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首页> 外文期刊>Biotechnology Progress >Chemometrics Applications in Biotechnology Processes: Predicting Column Integrity and Impurity Clearance During Reuse of Chromatography Resin
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Chemometrics Applications in Biotechnology Processes: Predicting Column Integrity and Impurity Clearance During Reuse of Chromatography Resin

机译：化学计量学在生物技术过程中的应用：预测色谱树脂再利用期间的色谱柱完整性和杂质清除率

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摘要

Separation media, in particular chromatography media, is typically one of the major contributors to the cost of goods for production of a biotechnology therapeutic. To be cost-effective, it is industry practice that media be reused over several cycles before being discarded. The traditional approach for estimating the number of cycles a particular media can be reused for involves performing laboratory scale experiments that monitor column performance and carryover. This dataset is then used to predict the number of cycles the media can be used at manufacturing scale (concurrent validation). Although, well accepted and widely practiced, there are challenges associated with extrapolating the laboratory scale data to manufacturing scale due to differences that may exist across scales. Factors that may be different include: level of impurities in the feed material, lot to lot variability in feedstock impurities, design of the column housing unit with respect to cleanability, and homogeneity of the column packing. In view of these challenges, there is a need for approaches that may be able to predict column underperformance at the manufacturing scale over the product lifecycle. In case such an underperformance is predicted, the operators can unpack and repack the chromatography column beforehand and thus avoid batch loss. Chemometrics offers one such solution. In this article, we present an application of chemometrics toward the analysis of a set of chromatography profiles with the intention of predicting the various events of column underperformance including the backpressure buildup and inefficient deoxyribonucleic acid clearance.
机译：分离介质，特别是色谱介质，通常是造成生物技术治疗剂生产的商品成本的主要因素之一。为了具有成本效益，行业惯例是在丢弃媒体之前，要在多个周期内重新使用它们。估算特定介质可重复使用的循环次数的传统方法包括执行实验室规模的实验，以监控色谱柱的性能和残留。然后，该数据集用于预测可在制造规模下使用介质的周期数（并行验证）。尽管已被广泛接受和广泛实践，但是由于跨规模可能存在差异，因此将实验室规模数据外推到生产规模仍存在挑战。可能不同的因素包括：进料中杂质的含量，原料杂质的批次间差异，关于清洁性的色谱柱容纳单元设计以及色谱柱填料的均质性。鉴于这些挑战，需要一种能够在整个产品生命周期中的制造规模上预测色谱柱性能不佳的方法。如果预计会出现这种性能不佳的情况，操作员可以事先拆开色谱柱并重新包装，从而避免批次损失。 Chemometrics提供了一种这样的解决方案。在本文中，我们介绍了化学计量学在一组色谱图分析中的应用，旨在预测色谱柱性能欠佳的各种事件，包括背压积累和低效脱氧核糖核酸清除率。

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