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使用高通量自动化微生物反应器系统在CHO细胞中生产模型IgG1

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells.

作者信息

Velugula-Yellela Sai Rashmika, Kohnhorst Casey, Powers David N, Trunfio Nicholas, Faustino Anneliese, Angart Phillip, Berilla Erica, Faison Talia, Agarabi Cyrus

机构信息

Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, U.S. Food and Drug Administration.

Center for Drug Evaluation and Research, Office of Product Quality, Office of Biotechnology Products, Division of Biotechnology Review and Research II, U.S. Food and Drug Administration;

出版信息

J Vis Exp. 2018 Sep 28(139):58231. doi: 10.3791/58231.

DOI:10.3791/58231
PMID:30320757
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6235343/
Abstract

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts, media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE's with a higher number of variables and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

摘要

自动化微型生物反应器(15毫升)对细胞培养工程师来说可能是一种有用的工具。它们有助于同时执行多种实验条件,同时将潜在的过程变异性降至最低。这种方法的应用包括:克隆筛选、温度和pH值变化、培养基和添加剂优化。此外,小反应器体积有利于进行大规模实验设计,以研究广泛的条件。这使得上游工艺在放大之前能够得到显著优化,因为在放大过程中,由于时间和经济限制,实验范围更加有限。与传统的小规模细胞培养装置(如摇瓶或转瓶)相比,自动化微型生物反应器系统具有各种优势。然而,在中试规模工艺开发过程中,必须格外小心,以确保这些优势得以实现。小心操作时,该系统可以实现高度自动化,可以编程运行具有更多变量的实验设计,并且与营养分析仪或细胞计数器集成时可以减少采样时间。将本文介绍的专家启发式方法与当前的自动化微型生物反应器实验相结合,可以最大限度地减少阻碍获得有意义结果的常见陷阱。在极端情况下,不遵守此处列出的原则可能会导致设备损坏,需要进行昂贵的维修。此外,微生物反应器系统的培养体积小,使得细胞培养条件的表征变得困难。在分批模式培养中,过程中采集的样品数量和数量受到限制,因为操作体积不能低于10毫升。本文将讨论微型生物反应器系统的优缺点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/2f24f3131177/jove-139-58231-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/bb64cec5e9b5/jove-139-58231-0.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/2022594f50a5/jove-139-58231-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/5b03f0818873/jove-139-58231-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/2f24f3131177/jove-139-58231-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/bb64cec5e9b5/jove-139-58231-0.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/2022594f50a5/jove-139-58231-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/5b03f0818873/jove-139-58231-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c217/6235343/2f24f3131177/jove-139-58231-3.jpg

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本文引用的文献

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Impact of media and antifoam selection on monoclonal antibody production and quality using a high throughput micro-bioreactor system.使用高通量微型生物反应器系统时,培养基和消泡剂选择对单克隆抗体生产及质量的影响
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3
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Biotechnol Prog. 2017 Mar;33(2):478-489. doi: 10.1002/btpr.2417. Epub 2017 Feb 6.
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