Smart Continuous Nanoparticle Manufacturing.

智能连续纳米颗粒制造。

• 批准号: 2597364
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2597364
• 关键词: Smart; Continuous; Nanoparticle; Manufacturing.

Aims: The project is envisioned to enable smart continuous nanoparticles manufacturing by developing a modular platform technology for nanoparticle production. Development of methods for real time characterisation of particle size, composition and morphology coupled with computerised reactor control the project will contribute towards algorithmic driven self-optimisation of nanoparticle formation and production. Key technology output includes real-time particle analysis methods, a robust nanoparticle process and control environment and an enabling technology for intensified data driven development. Methodology:The initial focus of the work will be identification of polymeric nanoparticles and compatible encapsulant targets relevant to biopharmaceutical industries by literature searching and collaboration with the industrial partners. The project will exploit the Cognitive Chemical Manufacturing EPSRC project control platform and further develop an automated control system integrating mixing and synthesis, separation and purification of nanoparticles equipped with online analytics for monitoring of particle characteristics. The platform's performance to deliver targeted nanoparticles and develop fundamental understanding of various nanoparticle types. Potential Impact of Project:This project aims to deliver an autonomous and rapid method for rapidly generating targeted nanoparticles. These materials have significant societal and economic impact (for example in the development of vaccines and targeted release medicines). Accelerated development of such materials will enable a faster route to patients and may therefore save lives whilst also providing economic returns. More generally the integration of machine learning within an industrial workflow provides experience to the whole project team (both industrial and academic) which may result in wider impact at AstraZeneca and the University of Leeds as Industry 4.0 practices are incorporated within normal working. Expected Deliverables:Month 4 - Literature review of polymeric nanoparticle generation routes Month 9 - Online measurements with SAXS, DLS, UV-Vis of chosen nanoparticle System Month 18 - Established platform integrating control, online analysis and feedback optimisation Month 30 - 2 Case study optimisations of polymeric nanoparticles using machine learning methods Month 36 - Benchmarking of autonomous method vs manual optimisation

目的：该项目旨在通过开发用于纳米颗粒生产的模块化平台技术来实现智能连续纳米颗粒制造。开发真实的时间表征颗粒尺寸、成分和形态的方法，并结合计算机化反应器控制，该项目将有助于算法驱动的纳米颗粒形成和生产的自我优化。关键技术产出包括实时颗粒分析方法、强大的纳米颗粒工艺和控制环境以及用于强化数据驱动开发的支持技术。方法：工作的最初重点将是通过文献检索和与工业合作伙伴的合作，识别与生物制药行业相关的聚合物纳米颗粒和相容的封装剂目标。该项目将利用认知化学制造EPSRC项目控制平台，并进一步开发一个自动化控制系统，该系统集成了混合和合成，分离和纯化纳米颗粒，并配备了在线分析，用于监测颗粒特性。该平台的性能，以提供有针对性的纳米粒子和发展各种纳米粒子类型的基本理解。项目的潜在影响：该项目旨在提供一种自主和快速的方法，用于快速生成靶向纳米颗粒。这些材料具有重大的社会和经济影响（例如在疫苗和靶向释放药物的开发中）。加速开发此类材料将使患者获得更快的治疗途径，因此可能挽救生命，同时也提供经济回报。更一般地说，在工业工作流程中集成机器学习为整个项目团队（包括工业和学术）提供了经验，这可能会对阿斯利康和利兹大学产生更广泛的影响，因为工业4.0实践已被纳入正常工作中。预期成果：第4个月-聚合物纳米颗粒生成路线的文献综述第9个月-所选纳米颗粒系统的SAXS、DLS、UV-Vis在线测量第18个月-集成控制、在线分析和反馈优化的已建立平台第30个月-使用机器学习方法优化聚合物纳米颗粒的案例研究第36个月-自主方法与手动优化的基准测试