Smart Continuous Nanoparticle Manufacturing.

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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