Abstract：
In response to the growing demand for therapeutic biomolecules, there is a need for continuous and cost-effective bio-separation techniques to enhance extraction yield and efficiency. Aqueous biphasic extractive fermentation has emerged as an integrated downstream processing technique, offering selective partitioning, high productivity, and preservation of biomolecule integrity. However, the dynamic nature of this technique requires a comprehensive understanding of the underlying separation mechanisms. Unfortunately, the analysis of parameters influencing this dynamic behavior can be challenging due to limited resources and time. To address this, mathematical modeling approaches can be employed to minimize the tedious trial-and-error experimentation process. This review article presents mathematical modeling approaches for both upstream and downstream processing techniques, focusing on the production of biomolecules which can be used in pharmaceutical industries in a cost-effective manner. By leveraging mathematical models, researchers can optimize the production and purification processes, leading to improved efficiency and processing cost reduction in biomolecule production.
摘要：
为了应对对治疗性生物分子日益增长的需求，需要连续和成本有效的生物分离技术来提高提取产率和效率。水相双相提取发酵已成为一种集成的下游加工技术，提供选择性分区，高生产率,和保持生物分子的完整性。然而,这种技术的动态性质需要对潜在的分离机制有全面的了解。不幸的是,由于有限的资源和时间，影响这种动态行为的参数分析可能是具有挑战性的。为了解决这个问题，可以采用数学建模方法来最大限度地减少繁琐的试错实验过程。这篇综述文章介绍了上游和下游处理技术的数学建模方法，专注于以经济有效的方式生产可用于制药工业的生物分子。通过利用数学模型，研究人员可以优化生产和纯化过程，导致生物分子生产效率提高和加工成本降低。
