BioEP works by creating mathematical models of the brain using short segments of electroencephalogram (EEG) recordings. Computer simulations rapidly reveal the ease with which seizures can emerge and form the basis of the BioEP seizure risk score.
Neuronostics is developing BioEP in partnership with the University of Birmingham, where mathematician Professor John Terry, co-founder of the company, is Director of Centre for Systems Modelling & Quantitative Biomedicine.
Professor Terry's research aims to improve diagnosis and treatment for people with epilepsy. He explains: "We build personalised models of the brain using EEG that is routinely collected when seeking to diagnose epilepsy. From these models the risk of epilepsy can be quickly determined. In contrast, multiple EEG recordings are often required to reach a clinical diagnosis at present. This is expensive, time-consuming, and exposes people with suspected epilepsy to risk."
The funding, from the National Institute for Health Research (NIHR), will enable the research partnership to progress a prototype clinical platform that can provide a risk score showing the individual's susceptibility to seizures. This measurement can be used in diagnosis, and as an objective assessment of response to treatment with AEDs, resulting in faster seizure control for people with epilepsy.
The clinical utility of the BioEP seizure risk score has already been demonstrated in a cohort of people with idiopathic generalized epilepsy.(1) Using just 20 seconds of an EEG recording that would be considered inconclusive in the current clinical pathway, BioEP achieved 72% diagnostic accuracy. This matches the accuracy achieved in the current diagnostic pathway, which typically takes a year, and involves multiple follow-ups.(2)
The company is interested to hear from commercial partners in EEG hardware manufacturing, digital EEG analysis, and companion diagnostics or prognostics, and research and clinical partners with interests in epilepsy, traumatic brain injury and dementia.
The NIHR funding was delivered through the AI in Health and Care Award, part of the NHS AI Lab, which was launched by the UK Government earlier this year to accelerate the adoption of Artificial Intelligence in health and care.
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About NeuronosticsNeuronostics was established in 2018 and is focussed on developing clinical decision support tools and at home monitoring devices for people with suspected neurological conditions. Neuronostics is currently Medilink SW Start up of the Year and has been supported by grant funding in excess of £1M. Neuronostics’ first product - BioEP - is a revolutionary, patented, biomarker of the susceptibility to seizures in the human brain, informed by clinical EEG recordings.
About the University of BirminghamThe University of Birmingham is ranked amongst the world’s top 100 institutions. Its work brings people from across the world to Birmingham, including researchers, teachers and more than 6,500 international students from over 150 countries.
About NIHRThe National Institute for Health Research (NIHR) is the nation's largest funder of health and care research. The NIHR:
- Funds, supports and delivers high quality research that benefits the NHS, public health and social care
- Engages and involves patients, carers and the public in order to improve the reach, quality and impact of research
- Attracts, trains and supports the best researchers to tackle the complex health and care challenges of the future
- Invests in world-class infrastructure and a skilled delivery workforce to translate discoveries into improved treatments and services
- Partners with other public funders, charities and industry to maximise the value of research to patients and the economy
The NIHR was established in 2006 to improve the health and wealth of the nation through research, and is funded by the Department of Health and Social Care. In addition to its national role, the NIHR supports applied health research for the direct and primary benefit of people in low- and middle-income countries, using UK aid from the UK government.
1. H Schmidt et al. A computational biomarker of idiopathic generalized epilepsy from resting state EEG Epilepsia 57: e200-e204 (2016).
2. S Smith. EEG in the diagnosis, classification, and management of patients with epilepsy Journal of Neurology, Neurosurgery & Psychiatry 76: ii2-ii7 (2005).