Model-based evaluation and model-free strategy for process development of three-column periodic counter-current chromatography

过程(计算) 过程开发 色谱法 一致性(知识库) 工艺工程 化学 栏(排版) 计算机科学 工程类 人工智能 操作系统 电信 帧(网络)
作者
Yan-Na Sun,Ce Shi,Xue‐Zhao Zhong,Xu-Jun Chen,Ran Chen,Qilei Zhang,Shan‐Jing Yao,Alois Jungbauer,Dong‐Qiang Lin
出处
期刊:Journal of Chromatography A [Elsevier]
卷期号:1677: 463311-463311 被引量:8
标识
DOI:10.1016/j.chroma.2022.463311
摘要

Multi-column counter-current chromatography is an advanced technology used for continuous capture processes to improve process productivity, resin capacity utilization and product consistency. However, process development is difficult due to process complexity. In this work, some general and convenient guidances for three-column periodic counter-current chromatography (3C-PCC) were developed. Boundaries and distributions of operating windows of 3C-PCC processes were clarified by model-based predictions. Interactive effects of feed concentration (c0), resin properties (qmax and De), recovery and regeneration times (tRR) were evaluated over a wide range for maximum productivity (Pmax). Furthermore, variation of Pmax was analyzed considering the constraint factors (capacity utilization target and flow rate limitation). The plateau value of Pmax was determined by qmax and tRR. The operating conditions for Pmax were controlled by qmax, tRR and c0 interactively, and a critical concentration existed to judge whether the operating conditions of Pmax under constraints. Based on the comprehensive understanding on 3C-PCC processes, a model-free strategy was proposed for process development. The optimal operating conditions could be determined based on a set of breakthrough curves, which was used to optimize process performance and screen resins. The approach proposed was validated using monoclonal antibody (mAb) capture with a 3C-PCC system under various mAb and feed concentrations. The results demonstrated that a thorough model-based process understanding on multi-column counter-current chromatography is important and could improve process development and establish a model-free strategy for more convenient applications.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Singularity应助科研通管家采纳,获得10
刚刚
Ava应助科研通管家采纳,获得10
刚刚
派大星完成签到,获得积分10
3秒前
风烟完成签到 ,获得积分10
7秒前
aylinChueng发布了新的文献求助10
11秒前
Snow完成签到 ,获得积分10
12秒前
和谐的醉山完成签到,获得积分10
14秒前
14秒前
李健应助小木子采纳,获得10
14秒前
无奈的萍完成签到,获得积分10
16秒前
双马尾小男生2完成签到,获得积分10
18秒前
蓝桉发布了新的文献求助10
19秒前
行者+完成签到,获得积分10
21秒前
21秒前
18062677029完成签到 ,获得积分10
24秒前
双马尾小男生完成签到,获得积分10
26秒前
小白222完成签到,获得积分10
30秒前
浮尘完成签到 ,获得积分0
36秒前
石破天惊完成签到,获得积分10
38秒前
科研通AI2S应助蓝桉采纳,获得10
39秒前
虚幻的冰露完成签到 ,获得积分10
39秒前
wanci完成签到,获得积分0
41秒前
张张完成签到 ,获得积分10
44秒前
客官们帮帮忙完成签到 ,获得积分10
46秒前
鲁大师完成签到 ,获得积分10
49秒前
缓慢雅青完成签到 ,获得积分10
54秒前
徐茂瑜完成签到 ,获得积分10
54秒前
嘻嘻完成签到 ,获得积分10
55秒前
你可真下饭完成签到 ,获得积分10
55秒前
Hosea完成签到 ,获得积分10
57秒前
henry完成签到 ,获得积分10
58秒前
vincentbioinfo完成签到,获得积分10
1分钟前
彪壮的微笑完成签到 ,获得积分10
1分钟前
伊可完成签到 ,获得积分10
1分钟前
人参跳芭蕾完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
冰阔落完成签到 ,获得积分10
1分钟前
Liao完成签到 ,获得积分10
1分钟前
yiling发布了新的文献求助10
1分钟前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Defense against predation 800
Very-high-order BVD Schemes Using β-variable THINC Method 568
Chen Hansheng: China’s Last Romantic Revolutionary 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3137067
求助须知:如何正确求助?哪些是违规求助? 2788055
关于积分的说明 7784485
捐赠科研通 2444102
什么是DOI,文献DOI怎么找? 1299733
科研通“疑难数据库(出版商)”最低求助积分说明 625557
版权声明 601010