Our vision for this Transition Award is to leverage and combine key emerging technologies in Artificial Intelligence (AI) and Engineering Biology (EB) to enable and pioneer a new era of world-leading advances that will directly contribute to the objectives of the National Engineering Biology Programme. Realisation of the benefits of Engineering Biology technologies is predicated on our ability to increase our capability for predictive design and optimisation of engineered biosystems across different biological scales. Such a scaled approach to Engineering Biology would serve to significantly accelerate translation of scientific research and innovation into applications of wide commercial and societal impact. Synthetic Biology has developed rapidly over the past decade. We now have the core tools and capabilities required to modify and engineer living systems. However, our ability to predictably design new biological systems is still limited, due to the complexity, noise, and context dependence inherent to biology. To achieve the full capability of Engineering Biology, we require a change in capacity and scope. This requires lab automation to deliver high-throughput workflows. With this comes the challenge of managing and utilising the data-rich environment of biology that has emerged from recent advances in data collection capabilities, which include high-throughput genomics, transcriptomics, and metabolomics. However, such approaches produce datasets that are too large for direct human interpretation. There is thus a need to develop deep statistical learning and inference methods to uncover patterns and correlations within these data. On the other hand, steady improvements in computing power, combined with recent advances in data and computer sciences have fuelled a new era of Artificial Intelligence (AI)-driven methods and discoveries that are progressively permeating almost all sectors and industries. However, the type of data we can gather from biological systems does not match the requirements for off-the-shelf ML/AI methods and tools that are currently available. This calls for the development of new bespoke AI/ML methods adapted to the specific features of biological measurement data. AI approaches have the potential to both learn from complex data and, when coupled to appropriate systems design and engineering methods, to provide the predictive power required for reliable engineering of biological systems with desired functions. As the field develops, there is thus an opportunity to strategically focus on data-centric approaches and AI-enabled methods that are appropriate to the challenges and themes of the National Engineering Biology Programme. Closing the Design-Build-Test-Learn loop using AI to direct the "learn" and "design" phases will provide a radical intervention that fundamentally changes the way that we design, optimise and build biological systems. Through this AI-4-EB Transition Award we will build a network of inter-connected and inter-disciplinary researchers to both develop and apply next-generation AI technologies to biological problems. This will be achieved through a combination of leading-light inter-disciplinary pilot projects for application-driven research, meetings to build the scientific community, and sandpits supported by seed funding to generate novel ideas and new collaborations around AI approaches for real-world use. We will also develop an RRI strategy to address the complex issues arising at the confluence of these two critical and transformative technologies. Overall, AI-4-EB will provide the necessary step-change for the analysis of large and heterogeneous biological data sets, and for AI-based design and optimisation of biological systems with sufficient predictive power to accelerate Engineering Biology.

Industrial Biotechnology (IB) is entering a golden age of opportunity. Technological and scientific advances in biotechnology have revolutionised our ability to synthesise molecules of choice, giving access to novel chemistries that enable tuneable selectivity and the use of benign reaction conditions. These developments can now be coupled to advances in the industrialisation of biology to generate innovative manufacturing routes, supported by high throughput and real-time analytics, process automation, artificial intelligence and data-driven science. The current excess energy demands of manufacturing and its use of expensive and resource intensive materials can no longer be tolerated. Impacts on climate change (carbon emissions), societal health (toxic waste streams, pollution) and the environment (depletion of precious resources, waste accumulation) are well documented and unsustainable. What is clear is that a petrochemical-dependent economy cannot support the rate at which we consume goods and the demand we place on cheap and easily accessible materials. The emergent bioeconomy, which fosters resource efficiency and reduced reliance on fossil resources, promises to free society from many of the shortcomings of current manufacturing practices. By harnessing the power of biology through innovative IB, the FBRH will support the development of safer, cleaner and greener manufacturing supply chains. This is at the core of the UKs Clean Growth strategy. The EPSRC Future Biomanufacturing Research Hub (FBRH) will deliver biomanufacturing processes to support the rapid emergence of the bioeconomy and to place the UK at the forefront of global economic Clean Growth in key manufacturing sectors - pharmaceuticals; value-added chemicals; engineering materials. The FBRH will be a biomanufacturing accelerator, coordinating UK academic, HVM catapult, and industrial capabilities to enable the complete biomanufacturing innovation pipeline to deliver economic, robust and scalable bioprocesses to meet societal and commercial demand. The FBRH has developed a clear strategy to achieve this vision. This strategy addresses the need to change the economic reality of biomanufacturing by addressing the entire manufacturing lifecycle, by considering aspects such as scale-up, process intensification, continuous manufacturing, integrated and whole-process modelling. The FBRH will address the urgent need to quickly deliver new biocatalysts, robust industrial hosts and novel production technologies that will enable rapid transition from proof-of-concept to manufacturing at scale. The emphasis is on predictable deployment of sustainable and innovative biomanufacturing technologies through integrated technology development at all scales of production, harnessing UK-wide world-leading research expertise and frontier science and technology, including data-driven AI approaches, automation and new technologies emerging from the 'engineering of biology'. The FBRH will have its Hub at the Manchester Institute of Biotechnology at The University of Manchester, with Spokes at the Innovation and Knowledge Centre for Synthetic Biology (Imperial College London), Advanced Centre for Biochemical Engineering (University College London), the Bioprocess, Environmental and Chemical Technologies Group (Nottingham University), the UK Catalysis Hub (Harwell), the Industrial Biotechnology Innovation Centre (Glasgow) and the Centre for Process Innovation (Wilton). This collaborative approach of linking the UK's leading IB centres that hold complementary expertise together with industry will establish an internationally unique asset for UK manufacturing.