在原料变化下评估连续捕获的动态控制,使用定期逆流色谱
Yu Fan1, Yan-Na Sun1, Liang-Zhi Qiao1
1Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China.
Journal of chromatography. A
|November 29, 2023
概括
基于模型的方法预测了使用多列染色学连续捕获抗体的风险. 该方法评估原料变化和动态控制失效,确保工艺稳定性并尽量减少蛋白质损失.
科学领域:
- 生物技术是生物技术.
- 化学工程是化学工程的重要组成部分.
- 过程分析技术 过程分析技术
背景情况:
- 连续染色学提供有效的抗体捕获,但面临过程干扰的风险.
- 原料 (目标蛋白,杂质) 的动态变化可能会影响长期的运行稳定性.
- 现有的控制策略可能会在持续生物处理中遇到不可预测的变化.
研究的目的:
- 开发和评估基于模型的方法来评估连续染色学中的风险.
- 了解原料变化对突破曲线和工艺性能的影响.
- 为实时动态控制策略在抗体捕获中建立一个预测工具.
主要方法:
- 利用基于模型的方法在不同的原料条件下模拟突破曲线.
- 在动态紫外线 (ΔUV) 控制下系统地评估了三列周期反流色谱的性能.
- 开发了一个轮图,以可视化目标蛋白和杂质变异对工艺结果的综合影响.
主要成果:
- 模型准确地预测了由于目标蛋白或杂质度的小幅降低而导致的蛋白质损失.
- 在各种原料场景下,由于控制失败或蛋白质损失导致的确定非操作区域.
- 证明了目标蛋白度的快速下降可以导致 ΔUV 控制失败.
- 展示了目标蛋白和杂质变异之间的复杂相互作用对工艺性能的影响.
结论:
- 基于模型的方法有效预测过程稳定性,并评估与动态变化相关的风险.
- 这种方法对于开发持续生物处理的强大实时动态控制策略至关重要.
- 开发的轮图有助于识别操作限制和潜在的故障模式.
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