Approach towards Quality Controlled Process Automation for the Downstream of Protein Mixtures by Inline Concentration Measurements Based on Ultraviolet/Visible Light (UV/VIS) Spectral Analysis

机译:基于紫外/可见光(UV / VIS)光谱分析的在线浓度测量对蛋白质混合物下游质量控制的过程自动化进行过程分析

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摘要

Downstream of pharmaceutical proteins, such as monoclonal antibodies, is mainly done by chromatography, where concentration determination of coeluting components presents a major problem. Inline concentration measurements (ICM) by Ultraviolet/Visible light (UV/VIS)-spectral data analysis provide a label-free and noninvasive approach to significantly speed up the analysis and process time. Here, two different approaches are presented. For a test mixture of three proteins, a fast and easily calibrated method based on the non-negative least-squares algorithm is shown, which reduces the calibration effort compared to a partial least-squares approach. The accuracy of ICM for analytical separations of three proteins on an ion exchange column is over 99%, compared to less than 85% for classical peak area evaluation. The power of the partial least squares algorithm (PLS) is shown by measuring the concentrations of Immunoglobulin G (IgG) monomer and dimer under a worst-case scenario of completely overlapping peaks. Here, the faster SIMPLS algorithm is used in comparison to the nonlinear iterative partial least squares (NIPALS) algorithm. Both approaches provide concentrations as well as purities in real-time, enabling live-pooling decisions based on product quality. This is one important step towards advanced process automation of chromatographic processes. Analysis time is less than 100 ms and only one program is used for all the necessary communications and calculations.
机译:药物蛋白(例如单克隆抗体)的下游主要是通过色谱法完成的,其中共洗脱组分的浓度测定是一个主要问题。通过紫外线/可见光(UV / VIS)光谱数据分析进行的在线浓度测量(ICM)提供了一种无标签且无创的方法,可显着加快分析和处理时间。在这里,提出了两种不同的方法。对于三种蛋白质的测试混合物,显示了一种基于非负最小二乘法的快速且易于校准的方法,与部分最小二乘法相比,该方法减少了校准工作。 ICM在离子交换柱上分析分离三种蛋白质的准确性超过99%,而传统峰面积评估的准确性不到85%。在完全重叠的峰的最坏情况下,通过测量免疫球蛋白G(IgG)和二聚体的浓度来显示偏最小二乘算法(PLS)的功能。在此,与非线性迭代部分最小二乘(NIPALS)算法相比,使用了更快的SIMPLS算法。两种方法都可以实时提供浓度和纯度,从而可以根据产品质量进行实时合并决策。这是迈向色谱过程高级过程自动化的重要一步。分析时间少于100毫秒,并且仅使用一个程序进行所有必要的通讯和计算。

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