Visual identification, analysis and modelling of sterilising grade filtration for liposome enveloped products

该项目寻求解决的生物工艺挑战：无菌过滤对生物药物的生产和安全至关重要。这些过滤系统的性能是工业上相关的挑战，随着包括病毒载体和脂质体在内的下一代治疗剂的发展，该挑战将继续沿着。这些产品在无菌过滤过程中可能存在困难，因为它们相对较大的尺寸导致保留在过滤器结构内。新型冠状病毒mRNA疫苗的成功凸显了脂质体日益重要的地位，该疫苗被包裹在脂质体中并在脂质体中递送。在这个项目中，我们将结合联合收割机共聚焦显微镜和x射线计算机断层扫描的高分辨率成像技术来测量生物成分在滤膜内的截留手段。了解这些机制将有助于合理确定这些产品无菌过滤的操作条件、膜类型和配方条件。目的：- 开发成像方法，以可视化脂质体产品的进料保留，在一系列过滤器类型中的制剂，同时最小化样品干扰-当复杂制剂通过或阻塞过滤器时识别复杂制剂中的不同污垢-联合收割机信息与补充技术结合，以确定污垢发生的位置和原因，以开发预测模型-将获得的知识应用于各种Pall系统，例如折叠片筒和TFF系统，以证明研究项目的稳健性。项目描述：在脂质包封产品（例如mRNA疫苗）的无菌过滤过程中性能的恶化是工业规模生物过程的常见问题[1，2]。在UCL和Pall-UCL卓越中心，各种高分辨率成像技术已成功用于可视化分离介质，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。目的是确定这些材料的结构特征，这些结构特征决定了它们的生物过程性能[3-5]。本EngD旨在应用这些方法来了解Pall无菌过滤分离膜系统。每种成像技术都有固有的优势和局限性，我们的目标是补充相关方法以最大限度地收集信息。例如，将X射线CT测量膜的3D结构的能力与共聚焦显微镜结合以识别荧光标记的生物成分[5]，能够识别这些成分被捕获在膜内的区域。然后，这些可以与结构特征相关联，例如内部孔径减小或弯曲度增加。本研究将联合收割机结合这些不同技术的信息，以建立一个预测脂质体无菌过滤膜性能的机理模型[6]。本项目期间将使用多种无菌级膜和脂质体类型的研究和比较来加深对该机理的理解。我们能够在项目中利用最新的微流体脂质体合成技术（由Precision NanoSystems开发）来进一步实现这一目标。

Bioprocess challenge the project seeks to address:Sterile filtration is essential to the manufacture and safety of biological medicines. The performance of these filtration systems is an industrially relevant challenge that continues to evolve along with next generation therapeutics including viral vectors and liposomes. These products can present difficulties during sterile filtration due to their relatively large size leading to retention within the filter structure. The increasing importance of liposomes has been highlighted by the success of Covid-19 mRNA vaccines which are enveloped and delivered in liposomes. In this project we will combine the high-resolution imaging techniques of confocal microscopy and x-ray computed tomography to measure the means of entrapment for biological components within the filter membrane. Understanding these mechanisms will enable a rational approach to determining operating conditions, membrane type and formulation conditions for sterile filtration of these products.Objectives:- Develop imaging approaches to visualise feed material retention for liposome products, formulations in a range of filter types whilst minimising sample interference- Identify different foulants in complex formulations as they pass or block the filter- Combine information with complementary techniques to determine where and why fouling is occurring to develop predictive models- Apply the knowledge gained to various Pall systems, for example pleated sheet cartridges and TFF systems to demonstrate robustness of the research projectProject Description:Deterioration of performance during sterile filtration of lipid enveloped products e.g. mRNA vaccines is a commonplace issue for industrial scale bioprocesses [1, 2]. At UCL and within the Pall-UCL Centre of Excellence various high-resolution imaging techniques have been successfully used to visualise separation media, including X-ray CT, confocal microscopy, electron microscopy and focused ion beam microscopy. The objective is to characterise the structural features of these materials that determine their bioprocess performance [3-5]. This EngD aims to apply these methods in order to understand Pall sterile filtration separation membrane systems.Each imaging technique has inherent advantages and limitations, we aim to complement relevant approaches to maximise information gathered. For example combining the capabilities of X-ray CT to measure the 3D structure of the membrane with confocal microscopy to identify fluorescently tagged biological components [5] enables the identification of the regions where those components are trapped within a membrane. These can then be correlated with structural features such as an internal pore size decrease or tortuosity increase. The research will combine the information from these various techniques in order to build towards a mechanistic model [6] to predict sterile filtration membrane performance for liposomes.Investigating and comparing multiple sterile grade membranes and liposome types during this project will be used to deepen this mechanistic understanding. We are able to make use of the latest microfluidic liposome synthesis technology (developed by Precision NanoSystems) within the project to further this objective.