Dept. of Biochemical Engineering, University College London, Torrington Place, London, U.K.
Biotechnol Prog. 2011 Nov-Dec;27(6):1653-60. doi: 10.1002/btpr.670. Epub 2011 Sep 21.
Downstream bioprocessing and especially chromatographic steps, commonly used for the purification of multicomponent systems, are significant cost drivers in the production of therapeutic proteins. There has been an increased interest in the development of systematic methods for the design of such processes, and the appropriate selection of a series of chromatographic steps is still a major challenge to be addressed. Several models have been developed previously but have assumed that 100% recovery of the desired product is obtained at each chromatographic step. In this work, a mathematical framework is proposed, based on mixed integer optimisation techniques, that removes this assumption and allows full flexibility on the position of retention time cut-points, between which the desired product fraction is collected. The proposed model is demonstrated on three example protein mixtures, each containing up to 13 contaminants and selecting from a set of up to 21 candidate steps. The proposed model results in a reduction of one to three chromatographic steps over solutions that no losses are allowed.
下游生物加工,特别是色谱步骤,常用于多组分系统的纯化,是治疗性蛋白生产中成本的主要驱动因素。人们越来越关注开发用于此类过程设计的系统方法,而适当选择一系列色谱步骤仍然是一个需要解决的主要挑战。以前已经开发了几种模型,但假设在每个色谱步骤中都可以获得所需产物的 100%回收率。在这项工作中,提出了一个基于混合整数优化技术的数学框架,该框架消除了这一假设,并允许在保留时间切割点之间(其中收集所需产物部分)的位置具有完全的灵活性。所提出的模型在三个示例蛋白质混合物上进行了演示,每个混合物包含多达 13 种污染物,并从多达 21 个候选步骤中进行选择。与不允许有任何损失的解决方案相比,所提出的模型可以减少一个到三个色谱步骤。