简化工艺开发和放大:风险评估以减少初级蛋白质回收的工作量

IF 3.7 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Biochemical Engineering Journal Pub Date : 2024-10-05 DOI:10.1016/j.bej.2024.109513
Markus C. Berg , Yvonne Sorz , Rainer Hahn , Michael C. Martinetz , Cécile Brocard , Astrid Dürauer
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引用次数: 0

摘要

风险评估是 "质量源于设计 "战略不可或缺的一个方面,它可以识别从工艺开发到技术转让等生物制药生产各个阶段的潜在障碍。我们探索了流程图、根本原因分析和失效模式及影响分析,以评估细菌细胞破坏的放大及其对离心和过滤步骤的影响。石川图显示,本研究通过实验收集的有关均质器阀门设计对产品释放、杂质分布、粒度分布、粘度和 dsDNA 片段大小影响的数据缺失。对微量、实验室和中试规模细胞破碎的细胞裂解物进行了上述参数分析。确定了每个规模上影响这些输出参数的工艺参数。微量级细胞破碎是在珠磨机中进行的。高压均质法用于实验室和中试规模。通过珠磨机进行细胞破碎,得到的匀浆产品和杂质含量与工作台规模的匀浆产品和杂质含量相当,但粘度高出 3 倍,dsDNA 片段明显更大,分别为 8.0 kbp 而不是 1.0 kbp。微型压力流量曲线确定了 dsDNA 片段大小对澄清过程中的过滤性能至关重要。将风险评估、微尺度细胞解体和台架尺度压力流量曲线结合起来,可以进行选择性和高效的工艺开发,并扩大初级回收步骤的规模。
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Streamlining process development and scale-up: Risk assessment to reduce workload in primary protein recovery
Risk assessment is an integral aspect of the Quality-by-Design strategy to identify potential obstacles at every stage of biopharmaceutical production, from process development to tech transfer. We explored flow process chart, root cause analysis, and failure mode and effects analysis, to assess the scale-up of bacterial cell disruption and its influence on centrifugation and filtration steps. The Ishikawa diagram suggests that data on the impact of homogenizer valve design on product release, impurity profile, particle size distribution, viscosity, and dsDNA fragment size are missing which were collected experimentally for this study. Cell lysates from micro-, lab- and pilot scales cell disruption were analyzed for the above-mentioned parameters. Process parameters affecting these output parameters were identified on each individual scale. Cell disruption on the micro scale was performed in a bead mill. High pressure homogenization was used on lab- and pilot scales. Cell disintegration by bead milling delivers homogenates of product and impurity content comparable to those on bench scale but with 3-fold higher viscosity and significantly larger dsDNA fragments, 8.0 instead of 1.0 kbp, respectively. Miniaturized pressure flow curves identified dsDNA fragment sizes as critical for filter performance during clarification. Combining risk assessment, micro scale cell disintegration and bench scale pressure flow curves allows for selective and efficient process development, and scale up for primary recovery steps.
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来源期刊
Biochemical Engineering Journal
Biochemical Engineering Journal 工程技术-工程:化工
CiteScore
7.10
自引率
5.10%
发文量
380
审稿时长
34 days
期刊介绍: The Biochemical Engineering Journal aims to promote progress in the crucial chemical engineering aspects of the development of biological processes associated with everything from raw materials preparation to product recovery relevant to industries as diverse as medical/healthcare, industrial biotechnology, and environmental biotechnology. The Journal welcomes full length original research papers, short communications, and review papers* in the following research fields: Biocatalysis (enzyme or microbial) and biotransformations, including immobilized biocatalyst preparation and kinetics Biosensors and Biodevices including biofabrication and novel fuel cell development Bioseparations including scale-up and protein refolding/renaturation Environmental Bioengineering including bioconversion, bioremediation, and microbial fuel cells Bioreactor Systems including characterization, optimization and scale-up Bioresources and Biorefinery Engineering including biomass conversion, biofuels, bioenergy, and optimization Industrial Biotechnology including specialty chemicals, platform chemicals and neutraceuticals Biomaterials and Tissue Engineering including bioartificial organs, cell encapsulation, and controlled release Cell Culture Engineering (plant, animal or insect cells) including viral vectors, monoclonal antibodies, recombinant proteins, vaccines, and secondary metabolites Cell Therapies and Stem Cells including pluripotent, mesenchymal and hematopoietic stem cells; immunotherapies; tissue-specific differentiation; and cryopreservation Metabolic Engineering, Systems and Synthetic Biology including OMICS, bioinformatics, in silico biology, and metabolic flux analysis Protein Engineering including enzyme engineering and directed evolution.
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