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Chromatographic Parameter Determination for Complex Biological Feedstocks

机译:复杂生物原料的色谱参数测定

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The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 L can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks. (C) 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers
机译:用于色谱法的机械模型需要精确的模型参数。特别是对于诸如澄清的细胞收获的复杂原料,这仍然可以是限制机械模型的障碍。另一个常见的障碍是确定所有所需参数的有限量的样品和时间。因此,本研究旨在在机器人液体处理系统上实施方法,该方法直接从含有单克隆抗体的复杂原料开始。通过使用本研究中确定的所有参数比较通过机械模型产生的预测的独立实验数据集来测试该方法。发现预测和实验数据之间的良好协议验证了这种方法。因此,可以得出结论,具有200L的床卷的Robocolumns可以利用来确定用于预测更大尺度列的等温参数。总体而言,这种方法提供了一种新方法来确定复杂生物原料色谱色谱机械模型的关键模型输入参数。 (c)2018年作者Biotechnology通过Wiley期刊,Inc。代表美国化学工程师研究所发布

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