Oxford Biomedica has formed a research and development collaboration with Microsoft Research to enhance gene and cell therapy manufacturing using the intelligent cloud and machine learning.
Oxford Biomedica stated that cell and gene therapy have the potential to offer long-term and potentially curative treatment options for a range of diseases.
With this collaboration, Oxford Biomedica researchers will combine their expertise with Microsoft in large scale manufacture and vector development, along with exploring new ways to increase the yield and to improve Oxford Biomedica’s lentiviral vectors, while further reducing the cost.
The company will supply large data sets for analysis via Microsoft Azure intelligent cloud platform.
Microsoft will use its cloud computing and machine learning to develop in silico models and new algorithms to advance next generation of cell and gene delivery technology.
Initially, the collaboration will run for two years, with the possibility of extending it further by either party.
Oxford Biomedica chief business officer Jason Slingsby said: “Our LentiVector gene delivery platform is recognised as a leading solution by major industry players but developing next-generation manufacturing technologies is complex and often involves uncertain outcomes.
“The collaboration with Microsoft Research will harness our rich data resources to offer greater insights into the biological processes required to enhance quality and optimise yields of lentiviral vectors.”
The collaboration builds on Oxford Biomedica’s digital framework initiative, established in 2018. Work is underway in the company’s partnership with Synthace to rapidly design, simulate and execute complex experimental designs to develop next generation manufacturing processes, including with stable producer cell lines for lentiviral vectors.
Last November, Oxford Biomedica formed a digital framework initiative to streamline the production of medicines. The company stated that it will invest £4m, supported by a £2m grant from Innovate UK, for building digital and robotics capabilities to drive improvements in analytical methodology, supply times and cost of goods.
The goal is to increase capacity, reduce manufacturing cost and wastage.