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

EPSRC-SFI:用于智能、集成、高效生物制药生产的尖端分析解决方案

基本信息

  • 批准号:
    EP/V042882/1
  • 负责人:
  • 金额:
    $ 56.27万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 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

项目摘要

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.
曾经有一段时间,小分子药物在治疗癌症、细菌、真菌和病毒感染等疾病的药物市场上占据主导地位。然而,在过去的十年中,生物制药已经彻底改变了慢性病的治疗,以及一些孤儿疾病。生物制药研究的进展有助于降低重大疾病的死亡率,也有助于提高预期寿命。目前研发管道中的数千种药物中约有40%是生物药物。这些蛋白质分子有可能为数百万患者提供改变生活的靶向个性化治疗,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成熟,但产品必须在蛋白质结构和糖基化方式(糖连接到这些蛋白质的模式)方面具有正确的保真度。因此,在发酵过程中需要监测产品质量,以确认最终产品的安全性和有效性。然而,这些细胞工厂的开发和优化受到当前可用分析技术性能的限制。目前,生物制药工艺开发以相当经验的方式进行,基于使用ELISA(抗体-抗原检测系统)测量有限特征(例如细胞生长、细胞活力和产物表达)的能力。此外,由于目前采用的分析平台的低通量以及缺乏在发酵系统内偶联这些的能力,使得能够确定产品质量和安全特性的技术直到产品开发周期的后期才被采用。为了满足这一未满足的需求,我们组建了一支独特的团队,他们在生物学和蛋白质组学、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变量化学计量学和机器学习的数据处理方面具有互补的技能。这一分组使我们处于一个难得的位置,可以利用生物制药、分析化学和信息学三分之一的前沿工作。最后,也是最重要的,我们可以在NIBRT使用最先进的生物制品生产自动化系统(国家生物加工研究和培训研究所),我们将重点关注中国仓鼠卵巢(CHO)的抗体生产细胞,因为这种生产系统主导着制药市场。我们将开发一个基于以下的集成技术平台:(i)MS,用于测量分泌到培养基中的蛋白质;(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;以及(iii)拉曼光谱,用于在线监测蛋白质结构和糖基化模式。此外,我们将使用计算方法来控制发酵,基于分析的反馈,以及使用计算机软件来设计发酵期间的最佳生长培养基和补料方案,以提高蛋白质产量并保持细胞健康。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Focusing ion funnel-assisted ambient electrospray enables high-density and uniform deposition of non-spherical gold nanoparticles for highly sensitive surface-enhanced Raman scattering.
聚焦离子漏斗辅助环境电喷雾能够实现非球形金纳米颗粒的高密度和均匀沉积,从而实现高灵敏度的表面增强拉曼散射。
  • DOI:
    10.1039/d3an01021j
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Akbali B
  • 通讯作者:
    Akbali B
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Royston Goodacre其他文献

The role of reporting standards for metabolite annotation and identification in metabolomic studies
  • DOI:
    10.1186/2047-217x-2-13
  • 发表时间:
    2013-10-16
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Reza M Salek;Christoph Steinbeck;Mark R Viant;Royston Goodacre;Warwick B Dunn
  • 通讯作者:
    Warwick B Dunn
Metabolomics and metabolite profiling
  • DOI:
    10.1007/s00216-013-6939-5
  • 发表时间:
    2013-04-17
  • 期刊:
  • 影响因子:
    3.800
  • 作者:
    Rainer Schuhmacher;Rudolf Krska;Wolfram Weckwerth;Royston Goodacre
  • 通讯作者:
    Royston Goodacre
Neural networks and olive oil
神经网络与橄榄油
  • DOI:
    10.1038/359594a0
  • 发表时间:
    1992-10-15
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Royston Goodacre;Douglas B. Kell;Giorgio Bianchi
  • 通讯作者:
    Giorgio Bianchi
Mind your Ps and Qs – Caveats in metabolomics data analysis
  • DOI:
    10.1016/j.trac.2024.118064
  • 发表时间:
    2025-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yun Xu;Royston Goodacre
  • 通讯作者:
    Royston Goodacre
The role of metabolites and metabolomics in clinically applicable biomarkers of disease
  • DOI:
    10.1007/s00204-010-0609-6
  • 发表时间:
    2010-10-16
  • 期刊:
  • 影响因子:
    6.900
  • 作者:
    Mamas Mamas;Warwick B. Dunn;Ludwig Neyses;Royston Goodacre
  • 通讯作者:
    Royston Goodacre

Royston Goodacre的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Royston Goodacre', 18)}}的其他基金

