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Details of Grant 

EPSRC Reference: EP/Y017544/1
Title: A Novel Artificial Intelligence Powered Neuroimaging Biomarker for Chronic Pain.
Principal Investigator: Selvarajah, Dr D
Other Investigators:
Colvin, Professor LA Wild, Professor J Lu, Professor H
Tesfaye, Professor S Steele, Professor D Bennett, Professor D
Segerdahl, Dr A Zhou, Dr S
Researcher Co-Investigators:
Project Partners:
Department: Oncology and Metabolism
Organisation: University of Sheffield
Scheme: Standard Research - NR1
Starts: 02 October 2023 Ends: 01 April 2025 Value (£): 445,541
EPSRC Research Topic Classifications:
Artificial Intelligence Medical Imaging
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
11 Jul 2023 Artificial intelligence innovation to accelerate health research Expert Panel Announced
08 Jun 2023 Artificial intelligence innovation to accelerate health research Sift Panel A Announced
Summary on Grant Application Form
SCALE OF THE PROBLEM: Chronic pain is a major unmet global health challenge. One in ten adults over the age of 30 suffers from chronic nerve pain (neuropathic pain, NeuP) that arises from injury to sensory nervous system. Worryingly, this is expected to increase due to aging, rising cases of diabetes and improved cancer survival. NeuP can have a negative impact on patients, their families and wider society. Patients typically report constant burning, aching or 'electric-shock' type pains in their feet, legs and hands. As the pain is felt every day, patients may have difficulty doing simple daily activities such as walking to the shop or socialising with friends. This results in a poor quality of life and depression, with one in six of people rating their quality of life as 'worse than death'. Unfortunately, current medications provide only partial benefit in around half of all patients, with many enduring inadequate pain relief and unwanted side effects. Over the past 25 years, there has been a lack of new drugs that are more effective than the ones currently in use for treating NeuP. One possible reason is that there are many different sub-types of NeuP even when caused by the same condition e.g. diabetes. Treatment response is very individual , with no good way to predict who will benefit. This often results in negative outcomes in drug trials especially when conducted on a diverse group of patients. Working with patients and industry partner AstraZeneca, our goal is to develop new biomarkers for NeuP to improve the success of future drug development programmes.

PATIENT INVOLVEMENT: Our patients with diabetes and NeuP provided input to develop a study question that 'matters most to patients'. We discussed the studies that have been conducted, how this proposal takes the next step towards validating a biomarker which would translate to improvements in clinical care.

SOLUTION: In a 'proof-of-concept' study funded by NIHR Efficacy Mechanisms Evaluation (129921), we used artificial intelligence (AI) to develop a biomarker using brain magnetic resonance imaging that accurately predicts treatment response. However, these studies have been performed in a single centre and exclusively in patients with NeuP caused by diabetes. We now want to conduct a large, multicentre study to confirm the effectiveness of our model and ensure the findings are generalisable.

APPROACH: Test our model on one of the largest NeuP neuroimaging datasets in the country comprising people with NeuP from multiple causes (diabetes and post-chemotherapy) and from different centres (Oxford and Dundee). To achieve this, we will collaborate with the PAINSTORM Advance Pain Discovery Platform [https://tinyurl.com/yeuwt8y8] - a world leading, inter-disciplinary group of clinicians (Profs Bennett, Tesfaye, Colvin and Steele) and scientists (Profs Wild, Lu, Dr Sergedahl), the pharmaceutical industry (AstraZeneca) and people living with NeuP whose focus is to study a large group of people with NeuP using several innovative technologies including brain imaging. This established partnership with AstraZeneca will bring in the ideas and needs of industry to ensure our biomarker is 'fit-for-purpose' not only for the industry but also for clinicians and patients.

EXPECTED OUTCOMES AND LEGACY: At the conclusion of this proposal we will have an effective, objective biomarker for NeuP that can be widely used. We will have established an open access online platform to maximize future collaborations. AstraZeneca are conducting a study in NeuP caused by diabetes and will be well positioned to perform 'real-world' feasibility testing of the biomarker. If successful, the biomarker will be incorporated in future clinical trials of NeuP medications.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.shef.ac.uk