Development of Predictive Modeling for Immuno-Affinity Chromatography Using Distributed Parameter System: For Purification of Therapeutic Blood Protein

使用分布式参数系统开发免疫亲和色谱预测模型：用于纯化治疗性血液蛋白

• 批准号: 8902499
• 负责人: Dewey Ryu
• 金额: $ 39.19万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-05-01 至 1992-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8902499&HistoricalAwards=false
• 关键词: Development; Predictive; Modeling; Immuno; Affinity

A comprehensive fundamental biochemical engineering study is being undertaken to develop a distributed parameter system working model, which takes into consideration distributed equilibrium coefficients as a function of system's and operational variables, for immuno-affinity purification. The biochemical and immuno-chemical reaction system as well as the purification process will be studied systematically to develop a practical systems model. For the development of this model the systems to be used are: (1) immuno-affinity purification of human plasma Protein C, and (2) purification of monoclonal antibodies using Protein A affinity chromatography. The benefits and impact of the anticipated research results will be: (1) The knowledge base for the development of large-scale immuno-affinity process design and optimization for the purification of blood proteins will be broadened and advanced, (2) A rational strategy will evolve by which large-scale immuno-affinity purification processes can be designed and optimized based on predictive modeling and the simulation of system performance. This study should provide a greater insight into the microscopic phenomena and also a better understanding of macroscopic phenomena related to the optimal design and operational strategy for large scale immuno-affinity purification systems. Both experimental and theoretical studies will be carried out to establish a knowledge base and to develope an optimal design and operational strategy through mathematical modeling and experimental verification. Protein C is a protein whose functions in blood include both blocking the blood coagulation pathways and dissolution of clots in animal, thus maintaining hemostasis in the human body. Lack of this protein causes complicated blood clotting related symptoms, such as thromboembolism, stroke, or even sudden death.

一项综合性的基础生化工程研究正在进行，以开发一个分布式参数系统工作模型，该模型考虑了分布式平衡系数作为系统和操作变量的函数，用于免疫亲和纯化。生物化学和免疫化学反应系统以及净化过程将被系统地研究，以建立一个实用的系统模型。对于该模型的开发，将使用的系统是：(1)人血浆蛋白C的免疫亲和纯化，(2)使用蛋白A亲和层析纯化单克隆抗体。预期研究结果的好处和影响如下：(1)为开发大规模免疫亲和工艺设计和优化血液蛋白纯化的知识基础将得到拓宽和完善；(2)基于预测建模和系统性能仿真的大规模免疫亲和纯化过程的设计和优化策略将逐步形成。本研究将为大规模免疫亲和纯化系统的优化设计和操作策略提供更深入的微观现象和更好的宏观现象理解。通过数学建模和实验验证，将进行实验和理论研究，以建立知识库，并制定最佳设计和操作策略。蛋白C是一种在动物体内具有阻断凝血途径和溶解凝块功能，从而维持人体止血功能的蛋白质。缺乏这种蛋白质会导致复杂的凝血相关症状，如血栓栓塞、中风，甚至猝死。