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Technology outlook for real-time quality attribute and process parameter monitoring in biopharmaceutical development-A review

机译:生物制药开发中实时质量属性和过程参数监测技术前景 - 评论

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摘要

Real-time monitoring of bioprocesses by the integration of analytics at critical unit operations is one of the paramount necessities for quality by design manufacturing and real-time release (RTR) of biopharmaceuticals. A well-defined process analytical technology (PAT) roadmap enables the monitoring of critical process parameters and quality attributes at appropriate unit operations to develop an analytical paradigm that is capable of providing real-time data. We believe a comprehensive PAT roadmap should entail not only integration of analytical tools into the bioprocess but also should address automated-data piping, analysis, aggregation, visualization, and smart utility of data for advanced-data analytics such as machine and deep learning for holistic process understanding. In this review, we discuss a broad spectrum of PAT technologies spanning from vibrational spectroscopy, multivariate data analysis, multiattribute chromatography, mass spectrometry, sensors, and automated-sampling technologies. We also provide insights, based on our experience in clinical and commercial manufacturing, into data automation, data visualization, and smart utility of data for advanced-analytics in PAT. This review is catered for a broad audience, including those new to the field to those well versed in applying these technologies. The article is also intended to give some insight into the strategies we have undertaken to implement PAT tools in biologics process development with the vision of realizing RTR testing in biomanufacturing and to meet regulatory expectations.
机译:通过在关键单位操作中整合分析的实时监测生物过程是通过设计制造和实时释放(RTR)的生物制药的最重要的质量必需品之一。明确定义的过程分析技术(PAT)路线图能够在适当的单元操作中监控关键过程参数和质量属性,以开发能够提供实时数据的分析范例。我们认为,不仅需要将分析工具集成到生物过程中的全面的帕特路线图,还应涉及用于自动数据管道,分析,聚合,可视化和智能实用性的高级数据分析,如机器和深层学习过程理解。在本次综述中,我们讨论了跨越振动光谱,多变量数据分析,多元色谱,质谱,传感器和自动采样技术的广泛的PAT技术。我们还根据我们在临床和商业制造方面的经验,进入数据自动化,数据可视化和智能实用性在PAT中的数据自动化,数据可视化和智能实用性。该评价为广泛的受众提供服务,包括该领域的新人,以适用于应用这些技术的人。本文还旨在介绍我们在生物制造中实现RTR测试的愿景,并达到生物制造过程开发的策略深入了解我们所承担的战略。

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