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首页> 外文会议>Conference on single-use technologies II: bridging polymer science to biotechnology applications >ANALYTICAL AND DATA STRATEGY FOR CONTINUOUS DOWNSTREAM MANUFACTURING
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ANALYTICAL AND DATA STRATEGY FOR CONTINUOUS DOWNSTREAM MANUFACTURING

机译：连续下游制造的分析和数据策略

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As advances emerge in developing continuous biomanufacturing processes, there is an increased need to deploy PAT tools to characterize, monitor, and control key quality attributes and a criticality to have a data infrastructure to support the immense amount of information being generated. While the desire for these tools exists in traditional batch processing, in a continuous operation, these become a requirement to ensure consistent product quality and enable proactive approaches in maintaining performance. The ultimate goal is to deploy PAT tools to reliably provide real-time information on product and process impurities throughout the entire operation. However, in its current state, there is a reliance on a mixture of inline, at-line, and offline technologies. By identifying the time criticality of CQAs, efforts can be focused on where to prioritize real-time measurements or instead, quicker or more automated testing for a subset of analytics. This work describes the application of this approach in the development of small-scale, compact in-line UV instruments to measure realtime protein concentration and in the integration of an automated sampling system with at-line and offline instrumentation for in-process impurity characterization. Introduction of these PAT tools add to the complexity of the data infrastructure as it introduces requirements for platforms capable of supporting spectral data, chemometric model deployment, spectral instrument management, and time-alignment of discrete data. With the vast amount of information produced in a continuous environment, interface and analysis tools need to be developed so that any end-user can digest data into a format that easily allows them to gain insight into an ongoing batch. This work will highlight the data architecture of the continuous platform, with a focus on software tools selected for aggregation and real-time data visualization. The capabilities of these software packages were demonstrated through a proof-of-concept study using single-pass tangential flow filtration (SPTFF) as a model unit operation, which allowed integration of continuous, spectral, and discrete data. These tools allowed scientists to go from viewing real-time data across multiple, equipment-specific software to one consolidated interface, which in turn reduced time spent in compiling data for analysis and reporting. In addition, advanced capabilities of deploying model predictive control in SPTFF were demonstrated to show the application of a closed loop process control in continuous manufacturing.
机译：随着开发连续生物制造工艺方面的进步，对部署PAT工具以表征，监视和控制关键质量属性的需求日益增长，并且越来越需要具有支持大量正在生成的信息的数据基础架构。尽管在传统的批处理过程中存在对这些工具的需求，但在连续操作中，这些成为确保一致的产品质量并采用主动方法保持性能的要求。最终目标是部署PAT工具，以在整个操作过程中可靠地提供有关产品和工艺杂质的实时信息。但是，在当前状态下，依赖于内联，联机和脱机技术的混合。通过确定CQA的时间紧迫性，可以将工作重点放在确定实时测量优先级的位置上，或者着重于对子集的分析进行更快或更自动化的测试。这项工作描述了这种方法在开发小型，紧凑的在线UV仪器以测量实时蛋白质浓度以及将自动采样系统与在线和离线仪器集成以进行过程中杂质表征中的应用。这些PAT工具的引入增加了数据基础架构的复杂性，因为它引入了对能够支持光谱数据，化学计量模型部署，光谱仪器管理以及离散数据的时间对齐的平台的要求。由于在连续的环境中产生大量的信息，因此需要开发接口和分析工具，以便任何最终用户都可以将数据摘要为一种格式，该格式可以轻松地使他们深入了解正在进行的批处理。这项工作将重点介绍连续平台的数据体系结构，重点是为聚合和实时数据可视化选择的软件工具。通过使用单次切向流过滤（SPTFF）作为模型单元操作的概念验证研究证明了这些软件包的功能，该模型允许集成连续数据，光谱数据和离散数据。这些工具使科学家们可以从跨多个特定于设备的软件查看实时数据到一个统一的界面，从而减少了为进行分析和报告而编译数据所花费的时间。此外，还演示了在SPTFF中部署模型预测控制的高级功能，以展示闭环过程控制在连续制造中的应用。

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