Commercialising next-generation AI models for ultra-efficient analysis of neurological clinical trials

Prior to appearing on the pharmacy's shelf, drugs undergo careful research in clinical trials. These clinical trials assess biological changes in the human body to determine whether or not a given drug is effective. In neurological clinical trials, brain MRI scans are used to test whether a treatment has any effect on the brain or not. However, the way in which these brain MRIs are analysed is becoming increasingly complex in order to extract often subtle information of interest, increasingly falling out of the reach of human experts. Current computational tools are time-consuming to deal with thousands of scans that are typical of large-scale clinical trials and checking the quality of results requires substantial manual human intervention.

In the analysis of brain scans, where conventional tools lag behind in speed and, more recently, in precision, artificial intelligence (AI) excels; now more than ever AI is able to perform tasks inconceivable for automation a few years ago. Such tasks include identifying similar patterns of disease in dissimilar brain images and millisecond quantification of brain structures. This brings ultra-efficiency to image analysis and will expedite neurological clinical trials.

Here we propose to second Dr Raví from a world-leading academic group at the UCL Department of Computer Science to a UCL spin-out called Queen Square Analytics (QSA) to adapt openly available AI tools from previous academic research and develop new commercial tools to expedite MRI analysis in commercial clinical trials. To validate and refine these AI tools, he will collaborate with the UCL Institute of Neurology to apply AI tools on brain images from multiple sclerosis (MS) clinical trials. This secondment will provide Dr Ravì with resources to expand his skill set and his career in commercial research and application of AI. This will have global impact, as AI tools will ultimately be applied to phase 2 and phase 3 clinical trials in MS from international pharmaceutical companies.

The knowledge exchange between academic and industrial sectors through this secondment will expedite the translation of public investment at the UCL Department of Computer Science into real-world impact at QSA. QSA will be able to access talent and develop IP for its initial growth. By the end of this secondment, Dr Ravì will become a highly-skilled scientist at the intersection of academia and industry and his tools will be serviced to pharmaceutical companies, promoting the UK economy by creating jobs and attracting investments.