Maximising bioproduction in CHO cell by interdisciplinary engineering and AI

通过跨学科工程和人工智能最大化 CHO 细胞的生物生产

• 批准号: 10029053
• 金额: $ 31.17万
• 依托单位: GENENET TECHNOLOGY (UK) LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10029053
• 关键词: Maximising; bioproduction; CHO; cell; interdisciplinary

Although CHO cells are one of the most highly employed cell lines in bioproduction (with \>£100 Billion market), current commercially available CHO cells inability to adapt and restore cell balance leads to stress-induced apoptosis and undesirable protein modifications. Further, the biotechnology industry lacks in-line methods to examine the actual cell viability during production in small or large-scale experiments. These pain points limit CHO-based recombinant protein production's efficiency and yield, leading to a considerable waste of resources, time and materials in manufacturing.GeneNet Technology, in collaboration with CPI (Centre for Process Innovation) and Taiwan based Cytena BPS and Instant NanoBiosensor, is here to engineer a stress sensing genetic circuit and AI cell embedded to current bioproduction (incubator) in real-time testing method. Combining cutting edge technology from Cytena BPS' next-generation bioreactor, which allows culture fine-tuning and real-time data collection from culturing and physiological conditions, and Instant NanoBiosensors' Fiber Optic Particle Plasmon Resonance technology which detects biomarker expression, we will gather comprehensive culturing, physiological and biomarker data during CHO cell bioproduction. This comprehensive data will be fed into GeneNet's ground-breaking technology, Artificial neural network (ANN) genetic circuits. ANN genetic circuits are the cutting-edge technology in synthetic biology and genetic engineering. In the past decade, synthetic genetic circuits only apply simple logic (AND/OR/NOT) gates to biocomputing. GeneNet's ground-breaking technology makes genetic circuits analogous to deep learning computers, turning CHO cells into smarter AI computers. All this will enable us to engineer smart, stress-sensing CHO cells to maximise protein production efficiency and yield, benefiting our downstream clients and wider industry and society as a whole.

尽管CHO细胞是生物生产中最常用的细胞系之一（具有1000亿英镑的市场），但目前市售的CHO细胞不能适应和恢复细胞平衡导致应激诱导的细胞凋亡和不期望的蛋白质修饰。此外，生物技术行业缺乏在线方法来检查在小规模或大规模实验中生产期间的实际细胞活力。这些痛点限制了基于CHO的重组蛋白生产的效率和产量，导致生产过程中相当大的资源，时间和材料浪费。GeneNet Technology与CPI（工艺创新中心）和台湾Cytena BPS和Instant NanoBiosensor合作，设计了一种压力传感基因电路和人工智能细胞嵌入当前生物生产（培养箱）的实时测试方法。结合Cytena BPS下一代生物反应器的尖端技术（允许培养微调和从培养和生理条件中实时收集数据）和Instant NanoBiosensors的光纤粒子等离子体共振技术（检测生物标志物表达），我们将在CHO细胞生物生产过程中收集全面的培养、生理和生物标志物数据。这些全面的数据将被输入GeneNet的突破性技术，人工神经网络（ANN）遗传电路。人工神经网络遗传电路是合成生物学和遗传工程的前沿技术。在过去的十年中，合成遗传电路只将简单的逻辑（AND/OR/NOT）门应用于生物计算。GeneNet的突破性技术使基因电路类似于深度学习计算机，将CHO细胞变成更智能的AI计算机。所有这些都将使我们能够设计智能的、压力敏感的CHO细胞，以最大限度地提高蛋白质生产效率和产量，使我们的下游客户以及更广泛的行业和整个社会受益。