Protein Adsorption and Transport in Chromatographic Bioprocessing

这项由美国国家科学基金会化学和生物分离项目颁发的奖项，支持特拉华大学亚伯拉罕·伦霍夫教授在蛋白质离子交换色谱中定量表征结构-性能关系的工作。这些分析的结果将用于在少量相关实验测量的基础上开发预测色谱行为的系统方法。离子交换色谱是工业生物处理中的一个主要单元操作，经验筛选方法的流行可以使有效的方法减少优化的试错方法的范围特别有价值。拟议的研究将区分固结聚合物或凝胶状基质上的传统吸附剂，以及聚合物修饰相，其中附加的各种柔性内含物已被证明可以提供一些性能改进。对于传统的吸附剂，先前的工作已经产生了预测吸附等温线和运输性质的方法，在一定程度上应该允许有效地预测整体色谱行为。然而，聚合物改性吸附剂仍然缺乏这种能力。因此，我们将测量聚合物改性吸附剂的保留和运输特性，并寻求将它们与材料的结构特征联系起来。此外，从传统介质开始，转向聚合物修饰的介质，机械方法将用于开发填充柱中蛋白质装载和洗脱的预测模型。拟议的研究应在几个领域产生影响。首先，它应该有助于提高生物加工色谱步骤的概念和详细设计的效率。一个补充的贡献将是对平稳相位设计，在适当的使用我们的结果可以允许理想的特性设计到这样的材料。二是为研究生和本科生的培养提供有效的教育手段；许多从事过这类项目的学生受雇于生物技术和制药行业。最后，建议的研究将包括一个组件，通过将柱建模的计算包作为Matlab例程和可在任何web浏览器中运行的applet，将研究结果传播给对色谱研究和实践感兴趣的更大社区。

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.