一致性(知识库)
可比性
过程(计算)
计算机科学
许可证
质量(理念)
产品(数学)
风险分析(工程)
工艺验证
生物技术
新产品开发
业务
生物
营销
人工智能
操作系统
认识论
哲学
组合数学
数学
几何学
作者
Paul Y K Wu,Taymar Hartman,Louise Almond,Jennitte Stevens,John Thrift,Juhi Ojha,Christina Alves,David Shaw,Michael W. Laird,Robyn Emmins,Yuan Zhu,Ren Liu,Zhimei Du,Rolf Koehler,Thomas Jostock,Karin Anderson,C. Ryan Campbell,Howard R. G. Clarke
标识
DOI:10.5731/pdajpst.2018.009316
摘要
The bioprocessing industry uses recombinant mammalian cell lines to generate therapeutic biologic drugs. To ensure consistent product quality of the therapeutic proteins, it is imperative to have a controlled production process. Regulatory agencies and the biotechnology industry consider cell line "clonal origin" an important aspect of maintaining process control. Demonstration of clonal origin of the cell substrate, or production cell line, has received considerable attention in the past few years, and the industry has improved methods and devised standards to increase the probability and/or assurance of clonal derivation. However, older production cell lines developed before the implementation of these methods, herein referred to as "legacy cell lines," may not meet current regulatory expectations for demonstration of clonal derivation. In this article, the members of the IQ Consortium Working Group on Clonality present our position that the demonstration of process consistency and product comparability of critical quality attributes throughout the development life cycle should be sufficient to approve a license application without additional genetic analysis to support clonal origin, even for legacy cell lines that may not meet current day clonal derivation standards. With this commentary, we discuss advantages and limitations of genetic testing methods to support clonal derivation of legacy cell lines and wish to promote a mutual understanding with the regulatory authorities regarding their optional use during early drug development, subsequent to Investigational New Drug (IND) application and before demonstration of product and process consistency at Biologics License Applications (BLA) submission.
科研通智能强力驱动
Strongly Powered by AbleSci AI