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Global Sensitivity Analysis for the determination of parameter importance in bio-manufacturing processes

机译:全局灵敏度分析,用于确定生物制造过程中的参数重要性

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The present paper describes the application of GSA (Global Sensitivity Analysis) techniques to mathematical models of bioprocesses in order to rank inputs such as feed titres, flow rates and matrix capacities for the relative influence that each exerts upon outputs such as yield or throughput. GSA enables quantification of both the impact of individual variables on process outputs, as well as their interactions. These data highlight those attributes of a bioprocess which offer the greatest potential for achieving manufacturing improvements. Whereas previous GSA studies have been limited to individual unit operations, this paper extends the treatment to an entire downstream process and illustrates its utility by application to the production of a Fab-based rattlesnake antivenom called CroFab (TM) [(Crotalidae Polyvalent Immune Fab (Ovine); Protherics U.K. Limited]. Initially, hyperimmunized ovine serum containing rattlesnake antivenom IgG (product), other antibodies and albumin is applied to a synthetic affinity ligand adsorbent column to separate the antibodies from the albumin. The antibodies are papain-digested into Fab and Fc fragments, before concentration by ultrafiltration. Fc, residual IgG and albumin are eliminated by an ion-exchanger and then CroFab-specific affinity chromatography is used to produce purified antivenom. Application of GSA to the model of this process showed that product yield was controlled by IgG feed concentration and the synthetic-material affinity column's capacity and flow rate, whereas product throughput was predominantly influenced by the synthetic material's capacity, the ultrafiltration concentration factor and the CroFab affinity flow rate. Such information provides a rational basis for identifying the most promising strategies for delivering improvements to commercial-scale biomanufacturing processes.
机译:本文介绍了GSA(全球敏感性分析)技术在生物过程数学模型中的应用,以便对输入(例如进料滴定度,流速和基质容量)进行排名,以评估每种对输出(例如产量或产量)的相对影响。 GSA可以量化各个变量对过程输出的影响及其相互作用。这些数据强调了生物过程的那些属性,这些属性为实现生产改进提供了最大的潜力。尽管以前的GSA研究仅限于单个单元操作,但本文将处理范围扩展到整个下游过程,并说明了其在生产基于Fab的响尾蛇抗蛇毒动物称为CroFab(TM)[(Crotalidae Polyvalent Immune Fab(最初,将含有响尾蛇抗人血清IgG(产品),其他抗体和白蛋白的超免疫绵羊血清加到合成的亲和配体吸附柱上,以从白蛋白中分离出抗体,然后用木瓜蛋白酶消化成Fab。通过离子交换除去Fc,残留的IgG和白蛋白,然后使用CroFab特异性亲和色谱法生产纯化的抗蛇毒血清,GSA在该过程模型中的应用表明产物收率为由IgG进料浓度和合成材料亲和柱的容量和流速控制,而prod uct产量主要受合成材料的容量,超滤浓缩因子和CroFab亲和流速的影响。此类信息为确定最有前途的策略提供了合理的基础,这些策略可为商业规模的生物制造工艺提供改进。

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