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Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control

机译:集成的机器人微型生物反应器平台,用于在线数据处理和过程控制的自动化,并行微生物培养

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During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liquid-handling stations can perform a large number of automated experiments in parallel. Nevertheless, the experimental data sets that are obtained are not always relevant for development of industrial bioprocesses, leading to a high rate of failure during scale-up. We present an automated mini bioreactor platform that enables parallel cultivations in the milliliter scale with online monitoring and control, well-controlled conditions, and advanced feeding strategies similar to industrial processes. The combination of two liquid handlers allows both automated mini bioreactor operation and at-line analysis in parallel. A central database enables end-to-end data exchange and fully integrated device and process control. A model-based operation algorithm allows for the accurate performance of complex cultivations for scale-down studies and strain characterization via optimal experimental redesign, significantly increasing the reliability and transferability of data throughout process development. The platform meets the tradeoff between experimental throughput and process control and monitoring comparable to laboratory-scale bioreactors.
机译:在过程开发过程中,实验搜索空间由可以在特定时间范围内执行的实验数量定义,但也取决于其复杂程度(例如输入,传感器,采样频率,分析)。高通量液体处理站可以并行执行大量自动化实验。然而,获得的实验数据集并不总是与工业生物过程的发展相关,从而导致在放大过程中失败率很高。我们提供了一个自动化的微型生物反应器平台,该平台可通过在线监控和控制,条件可控的条件以及与工业过程类似的高级饲养策略,实现以毫升为单位的平行培养。两种液体处理机的结合,可实现自动化的微型生物反应器操作和并行在线分析。中央数据库支持端到端数据交换以及完全集成的设备和过程控制。基于模型的运算算法可通过优化的实验重新设计,实现用于按比例缩小研究和菌株表征的复杂栽培的准确性能,从而显着提高整个过程开发过程中数据的可靠性和可传递性。与实验室规模的生物反应器相比,该平台满足了实验通量,过程控制和监控之间的折衷。

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