milorna - machine informed learning of rna medicines

The project led by the UK SME Micropore Technologies (Micropore), supported by Northumbria University, Strathclyde University and Teesside University, aims to develop and validate a new approach to speed process development using machine learning. The area of focus is the encapsulation of genomic material (RNA) in protective nanoparticles. The development of these products is complex with process equipment design, operating approach, formulation and active product all impacting on behaviour. The intention is to learn this complex relationship and use the model within a design of experiments method to carry out the next set of development tests. The iterative approach of model, specify experiments and obtain results will be faster than current design of experiments methods as 'intelligence' on the complex process behaviour is built into the machine learning model. If successful, this new approach will make a step-change improvement in the efficiency with which new genomic medicines progress from discovery to real application in disease prevention and treatment. The success of mRNA-based vaccines during the COVID-19 pandemic has resulted in a large increase in interest in other nucleic acid medicines that are delivered to cells via nanoparticle delivery systems. Similar technologies are being researched to enable breakthrough vaccines for other diseases, as well as targeted treatments for cancer, rare diseases and more. However, there remain barriers to successful development and manufacture of nano delivered intracellular drugs. The encapsulation of the nucleic acids within protective nanoparticles (NPs), such as lipid nanoparticles (LNPs), is perhaps the most critical stage in the manufacturing process. Micropore has pioneered and patented micromixing/encapsulation technology called Advanced Crossflow (AXF) that combines the size-control and uniformity advantages of microfluidic approaches with an ability to scale up to commercial volumes, simply by increasing instrument size and material flow. Micropore can offer a single, highly-efficient, but flexible, multi-product technology platform that can span multiple phases of the drug development and production pathway - from lab scale to commercial scale without the need to redevelop and re-optimise processes at different stages. The project will consider how the initial lab scale development can be speeded up by exploiting machine learning and thereafter the benefits of the scalability of the technology mean that subsequent redesign is not required for the larger scales.