Model-Based Dynamic Optimization of Monoclonal Antibodies Production in Semibatch Operation—Use of Reformulation Techniques
Model-Based Dynamic Optimization of Monoclonal Antibodies Production in Semibatch Operation—Use of Reformulation Techniques
复制标题
基于模型的半批量操作中单克隆抗体生产的动态优化——重组技术的使用
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
A. Mitsos
中科院分区：
文献类型：
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作者：
C. Kappatou;A. Mhamdi;A. Campano;A. Mantalaris;A. Mitsos
单克隆抗体（mab）是生物制药市场的主导产品之一，具有重要的治疗和诊断应用。这使人们更加注意加强它们的生产过程，在这些过程中，可以利用基于模型的方法成功地进行优化和控制。在这篇手稿中，哺乳动物细胞培养在半批操作中进行了mAb生产的动态优化。为了开发一个适合优化的模型，Quiroga等人（2016）提出了一个基于预测能量的mAb生产模型，该模型采用了包括函数平滑、减小模型尺寸和缩放在内的重新制定步骤。重新制定的模型的优化导致了一个最优喂养策略的推导，考虑到间接的质量措施，稀释效应，和细胞的能量需求。结果表明，采用重新制定的模型可以提高产量，从而表明了较强的深度效益。
Monoclonal antibodies (mAbs) constitute one of the leading products of the biopharmaceutical market with significant therapeutic and diagnostic applications. This has drawn increased attention to the intensification of their production processes, where model-based approaches can be utilized for successful optimization and control purposes. In this manuscript, dynamic optimization of mAb production in mammalian cell cultures in semibatch operation is performed. To develop a model suitable for optimization, reformulation steps consisting of function smoothening, reducing model size, and scaling are applied to a predictive energy-based model for mAb production presented in Quiroga et al. (2016). Optimization of the reformulated model leads to the derivation of an optimal feeding strategy, accounting for indirect quality measures, dilution effects, and the energy requirements of the cells. The results highlight the increased production outcome by using the reformulated model, and thus indicate the strong depe...