4.6 Article

Extreme scale-down of expanded bed adsorption:: Purification of an antibody fragment directly from recombinant E. coli culture

期刊

BIOTECHNOLOGY AND BIOENGINEERING
卷 87, 期 5, 页码 641-647

出版社

WILEY-BLACKWELL
DOI: 10.1002/bit.20173

关键词

scale-down; expanded bed adsorption; process mimic

向作者/读者索取更多资源

Scale-down is a methodology that combines the use of very small volumes of process fluid in dedicated devices to predict accurately the behaviour of process-scale biotechnological unit operations and for the production of comparable material for use in further devices which, taken together, facilitate the mimic of a complete full-scale process. This article provides the rationale behind the development of a small-scale mimic and demonstrates the use of a highly scaled-down expanded bed to predict hydrodynamic, kinetic, and adsorptive performance using less than 5-mL sample volumes. Data acquired on a specially developed 1.9 mm ID column was compared with that obtained in a standard 25 mm ID column. A homogenised E. coli system expressing an antibody fragment (F(ab)) adsorbed onto an rProtein A matrix was used to characterise the full adsorptive performance. Breakthrough curve studies using BSA in buffer were used to characterise binding kinetics. Performance at the two scales was comparable both in terms of expansion, axial dispersion, binding isotherms, and elution behaviour of the antibody fragment. The eluted F(ab) material was further purified by ion exchange chromatography to demonstrate the similarity between the profile of the product material obtained at both scales. The high level of scale-down (similar to200-fold) provides for rapid process evaluation early in development, where material is at a premium and where a fast appreciation of the likely merits of one process strategy will lead to greater confidence in process selection and more robust flowsheets. (C) 2004 Wiley Periodicals, Inc.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据