EPSRC-SFI: Cutting Edge Analytical Solutions for Smart, Integrated, Efficient Biopharmaceutical Production

曾经有一段时间，小分子在治疗癌症、细菌、真菌和病毒感染等疾病的制药市场占据主导地位。然而，在过去的十年中，生物制药已经彻底改变了慢性疾病的治疗，以及一些孤儿疾病。生物制药研究的进步有助于降低主要疾病的死亡率，也有助于提高预期寿命。目前正在研发的数千种药物中，约有40%是生物制药。这些蛋白质分子有可能为数百万患者提供改变生活的有针对性的个性化治疗，并解决与人口老龄化相关的挑战。虽然用于生物制药生产的哺乳动物细胞培养已经建立，但产品必须在蛋白质结构和糖基化方式（附着在这些蛋白质上的糖的模式）方面具有正确的保真度。因此，在发酵过程中需要对产品质量进行监控，以确认最终产品的安全性和有效性。然而，这些细胞工厂的发展和优化受到当前可用分析技术性能的限制。目前，生物制药工艺开发是以相当经验的方式进行的，基于使用ELISA（一种抗体-抗原检测系统）测量细胞生长、细胞活力和产品表达等有限特征的能力。此外，由于目前使用的分析平台的低通量，以及在发酵系统中缺乏耦合这些特性的能力，直到产品开发周期的后期才采用能够确定产品质量和安全特性的技术。为了解决这一未满足的需求，我们组建了一支独特的团队，他们在生物制剂和蛋白质组学、基于拉曼光谱和质谱的代谢物和分泌蛋白分析的发酵在线分析以及使用多元化学计量学和机器学习的数据处理方面具有互补的技能。这种分组使我们在一个罕见的位置，利用工作在尖端的生物制药，分析化学和信息学。最后，也是最重要的一点，我们在NIBRT（国家生物加工研究和培训研究所）拥有先进的生物制剂生产自动化系统，我们将专注于中国仓鼠卵巢（CHO）细胞的抗体生产，因为这种生产系统在制药市场占据主导地位。我们将开发一个基于以下技术的集成技术平台：(1)质谱法测量培养基中分泌的蛋白质；（ii）在线LC-MS用于测量培养基中分泌或被细胞吸收的小分子；（iii）用于在线监测蛋白质结构和糖基化模式的拉曼光谱。此外，我们将根据分析的反馈使用计算方法来控制发酵，并使用计算机软件来设计发酵过程中的最佳培养基和饲喂方案，以提高蛋白质产量和维持细胞健康。

There was a time when small molecules dominated the pharmaceutical market for the treatment of diseases like cancer as well as bacterial, fungal and viral infections. However, over the last decade biopharmaceuticals have revolutionised the treatment of chronic diseases, as well as a number of orphan diseases. Advances in biopharmaceutical research have contributed to reduction in mortality from major diseases and also contributed towards increased life expectancy. Around 40% of the thousands of pharmaceuticals in the current Research and Development pipeline are biopharmaceuticals. These protein molecules have the potential to offer life-changing targeted personalised treatments to millions of patients and address the challenges associated with ageing populations.While mammalian cell culture for biopharmaceutical production is well established, the product must have the correct fidelity in terms of the structure of the protein and the way in which it is glycosylated (the patterns of sugars attached to these proteins). Therefore, product quality needs to be monitored during the fermentation process to confirm the safety and efficacy of the final product. However, the development and optimisation of these cell factories is limited by the performance of currently available analytical technology. Currently biopharmaceutical process development is performed in a rather empirical manner, based on the ability to measure limited features such as cell growth, cell viability and product expression using ELISA (an antibody-antigen detection system). In addition, technologies that enable product quality and safety characteristics to be determined are not employed until late in the product development cycle due to the low throughput of currently employed analytical platforms, as well as the lack of ability to couple these within the fermentation system. In order to address this unmet need we have assembled a unique team with complementary skills in biologics and proteomics, on-line analysis of fermentations with Raman spectroscopy and mass spectrometry-based metabolite and secreted protein analyses, as well as data processing using multivariate chemometrics and machine learning. This grouping puts us in a rare position to exploit work at the cutting-edge trisection of biopharmaceuticals, analytical chemistry and informatics.Finally, and most importantly, we have access to a state-of-the-art automation system for the production of biologics at NIBRT (National Institute for Bioprocessing Research and Training) and we shall focus on antibody production by Chinese hamster ovary (CHO) cells as this production system dominates the pharmaceutical market. We shall develop an integrated technology platform based on: (i) MS for measuring proteins secreted into the culture media; (ii) at-line LC-MS for measuring small molecules in culture media that are either secreted or taken up by the cells; and (iii) Raman spectroscopy for on-line monitoring of the protein structure and glycosylation pattern. In addition, we shall use computational approaches to control the fermentation based on feed-back from the analytics as well as using computer software for designing optimal growth media and feeding regimes during fermentation to enhance protein production and maintaining cellular health.