Magnitude Biosciences Raises €1.5 Mn to Scale AI-Powered Drug Discovery Platform

The funding will help the company bring VivoScan, its technology for quickly testing potential treatments and drugs in living organisms, to the wider market. The platform is designed to make high-throughput testing faster and more efficient.

The round was led by Northstar Ventures through several of its funds, including the North East Spinout Inspire Fund, North East Innovation Fund and Northstar EIS Growth Fund. Maven’s regional funds and new angel investors also participated. The funding also helped unlock an additional €253,000 (£217,000) Innovate UK grant.

Dr. Fozia Saleem, CEO of Magnitude Biosciences, says: “Our ambition is to become the first company to provide a platform to screen millions of compounds in a whole organism. This investment in VivoScan gives us the opportunity to turn that ambition into reality and fundamentally change the scale and speed at which drug discovery can be done.”

“We are building a platform that can move beyond simply screening more compounds.” continues Saleem. “VivoScan generates rich, whole organism biological data that can help researchers understand how potential therapies affect health, ageing and disease. By making data generation faster and more cost effective, we will be able to help pharmaceutical and biotechnology companies identify better drug candidates earlier and ultimately accelerate the development of new treatments.”

Founded in 2018 and based in Durham, UK, Magnitude Biosciences helps drug developers test and study potential treatments using living biological models.

Its VivoScan platform allows researchers to test large numbers of drug compounds in a whole living organism, instead of studying only individual cells or molecules.

VivoScan uses tiny C. elegans worms, which are commonly used in scientific research. The platform combines automated imaging, robotics and AI to quickly study how the worms respond to potential treatments.

The technology can help researchers find promising drug candidates faster and understand their effects at an earlier stage. It could be especially useful for research into ageing and neurodegenerative diseases, where predicting how a treatment will work in a living system can be challenging.

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