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In the UK, 130,000 people live with MS, costing the NHS more than 拢2.9 billion a year. MS is an unpredictable disease and one out of three people living with MS require a change of treatment within two years because of insufficient treatment benefits.

Dr Eshaghi鈥檚 five-year research fellowship will develop AI technologies to characterise MS types using widely available NHS data. These AI tools will predict how symptoms may change, when MS may worsen, and which drugs are most likely to help.听

MS types are classified according to when and how symptoms appear. However, this does not reflect the underlying tissue changes, potential response to treatment or future disability. A better understanding of a patient鈥檚 MS type will enable doctors to recommend the most appropriate treatment with the fewest side effects.听

Dr Eshaghi previously developed an artificial intelligence (AI) tool to detect MS types based on brain images (MRI) from clinical trials. His NIHR-funded fellowship will look at larger, more diverse patient populations within the NHS to develop new tools that will benefit anyone diagnosed with MS.听

Working with colleagues from seven NHS Trusts and two international clinical centres, Dr Eshaghi will build AI tools that will enable measuring and predicting whether a treatment works at an individual level. He will also use AI to refine these predictions further so that they are even more personalised.听

The research will calculate how these digital tools may save costs in future healthcare by recommending appropriate treatments earlier and delaying disability.听

Dr Eshaghi said: 鈥淢y fellowship will use pioneering technology with privacy-preserving AI, that will enable constantly improving AI tools while obviating the need to share private patient information out of the hospital setting. It will maximise the use of life-saving data to benefit patients, while minimising risks to patient privacy. Such technologies will one day become decision aid tools for doctors and help patients to plan their future with certainty. This exciting work has become possible thanks to the mentors at the Queen Square Institute of Neurology and Department of Medical Physics and Computer Science, collaborators, and patient steering committee who contributed to design of the project."听

Professor Alan Thompson, Dean of the UCL Faculty of Brain Sciences, said: 鈥淭he use of AI has huge potential to improve our understanding of the underlying disease mechanisms that inform our clinical classification of MS and has been a focus of the MS group鈥檚 research involving Professor Olga Ciccarelli and, of course, Arman. It is fantastic that this research will use large and diverse NHS datasets to develop personalised treatments for people diagnosed with MS, which will make a real difference to our ability to minimise the impact of the disease.鈥澨�

Professor Olga Ciccarelli, NIHR Research Professor and Head of the Department of Neuroinflammation added: 鈥淚 am delighted to see that Arman has been awarded a prestigious fellowship to make a significant contribution to improving management of people with MS鈥�.听听

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Image:听MRI scans of a study participant who developed secondary progressive multiple sclerosis