A new study will investigate how AI and machine learning could help speed up the development and production of mRNA-based vaccines and medicines.
Innovate UK has awarded more than £440,000 to the project which aims to fast-track the development process in genomic medicine – which analyses DNA to understand an individual's genetic makeup – to treat existing conditions, such as cancer or rare diseases, or to produce new vaccines.
The University of Strathclyde will play a critical role in the study focused on testing the protective lipid-based nanoparticles that are used to encapsulate ribonucleic acid (RNA) for delivery into cells.
Intricate processes
RNA is present in all living cells and is used by the body to construct cells or respond to immune challenges. Messenger RNA – or mRNA – carries the genetic instructions the body uses to create cells.
The consortium, which is being led by Redcar-based drug formulation and manufacturing company Micropore Technologies, includes researchers from the Universities of Northumbria and Teesside.
Professor Yvonne Perrie, Head of the Strathclyde Institute of Pharmacy and Biomedical Sciences, said: "This research has the potential to transform the development and manufacturing of genomic medicines.
“By applying machine learning to these intricate processes, we aim to make significant strides in how quickly and effectively treatments can be brought to patients. We’re delighted to contribute our expertise in nanoparticle testing to this collaboration."
Critical stage
Professor Wai Lok Woo of Northumbria University, Chair in Machine Learning, added: “The development of genomic medicines is complex, with the encapsulation of nucleic acids within protective nanoparticles being perhaps the most critical stage in the manufacturing process.
“However, process equipment design, operating approach, formulation and active product all impact on how these intracellular drugs behave, and current iterative approaches to understand these behaviours is highly time consuming. This creates a barrier to the timely and successful development and manufacture of nano-delivered intracellular drugs.
“Our intention is to use machine learning to identify and learn this complex series of relationships and build models which can accelerate formulation development.
This will make a step-change improvement to the speed and efficiency with which new genomic medicines can progress from discovery to real application in disease prevention and treatment.
Micropore Technologies, whose Advanced Crossflow technology is already making strides in drug development, will work with the universities to implement machine learning models that reduce development costs and increase efficiency.
Dave Palmer, Technical Manager at Micropore Technologies, said: “We are looking forward to working with our partners to exploit machine learning to speed up the initial lab scale development and production pathway to improve the manufacturing process and ultimately bring new genomic medicines into use much more quickly than had previously been possible.”
The project underscores Strathclyde’s role as a leader in health innovation, working with academic and industry partners to tackle some of the most pressing challenges in medicine.