3D measurement of fouling in membrane filtration: towards model based investigation and design

生物工艺挑战该项目旨在解决膜过滤系统的污染是一个日益严重的问题，由于上游滴度和相关的负担增加[1]。这些复杂进料含有大量不需要的材料，这些材料可通过几种结垢机制对性能产生有害影响，这些结垢机制可减少通过膜结构的渗透并改变筛分系数[2]。在这里，我们的目标是发展一个更好地了解这些机制，使用测量和可视化的方法，将通知建模和模拟工作的核心，使改进的膜设计和options.Objectives-要先进的成像方法，以测量污垢的位置内的膜和饲料类型的代表目前的生物处理的挑战-结合联合收割机共聚焦显微镜和x-射线光电子显微镜，射线CT技术以新的分辨率水平确定膜内污垢的位置和种类。-在多个长度尺度上使用这些方法，从最初的小样品到折叠片盒和单程TFF系统，以确定放大方法的影响。将获得的三维数据与建模方法相结合。项目描述过滤过程中的污垢是工业生物过程中常见的问题[1，2]，需要考虑各种目标产品尺寸和必须去除的杂质。在伦敦大学学院和欧洲中心内，各种高分辨率成像技术已被应用于可视化和检测Pall分离介质，包括X射线CT、共聚焦显微镜、电子显微镜和聚焦离子束显微镜[3-5]。这表明，以互补的方式利用多种技术可以克服个别方法的缺点，并最大限度地收集有关样本的数据。在这个共聚焦和超荧光显微镜项目中，将使光学切片和大视场成像分别标记饲料，以确定在不同特性，如孔径和不对称性的Pall过滤膜内的截留材料的位置和组成。该研究将建立在一个CoE MSc项目的基础上，该项目使用共聚焦显微镜应用于双层膜，研究脂质体截留在Pall膜内的位置。膜系统这将通过使用具有不同尺寸和组成的脂质体材料来进一步实现，以便模拟产物如慢病毒和潜在的污染物，例如可以在成像之前单独标记的细胞外囊泡。这些模拟物将被设计为与其他CoE EngD项目（如慢病毒制造）保持一致，生成的数据将支持CoE愿景。[1]Gronemeyer等人（2014），[2]，Fallahianbijan等人（2019）[3]，约翰逊等人（2017）[4]约翰逊等人（2018），[5]杰克逊等人（2014）拟定时间表第1年：成像和分析培训（例如共聚焦），脂质体的初始膜实验Year 2：Expand media（包括双层）和配方（转向慢病毒的脂质体模拟物）第3年：将联合收割机结果与CoE中的其他成像数据结合，研究多长度尺度成像第4年：完成研究，比较lenti模拟与实际，CoE成像协作，提交论文

Bioprocess challenge the project seeks to address Fouling of membrane filtration systems is an ever-increasing issue due to upstream titre and associated burden increases [1]. These complex feeds contain a large array of unwanted material that can detrimentally affect performance through several fouling mechanisms that can reduce permeation through membrane structure and change sieving coefficients [2]. Here we aim to develop a better understanding of these mechanisms using a measurement and visualisation approach that will inform modelling and simulation efforts core the CoE vision of enabling improved membrane design and operation.Objectives- To advance imaging approaches to measure foulant locations within membrane and feed types representative of current bioprocessing challenges - To combine confocal microscopy and x-ray CT techniques to determine at new levels of resolution the location and species of foulant within membranes.- Use these methods at multiple length scales, from small samples initially up to pleated sheet cartridges and single pass TFF systems to determine the impact of scale-up approach.- Interface the three dimensional data acquired with modelling approaches.Project DescriptionFouling during filtration is a commonplace issue for industrial bioprocesses [1, 2], with a variety of target product sizes to consider and impurities that must be removed. At UCL and within the CoE various high-resolution imaging techniques have been applied to visualise and characterise Pall separation media, including x-ray CT, confocal microscopy, electron microscopy and focused ion beam microscopy [3-5]. This has shown that utilising multiple techniques in a complementary manner can overcome the shortcomings of individual methods and maximise the data gathered about a sample. In this project confocal and super-fluorescence microscopy, will enable optical slicing and large field of view imaging respectively on tagged feeds to identify the location and composition of entrapped material within Pall filtration membranes of varying characteristics such as pore size and asymmetry.The research would build upon a CoE MSc project that investigated the location liposome entrapment within Pall membranes using confocal microscopy applied to dual layer membrane systems. It would further this by using liposome material with differing sizes and compositions in order to mimic products such as lentivirus and potential foulants e.g. extracellular vesicles that could be individually labelled prior to imaging. These mimics will be designed to align with other CoE EngD projects such as in lentivirus manufacture, and the data generated will support the CoE vision.[1] Gronemeyer et al. (2014), [2], Fallahianbijan et al. (2019) [3], Johnson et al. (2017)[4] Johnson et al. (2018), [5] Jackson et al. (2014)Proposed timelineYear 1: Imaging and analysis training (e.g. confocal), initial membrane experiments with liposomesYear 2: Expand media (including dual layer) and formulation (move to liposome mimic of lentivirus) Year 3: Combine results with other imaging data in the CoE, investigate multi-length scale imagingYear 4: Complete studies, compare lenti mimic to actual, CoE imaging collaboration, submit thesis