Development of a high‐throughput scale‐down model in Ambr® 250 HT for plasmid DNA fermentation processes

Author:

Fang Shu1,Sinanan Dillon J.1,Perez Marc H.1,Cruz‐Quintero Raúl G.1,Jadhav Sachin R.1

Affiliation:

1. BioProcess Research & Development Pfizer Inc. Chesterfield Missouri USA

Abstract

AbstractRecent advances in messenger ribonucleic acid (mRNA) vaccines and gene therapy vectors have increased the need for rapid plasmid DNA (pDNA) screening and production within the biopharmaceutical industry. High‐throughput (HT) fermentor systems, such as the Ambr® 250 HT, can significantly accelerate process development timelines of pDNA upstream processes compared to traditional bench‐scale glass fermentors or small‐scale steam‐in‐place (SIP) fermentors. However, such scale‐down models must be qualified to ensure that they are representative of the larger scale process similar to traditional small‐scale models. In the current study, we developed a representative scale‐down model of a Biostat® D‐DCU 30 L pDNA fermentation process in Ambr® 250 HT fermentors using three cell lines producing three different constructs. The Ambr scale‐down model provided comparable process performance and pDNA quality as the 30 L SIP fermentation process. In addition, we demonstrated the predictive value of the Ambr model by two‐way qualification, first by accurately reproducing the prior trends observed in a 30 L process, followed by predicting new process trends that were then successfully reproduced in the 30 L process. The representative and predictive scale‐down Ambr model developed in this study would enable a faster and more efficient approach to strain/clone/host‐cell screening, pDNA process development and characterization studies, process scale‐up studies, and manufacturing support.

Publisher

Wiley

Reference35 articles.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3