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Good modeling practice for industrial chromatography: Mechanistic modeling of ion exchange chromatography of a bispecific antibody

机译:工业色谱的良好建模实践:双特异性抗体的离子交换色谱的力学建模

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摘要

In the biopharmaceutical industry, development and characterization of chromatography processes is typically based on statistical models. Although these approaches are easy to apply, the resulting models may fail to predict non-linear behavior in preparative chromatography with complex protein feed streams. An alternative to empirical methods are mechanistic models. In chemical engineering, mechanistic modeling has been a standard method for decades. As mechanistic models continue their advance in the biopharmaceutical industry, this study underlines the need of a standardized methodology for mechanistic model calibration.A lumped rate model was applied to the polishing chromatography of a bispecific antibody. Following guidelines for good modeling practice, the model was thoroughly analyzed. Potential limitations such as over-parameterization, parameter correlations, imprecise parameter estimates or systematic errors were considered by evaluation of parameter confidence intervals, visual sensitivity analysis and model validation across different scales. Application of simulations for identification of critical process parameters will be discussed. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在生物制药工业中,色谱方法的开发和表征通常基于统计模型。尽管这些方法易于应用,但所得模型可能无法预测具有复杂蛋白质进料流的制备色谱中的非线性行为。机械模型是经验方法的替代方法。在化学工程中,机械建模已成为数十年来的标准方法。随着机械模型在生物制药行业中的不断发展,本研究强调了机械模型校准的标准化方法的必要性。将集总速率模型应用于双特异性抗体的抛光色谱法。遵循良好建模实践的准则,对模型进行了全面分析。通过评估参数置信区间,视觉灵敏度分析和跨不同规模的模型验证,可以考虑潜在的限制因素,例如过度参数化,参数相关性,不精确的参数估计或系统误差。将讨论模拟在识别关键过程参数中的应用。 (C)2019 Elsevier Ltd.保留所有权利。

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