AI-assisted multiple sclerosis breakthrough paves way for personalised treatment

In a world first, researchers at UCL spinout venture Queen Square Analytics (QSA) have used AI to reveal two distinct types of multiple sclerosis (MS), paving the way for more personalised care. 

The study, led by QSA in collaboration with UCL and Merck, has been peer-reviewed and published in neurology journal Brain. 

QSA used AI to analyse data from large datasets of blood tests and MRI scans to gain new insight on MS subtypes and stages, a groundbreaking approach which revealed new characteristics of the disease. 

The team focused on a blood protein called sNfL, an early warning sign of nerve damage, together with brain scans, making it easier for clinicians to spot changes in MS. Using AI, they identified two clear patterns: 

• Early-sNfL type: people show high sNfL levels and brain changes early on, meaning their MS is more active and aggressive. 

• Late-sNfL type: brain changes happen first, with sNfL levels rising later, suggesting a slower, more gradual form of MS. 

This news has also been reported in The Guardian.

UCLB’s role 

UCLB has supported QSA from business planning and commercialisation to sharing their breakthroughs with a wider audience. It helped establish the senior management team, advised on building QSA’s business plan and route to market, as well as supporting grant applications to assist with the creation of the company.   

Dr. Weng Sie Wong, Senior Business Manager, Physical Sciences & Engineering, and non-executive Board Director of QSA, said: “This exciting discovery brings us closer to truly personalised MS care, improving outcomes for people worldwide. UCLB has played a pivotal role in supporting QSA from its earliest days, helping the team turn world-class research into real-world impact.” 

Better understanding of MS

This breakthrough brings new hope, empowering doctors to identify patients who may benefit from early, targeted care, and paving the way for more personalised treatment journeys. There are estimated to be 3 million MS sufferers worldwide. 

Dr. Arman Eshaghi, Founder Queens Square Analytics, said: “In the future, AI algorithms may act as decision aids for doctors and people living with MS. For example, when a computer assigns a high likelihood that a patient has an early sNfL subtype MS, they may become a likely candidate for higher-efficacy treatments and be monitored more closely. In contrast, those with late sNfL subtype may be assigned to different types of treatments.” 

About UCLB 

UCLB is UCL’s expert commercialisation partner, bringing brilliant ideas to life, and to market. We work side by side with academics, clinicians and innovators to turn exceptional research into successful products, spinouts and technologies that create real value in the world. 

As a powerhouse of commercialisation at the heart of London’s innovation ecosystem, we bring specialist commercial, scientific and investment expertise to every stage of the journey, from early protection and development through to licensing, venture creation and growth, harnessing the strength and opportunity of UCL’s innovations to deliver outstanding investor returns, substantial impact, and a pipeline of high-quality ventures that shape our future.  

By unlocking the full value of UCL’s research, we ensure that what happens here drives change everywhere.