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多能干细胞产品的分布式自动化制造。

Distributed automated manufacturing of pluripotent stem cell products.

作者信息

Shariatzadeh Maryam, Chandra Amit, Wilson Samantha L, McCall Mark J, Morizur Lise, Lesueur Léa, Chose Olivier, Gepp Michael M, Schulz André, Neubauer Julia C, Zimmermann Heiko, Abranches Elsa, Man Jennifer, O'Shea Orla, Stacey Glyn, Hewitt Zoe, Williams David J

机构信息

1Centre for Biological Engineering, Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU UK.

Present Address: Yposkesi, 26, rue Henri Auguste-Desbruères, 91100 Corbeil-Essonnes, France.

出版信息

Int J Adv Manuf Technol. 2020;106(3):1085-1103. doi: 10.1007/s00170-019-04516-1. Epub 2019 Dec 4.

Abstract

Establishing how to effectively manufacture cell therapies is an industry-level problem. Decentralised manufacturing is of increasing importance, and its challenges are recognised by healthcare regulators with deviations and comparability issues receiving specific attention from them. This paper is the first to report the deviations and other risks encountered when implementing the expansion of human pluripotent stem cells (hPSCs) in an automated three international site-decentralised manufacturing setting. An experimental demonstrator project expanded a human embryonal carcinoma cell line (2102Ep) at three development sites in France, Germany and the UK using the CompacT SelecT (Sartorius Stedim, Royston, UK) automated cell culture platform. Anticipated variations between sites spanned material input, features of the process itself and production system details including different quality management systems and personnel. Where possible, these were pre-addressed by implementing strategies including standardisation, cell bank mycoplasma testing and specific engineering and process improvements. However, despite such measures, unexpected deviations occurred between sites including software incompatibility and machine/process errors together with uncharacteristic contaminations. Many only became apparent during process proving or during the process run. Further, parameters including growth rate and viability discrepancies could only be determined post-run, preventing 'live' corrective measures. The work confirms the critical nature of approaches usually taken in Good Manufacturing Practice (GMP) manufacturing settings and especially emphasises the requirement for monitoring steps to be included within the production system. Real-time process monitoring coupled with carefully structured quality systems is essential for multiple site working including clarity of decision-making roles. Additionally, an over-reliance upon post-process visual microscopic comparisons has major limitations; it is difficult for non-experts to detect deleterious culture changes and such detection is slow.

摘要

确定如何有效地生产细胞疗法是一个行业层面的问题。分散式生产变得越来越重要,其面临的挑战也得到了医疗监管机构的认可,偏差和可比性问题受到了他们的特别关注。本文首次报告了在一个自动化的、三个国际站点分散式生产环境中进行人类多能干细胞(hPSC)扩增时遇到的偏差和其他风险。一个实验示范项目在法国、德国和英国的三个研发站点使用CompacT SelecT(赛多利斯斯泰迪姆公司,英国罗伊斯顿)自动化细胞培养平台扩增了一种人类胚胎癌细胞系(2102Ep)。各站点之间预期的差异涵盖材料输入、工艺本身的特点以及生产系统细节,包括不同的质量管理体系和人员。在可能的情况下,通过实施标准化、细胞库支原体检测以及特定的工程和工艺改进等策略预先解决了这些问题。然而,尽管采取了这些措施,各站点之间仍出现了意外偏差,包括软件不兼容、机器/工艺错误以及异常污染。许多偏差直到工艺验证或生产过程中才显现出来。此外,包括生长速率和活力差异在内的参数只能在生产结束后确定,这使得无法采取“实时”纠正措施。这项工作证实了良好生产规范(GMP)生产环境中通常采用的方法的关键性质,尤其强调了在生产系统中纳入监测步骤的必要性。实时过程监测与精心构建的质量体系相结合对于多站点协作至关重要,包括明确决策角色。此外,过度依赖后处理的目视显微镜比较存在重大局限性;非专业人员很难检测到有害的培养变化,而且这种检测速度很慢。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f91/6954896/96c6fc481a9a/170_2019_4516_Fig1_HTML.jpg

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