Scale-Down Model Development in ambr systems: An Industrial Perspective

被引:44
作者
Sandner, Viktor [1 ,2 ]
Pybus, Leon P. [3 ]
McCreath, Graham [1 ]
Glassey, Jarka [2 ]
机构
[1] FUJIFILM Diosynth Biotechnol, Proc Dev, Proc Design, Belasis Ave, Billingham TS23 1LH, Cleveland, England
[2] Merz Court Univ Newcastle, Sch Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
[3] FUJIFILM Diosynth Biotechnol, Mammalian Cell Culture, Proc Dev, Billingham TS23 1LH, Cleveland, England
基金
欧盟地平线“2020”;
关键词
high-throughput systems; miniature bioreactors; process characterization; regulatory qualification; scale-down models; CELL-CULTURE PROCESS; MONOCLONAL-ANTIBODY PRODUCTION; PROCESS-DEVELOPMENT REPRODUCIBILITY; COMPUTATIONAL FLUID-DYNAMICS; MULTIVARIATE-ANALYSIS; BIOREACTOR DESIGN; QUALITY; PERFORMANCE; SCALABILITY; PARAMETERS;
D O I
10.1002/biot.201700766
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
High-Throughput (HT) technologies such as miniature bioreactors (MBRs) are increasingly employed within the biopharmaceutical manufacturing industry. Traditionally, these technologies have been utilized for discrete screening approaches during pre-clinical development (e.g., cell line selection and process optimization). However, increasing interest is focused towards their use during late clinical phase process characterization studies as a scale-down model (SDM) of the cGMP manufacturing process. In this review, the authors describe a systematic approach toward SDM development in one of the most widely adopted MBRs, the ambr 15 and 250 mL (Sartorius Stedim Biotech) systems. Recent efforts have shown promise in qualifying ambr systems as SDMs to support more efficient, robust and safe biomanufacturing processes. The authors suggest that combinatorial improvements in process understanding (matching of mass transfer and cellular stress between scales through computational fluid dynamics and in vitro analysis), experimental design (advanced risk assessment and statistical design of experiments), and data analysis (combining uni- and multi-variate techniques) will ultimately yield ambr SDMs applicable for future regulatory submissions.
引用
收藏
页数:11
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