Bioprocess Technologies that Preserve the Quality of iPSCs. Issue 10 (October 2020)

• Record Type: Journal Article
• Authors: Polanco, Ashli; Kuang, Bingyu; Yoon, Seongkyu
• Is Part Of: Trends in biotechnology. Volume 38:Issue 10(2020)
• Page Start: 1128
• Page End: 1140
• Publication Date: 2020-10
• Subjects: induced pluripotent stem cells -- cell therapy -- quality control -- clinical manufacturing; Biotechnology -- Periodicals; Biochemical engineering -- Periodicals; Genetic engineering -- Periodicals; Industrial microbiology -- Periodicals; 660.605
• DOI: 10.1016/j.tibtech.2020.03.006
• Languages: English
• ISSNs: 0167-7799

Abstract

Abstract : Large-scale production of induced pluripotent stem cells (iPSCs) is essential for the treatment of a variety of clinical indications. However, culturing enough iPSCs for clinical applications is problematic due to their sensitive pluripotent state and dependence on a supporting matrix. Developing stem cell bioprocessing strategies that are scalable and meet clinical needs requires incorporating methods that measure and monitor intrinsic markers of cell differentiation state, developmental status, and viability in real time. In addition, proper cell culture modalities that nurture the growth of high-quality stem cells in suspension are critical for industrial scale-up. In this review, we present an overview of cell culture media, suspension modalities, and monitoring techniques that preserve the quality and pluripotency of iPSCs during initiation, expansion, and manufacturing. Highlights: Maintenance of pluripotent status and self-renewal capability are essential for the production of clinical-grade iPSCs for cell therapies. Media and matrix formulations and matrices have evolved through consideration of the signaling pathways that help to sustain pluripotency in iPSC lines and overall process scalability. Matrix- and feeder-free iPSC suspension culture systems overcome the limited scalability of static matrices while supporting iPSC growth and pluripotent status. Development of iPSC monitoring techniques, in silico models, and quality-by-design strategies that incorporate real-time data would enable robust process scalability.