Understanding the impact of the engineering environment on transient transfection and process scale-up

瞬时基因表达（TGE）传统上用于快速生产重组蛋白，以支持药物开发期间的临床前研究。这项技术涉及将质粒DNA引入哺乳动物细胞，然后在有限的时间内（通常是两周）表达感兴趣的蛋白质。近年来，该技术取得了一些进展，使滴度从mg/L增加到g/L。这些进步，加上稳健、可扩展和定义明确的流程，为探索TGE作为快速生产临床材料的替代工具（例如，在大流行情况下或在个性化药物的背景下）提供了机会。本研究的目的是阐明转染剂添加（体积、浓度等）、搅拌模式、生物反应器几何形状和操作条件对瞬时转染过程中细胞生长、DNA摄取和生产力的影响，并应用研究结果来定义一种适用于200L规模的最佳缩放方法。该提案是使用缩小的生物反应器系统来研究这一过程，该系统最准确地反映了几何形状和流动条件，这是建立在伦敦大学学院已经可用的缩小模型和流体动力学表征方法的基础上的（见下文），以实现快速进展和产生结果。博士候选人将为项目做出贡献，并将专注于以下目标：通过定制系统中的高级工程特性来提高对过程的理解。混合动力学将使用基于当前工艺的模型系统来评估不同操作条件下的混合动力学，在摇晃和搅拌生物反应器配置中，流体流变学和进料位置的影响将使用工业系统的缩小模拟来评估。在特定的生物反应器中建立最佳转染条件。这也将使不同生物反应器几何形状之间的转染条件的可靠的规模转换，即波浪到搅拌配置。进行大规模的生物验证实验。将建立一个瞬态转染过程模型，并结合相关分析和实验，根据表征研究的信息，使用搅拌策略、曝气和进料位置进行实验。该项目将成为伦敦大学学院-阿斯利康卓越中心（CoE）的一部分，该中心是伦敦大学学院（UCL）和阿斯利康之间的联合合作。该中心的目标是为上游和下游生物制药加工活动生成一套预测决策工具。这涉及到微尺度和高通量研究的应用，涉及到相关发展、多变量数据分析（MVDA）、过程经济学和离散事件优化。候选人将加入一个由博士和博士后研究人员组成的团队，在CoE中从事上游和下游处理以及建模工具的工作。该项目将由伦敦大学学院生化工程系与阿斯利康在剑桥（英国）和盖瑟斯堡（美国）的基地合作主持。

Transient gene expression (TGE) is traditionally used for rapid production of recombinant proteins to support preclinical studies during drug development. This technology involves introducing plasmid DNA into mammalian cells which then express the protein of interest over a limited period of time, typically two weeks. In recent years, there have been some advances in this technology which have led to an increase in titres from mg/L to g/L. These advances, combined with a robust, scalable and well defined process, provide an opportunity to explore TGE as an alternative tool for rapid production of clinical material (e.g. in a pandemic situation or in the context of personalised medicines). The purpose of this research is to elucidate the effect of transfection agent addition (volume, concentration etc), agitation mode, bioreactor geometry and operating conditions on cell growth, DNA uptake, and productivity in a transient transfection process and apply the findings to define an optimal scaling methodology valid up to 200L scale. The proposal is to study the process using scale-down bioreactor systems that most accurately reflect the geometry and flow conditions This builds upon scale-down models and fluid dynamics characterisation methods already available at UCL (see below) to enable rapid progress and generation of results. The doctoral candidate will contribute to the project and will focus on the following objectives:Improve process understanding through advanced engineering characterization in customised systems. Mixing kinetics will be evaluated for different operating conditions using a model system based on current processes, in both rocked and stirred bioreactor configurations, and the impact of fluid rheology and feed location will be evaluated using scale-down mimics of the industrial systems.Establish optimum transfection conditions in specified bioreactor geometries. This will also enable reliable scale translation of transfection conditions between different bioreactor geometries i.e. wave to stirred configurations.Conduct biological verification experiments at scale. A transient transfection process model will be established with associated analytics and experiments will be run using agitation strategy, aeration and feed location as informed by the characterization studies.This project will be part of the UCL-AstraZeneca Centre of Excellence (CoE) that is a joint collaboration between University College London (UCL) and AstraZeneca. The centre's aim is to generate a set of predictive decisional tools for both upstream and downstream biopharmaceutical processing activities. This involves the application of micro-scale and high-throughput studies involving correlation development, multivariate data analysis (MVDA), process economics and discrete-event optimisation. The candidate will join a team of PhD and postdoctoral researchers working in the CoE across upstream and downstream processing as well as modelling tools. The project will be hosted by the department of Biochemical Engineering at University College London in collaboration with AstraZeneca sites across Cambridge (UK) and Gaithersburg (US).