应用流程表建模进行调度和去瓶颈分析,以支持血浆治疗蛋白纯化工艺的开发和放大

IF 3.7 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Biochemical Engineering Journal Pub Date : 2024-09-16 DOI:10.1016/j.bej.2024.109501
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引用次数: 0

摘要

血浆分馏是生产白蛋白和免疫球蛋白 G 等治疗和诊断蛋白质的关键工艺。为了支持工艺开发,我们采用了基于流程表建模的方法来提高生产效率和生产力,同时最大限度地减少资源投资。首先建立的流程表模型代表了中试规模的基线药物生产工艺,其操作参数是从 CSL Behring 实验室规模实验中推断出来的。为了提高运行效率和节约成本,采用了吞吐量分析法,通过新的工艺设计、调度和瓶颈识别来提高批次吞吐量。通过实施这些策略,只需在流程中增加一名操作员和一个缓冲制备罐,就能将批次吞吐量提高 47.2%。此外,在采用一种涉及多次提取初始材料(糊状物)的新策略后,批次产量翻了一番,运营成本降低了 36.1%。为了评估改进设计的性能并验证模型结果,CSL Behring 公司进行了两次萃取的中试规模实验,并与模型预测结果进行了比较,结果一致。这项工作证明了流程图建模在促进从实验室规模到中试规模的工艺开发方面的潜力,从而以有限的资源投资促进具有成本效益的高效生产。
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Application of flowsheet modeling for scheduling and debottlenecking analysis to support the development and scale-up of a plasma-derived therapeutic protein purification process

Plasma fractionation stands as a pivotal process for the production of therapeutic and diagnostic proteins, such as albumin and immunoglobulin G. Besides these two primary proteins in human plasma, numerous other proteins can be purified for therapeutic purposes. To support process development, a flowsheet modeling-based approach is utilized to improve production efficiency and productivity while minimizing the resource investments. The flowsheet model is first built to represent the baseline drug substance production process at pilot-scale, with operating parameters extrapolated from lab-scale experiments conducted at CSL Behring. To improve operational efficiency and save costs, throughput analysis is applied to enhance the batch throughput through new process design, scheduling, and bottleneck identification. Through implementing the strategies, the batch throughput could be increased by 47.2 % by introducing one additional operator and one buffer preparation tank into the process. Furthermore, after applying a new strategy involving multiple extractions of the initial material (paste), the batch throughput was doubled, with operating cost of goods reduced by 36.1 %. To assess the performance of the modified design and validate the model results, the pilot-scale experiments with two extractions were performed by CSL Behring and compared with model predictions, resulting in good agreement. This work demonstrates the potential of flowsheet modeling in facilitating process development from lab-scale to pilot-scale, fostering cost-effective and efficient production with limited resource investment.

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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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