首页> 外文会议>Cell culture engineering conference >INTERROGATING CELL CULTURE POPULATIONS FOR THE SELECTION OF PRODUCTION CELL LINES USING MICROFLUIDIC CULTURING, SINGLE CELL ANALYSIS, AND PREDICTIVE MODELLING
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INTERROGATING CELL CULTURE POPULATIONS FOR THE SELECTION OF PRODUCTION CELL LINES USING MICROFLUIDIC CULTURING, SINGLE CELL ANALYSIS, AND PREDICTIVE MODELLING

机译:使用微流体培养,单细胞分析和预测建模选择生产细胞系的细胞培养群

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Cell line development for manufacturing is a lengthy, multi-step, resource intensive, critical path activity. Attempts to perform in silico modelling and prediction of cell culture has been difficult due to complexities around heterogeneous cell culture populations that rapidly shift over generations under changing selective conditions. For example, early populations will often change as response to media and culturing conditions from a static colony culturing in microtiter plates, to small scale suspension culturing, and finally in a controlled bioreactor processes. As a result, it is challenging to make the final cell line selection early, while predicting future bioprocess performance, and ultimately estimate the protein product quality. We address this challenge by drastically increasing the amount of early cell culture population data obtained through use of emerging single cell technologies. Data obtained is combined with modelling approaches to select the best cell lines upfront to reduce timelines and processing steps. To achieve this, we have implemented a platform from Berkeley Lights that effectively digitalizes most aspects of cell culture. Thousands of individual cell lines can be manipulated, cultured and interrogated on a perfusion nanofluidic chip resulting in extensive data on cell behavior on an individual cell level as well as the populations. Through multivariate predictive modeling of this data, we can predict the performance of candidate clonal cell lines in larger scale production runs. Incorporation of additional single cell analysis such as digital droplet RT-PCR and next generation sequencing further predicts product quality, such as heterogeneity of bispecifics and sequence variant detection. Similar approaches can further be used to then study the stability and integrity of a final CHO cell banks. When combined, single cell interrogation of early culture populations allow for the dematerialization of the CLD process, make better predictions of bioprocess performance, and reduce select the final production clone earlier.
机译:制造的细胞系开发是冗长,多步,资源密集,关键的关键路径活动。由于在改变选择性条件下迅速转移几代内的异质细胞培养群体,因此难以在细胞培养物中进行三种模型和预测细胞培养的预测。例如,早期种群通常会随着对微量滴定板中培养的静态殖民地的响应而变化,以小规模悬浮培养,最后在受控的生物反应器过程中。因此,提前进行最终的细胞系选择是挑战性的,同时预测未来的生物过程性能,最终估计蛋白质产品质量。我们通过急剧增加通过使用新兴的单细胞技术获得的早期细胞培养人群数据量来解决这一挑战。获得的数据与建模方法组合以选择最佳的细胞系,以减少时间表和处理步骤。为实现这一目标,我们已经实施了来自伯克利灯光的平台,有效地将细胞培养的大多数方面都设计成。可以在灌注纳米流体芯片上操纵,培养和询问成千上万个单独的细胞系,导致各个细胞水平以及群体上的细胞行为的广泛数据。通过这种数据的多变量预测建模,我们可以预测较大规模生产中候选克隆细胞系的性能。掺入额外的单细胞分析,例如数字液滴RT-PCR和下一代测序进一步预测了产品质量,例如BISPecifics的异质性和序列变体检测。可以进一步使用类似的方法来研究最终CHO细胞库的稳定性和完整性。当合并时,早期培养种群的单细胞询问允许对CLD过程的废除,更好地预测生物过程性能,并更早地减少选择最终的生产克隆。

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