Ultra-high-throughput mass spectrometry for quantitative metabolomics
用于定量代谢组学的超高通量质谱
  • 批准号:
    BB/W019558/1
  • 财政年份:
    2022
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
Multi-purpose instrument for advanced Raman spectroscopy techniques
用于先进拉曼光谱技术的多用途仪器
  • 批准号:
    BB/L014823/1
  • 财政年份:
    2014
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
Combing biophysical and 'omics methods for understanding the basis of blood clotting and haemostasis, and how to modify it
结合生物物理学和组学方法来了解凝血和止血的基础以及如何对其进行修改
  • 批准号:
    BB/L025752/1
  • 财政年份:
    2014
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
Raman spectroscopy as a novel analytical bioprocessing tool for PAT
拉曼光谱作为 PAT 的新型分析生物处理工具
  • 批准号:
    BB/G010250/1
  • 财政年份:
    2009
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
Analysis of the dynamics and robustness of metabolic networks in a genetically engineered Pseudomonas fluorescens with inducible exo-polysaccharide pr
具有诱导性外多糖蛋白的基因工程荧光假单胞菌代谢网络的动力学和鲁棒性分析
  • 批准号:
    BB/F003447/1
  • 财政年份:
    2007
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant

相似国自然基金

致病疫霉RxLR效应蛋白SFI7抑制马铃薯ETI免疫反应的分子机制研究
  • 批准号:
    31800134
  • 批准年份:
    2018
  • 资助金额:
    24.0 万元
  • 项目类别:
    青年科学基金项目
马铃薯致病疫霉RXLR效应蛋白SFI5在抑制番茄MTI早期反应中分子机制的研究
  • 批准号:
    31701862
  • 批准年份:
    2017
  • 资助金额:
    25.0 万元
  • 项目类别:
    青年科学基金项目
黔北农村留守学龄儿童意外伤害特征及SFI干预模式研究
  • 批准号:
    81160350
  • 批准年份:
    2011
  • 资助金额:
    53.0 万元
  • 项目类别:
    地区科学基金项目
Sfi1p蛋白在面包酵母SPB复制及SPB相关细胞过程中的作用研究
  • 批准号:
    30771108
  • 批准年份:
    2007
  • 资助金额:
    27.0 万元
  • 项目类别:
    面上项目

相似海外基金

EPSRC-SFI: Developing a Quantum Bus for germanium hole-based spin qubits on silicon (GeQuantumBus)
EPSRC-SFI:为硅上基于锗空穴的自旋量子位开发量子总线 (GeQuantumBus)
  • 批准号:
    EP/X039889/1
  • 财政年份:
    2024
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC-SFI: Developing a Quantum Bus for germanium hole based spin qubits on silicon (Quantum Bus)
EPSRC-SFI:为硅上基于锗空穴的自旋量子位开发量子总线(量子总线)
  • 批准号:
    EP/X040380/1
  • 财政年份:
    2024
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC-SFI: Supercoiling-driven gene control in synthetic DNA circuits
EPSRC-SFI:合成 DNA 电路中超螺旋驱动的基因控制
  • 批准号:
    EP/V027395/2
  • 财政年份:
    2024
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC-SFI Aluminium-Rich Nitride Electronics (ARNE)
EPSRC-SFI 富铝氮化物电子器件 (ARNE)
  • 批准号:
    EP/X036901/1
  • 财政年份:
    2024
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC-SFI: Developing a Quantum Bus for germanium hole based spin qubits on silicon
EPSRC-SFI:为硅上基于锗空穴的自旋量子位开发量子总线
  • 批准号:
    EP/X039757/1
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC & SFI CDT in Sustainable Chemistry - Year 1
电力系统研究委员会
  • 批准号:
    2888667
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Studentship
EPSRC & SFI CDT in Sustainable Chemistry - Year 1
电力系统研究委员会
  • 批准号:
    2888844
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Studentship
EPSRC-SFI: "CFT and Gravity: Heavy States and Black Holes"
EPSRC-SFI:“CFT 和重力:重态和黑洞”
  • 批准号:
    EP/W019663/1
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC-SFI: Krylov subspace methods for non-symmetric PDE problems: a deeper understanding and faster convergence
EPSRC-SFI:非对称 PDE 问题的 Krylov 子空间方法:更深入的理解和更快的收敛
  • 批准号:
    EP/W035561/1
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Research Grant
EPSRC & SFI CDT in Sustainable Chemistry - Year 1
电力系统研究委员会
  • 批准号:
    2888671
  • 财政年份:
    2023
  • 资助金额:
    $ 56.27万
  • 项目类别:
    Studentship
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了