Developing Digital Technology for Healthcare Relevant Algal Biorenewables Manufacturing

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Our aim is to apply state-of-the-art machine learning based digital technology recently developed in our research to facilitate large scale manufacturing of three photo-production processes for high-value biorenewables (i.e. Spirulina biomass, lutein, and arachidonic acid) production. Microalgal photo-production processes directly convert solar energy and CO2 into healthcare relevant commercial compounds, and are considered as a promising sustainable biotechnology for future industry. Sales of the three products investigated in this project have been estimated to be £1.13 billion by 2024. The global market demand of photo-production based chemicals has been expected to reach £35 billion by 2023, with an annual growth rate of 5.2%.Developing digital technologies to construct automated biomanufacturing systems for valuable biomaterials production is of great importance to the UK's economy. The UK's Bioeconomy is currently worth ~£220 billion and is predicted to double by 2030. This sector also supports over 5 million jobs. In order for the UK to retain its leadership in industrial biotechnology and digital economy, it is crucial to develop cost-effective and self-sustained photo-production processes to reduce dependency on petroleum chemicals and fossil fuels. This will cement the UK as a world-pioneer in 'smart' manufacturing and disruptive biotechnology, with benefits not only in generating high quality products and services, but also boosting the national economy through the manufacture of healthcare relevant chemicals and creation of new job opportunities.The two research groups at Xiamen University, China are national leading experts and have rich industrial experience in sustainable photo-production process design, scale-up, and optimisation. There are a range of experimental facilities and photobioreactors from lab scale to industrial scale available at their groups. We have established initial collaborations with the groups in China. To guarantee success, we will: (i) develop different modelling tools to quantify the three photo-production systems, and test their accuracy for process prediction and state estimation; (ii) integrate advanced online optimisation techniques into the models to form a digital framework for process monitoring and optimal control, and verifies the framework's performance through lab and pilot scale experiments; (3) update the digital framework and install it into the large scale manufacturing systems, meanwhile embed a deep learning technology into the digital framework to visualise process behaviour at different temporal and spatial space. Most of the digital technologies have been developed in the University of Manchester, and there are sufficient experimental resources and experimental facilities at Xiamen University. This international collaboration provides an excellent opportunity to link frontier digital technologies invented in the UK with advanced industrial biotechnologies developed in China, and will initiate the first thorough investigation in using novel digital technologies for photo-production process real-time monitoring and state estimation, online optimisation and control, and bioreactor visualisation. This project will boost collaborations between the University of Manchester and Xiamen University, and will significantly benefit the academics and PhD students involved in this project. Outcome will be used as evidence to: i) apply for future long-term collaborative grants such as the Newton Institutional Links Grants, the High-level Foreign Experts Plan, and the UKRI-China R&D fund; ii) co-supervise PhD and MSc students to extend their knowledge in fields of experimentation and simulation; iii) secure PhD studentships from overseas companies and the China Scholarship Council; iv) bring advanced industrial skills into UK SME biotech companies to facilitate the domestic development of photo-production processes and industrial biotechnologies.