Protein Adsorption and Transport in Chromatographic Bioprocessing

CBET-0828590 Lenhoff这个由化学和生物分离计划颁发的NSF奖项支持特拉华大学的Abraham Lenhoff教授在蛋白质离子交换层析中定量表征结构-性能关系的工作。然后，这种分析的结果将被用来根据少量相关的实验测量来开发预测色谱行为的系统方法。离子交换层析是工业生物处理中的主要单元操作，而经验性筛选方法的普及可以使有效的方法缩小试错法的优化范围特别有价值。拟议的研究将区分固结的聚合物或凝胶状基质上的传统吸附剂，以及聚合物修饰相，在这些相中，各种附加的柔性夹杂物已被证明可提供一些性能改善。对于传统的吸附剂，以前的工作已经提出了预测吸附等温线和传输性质的方法，其程度应该能够有效地预测整个色谱行为。然而，聚合物修饰的吸附剂仍然缺乏这样的能力。因此，我们将测量聚合物修饰的吸附剂的保留和传输性能，并试图将它们与材料的结构特征相关联。此外，从传统介质开始，转向聚合物修饰介质，将使用机械方法来开发填充柱中蛋白质负载和洗脱的预测模型。拟议的研究将在几个领域产生影响。首先，它应该大大有助于提高生物处理中层析步骤的概念性和详细设计的效率。一个补充的贡献将是固定相设计，在那里，适当地使用我们的结果可以允许在这种材料中设计出所需的特性。其次，这项研究将成为培养研究生和本科生的有效教育工具；许多曾参与过此类项目的学生受雇于生物技术和制药行业。最后，拟议的研究将包括一个组成部分，通过将柱建模的计算程序包作为MatLab例程和可以在任何网络浏览器上运行的小程序来提供，从而将研究结果传播给对色谱学研究和实践感兴趣的更大的社区。

CBET-0828590LenhoffThis NSF award by the Chemical and Biological Separations program supports work by Professor Abraham Lenhoff at the University of Delaware to characterize quantitatively the structure-performance relationship in ion-exchange chromatography of proteins. The results of such analyses will then be used to develop systematic approaches for predicting chromatographic behavior on the basis of a small number of relevant experimental measurements. Ion-exchange chromatography is a major unit operation in industrial bioprocessing, and the prevalence of empirical screening methods can make efficient methods for reducing the scope of trial-and-error methods of optimization particularly valuable. The proposed research will distinguish between traditional adsorbents on consolidated polymeric or gel-like base matrices, and polymer-modified phases in which additional flexible inclusions of various kinds have been shown to offer some performance improvements. For the traditional adsorbents, prior work has produced approaches to predict adsorption isotherms and transport properties to a degree that should allow effective prediction of overall chromatographic behavior. Such capabilities are still lacking for the polymer-modified adsorbents, however. We will therefore measure retention and transport properties for the polymer-modified adsorbents and seek to correlate them with structural characteristics of the materials. In addition, starting with traditional media and moving on to polymer-modified ones, mechanistic methods will be used to develop predictive models of protein loading and elution in packed columns.The proposed research should have an impact in several areas. First, it should contribute significantly to improving the efficiency of conceptual and detailed design of chromatographic steps in bioprocessing. A complementary contribution will be to stationary-phase design, where suitable use of our results can allow desirable characteristics to be designed into such materials. Second, the research will be an effective educational vehicle for training of graduate and undergraduate students; numerous such students who have worked on previous projects of this kind are employed in the biotech and pharma industries. Finally, the proposed research will include a component to disseminate the findings to the larger community interested in chromatographic research and practice by making computational packages for column modeling available as both Matlab routines and as applets that can be run in any web browser.