We are thrilled to be granted this designation by the FDA. It is a key milestone for our technology to contribute its potential to the early clinical diagnosis of a wide range of neuropathologies worldwide. In the future, the access to clinical data enabled by the AI centre will facilitate future regulatory milestones, such as CE and other FDA certifications.
Dr Hojjat Azadbakht, Chief Executive and Founder of AINOSTICS
01 September 2022
FDA granted Breakthrough Device Designation for AI-Powered technology that predicts Alzheimer's Disease years before symptoms appear
The product BR[AI]N™ has been shown to be able to predict conversion to Alzheimer’s disease in subjects classed as MCI with an accuracy of 92 percent and up to 7 years before clinical diagnosis was established in these subjects
Partner of the London Medical Imaging & AI Centre for Value Based Healthcare (Ai4VBH), AINOSTICS, has been awarded Breakthrough Device Designation by the US Food and Drug Administration (FDA) to its product, BR[AI]N™, developed by funding received as part of the collaboration with the AI Centre.
The product automates the analysis of medical images such as CT, MRI and PET scans, providing users with the capability to identify subtle, early signs of neurological conditions such as dementia which are often invisible to the naked eye.
BR[AI]N™ allows accurate and timely diagnosis for early intervention which leads to better treatment outcomes for patients and value-based healthcare.
Granting the Breakthrough status to its technology, the FDA recognises that AINOSTICS can provide more effective diagnoses and outcome prognosis in dementia, addressing a need for which currently no approved alternatives exist.
There are currently no methods in the NHS for predicting who will convert to dementia.
The number of people living with dementia worldwide is estimated at over 50 million, reaching 82 million in 2030 and is the UK’s leading cause of death, yet it is estimated that only 66 percent of sufferers have received a diagnosis.
Even in those who receive a diagnosis, due to the absence of an accurate early diagnostic test, the average time from symptom onset to diagnosis is 3 years.
This issue also affects the trials of novel dementia therapeutics, where current inclusion criteria/tests in trials for predementia-AD have low to moderate accuracies, leading to very high attrition rates.
As part of the clinical assessment of dementia, the National Institute for Health and Care Excellence (NICE) recommends the use of magnetic resonance imaging (MRI) for better diagnosis.
Currently, these scans are visually inspected by clinicians, a process which is subjective, time-consuming and not reproducible.
Consequently, it is not possible to know whether someone has dementia when they are first assessed. Doctors refer to this uncertain situation as ‘mild cognitive impairment’ (MCI).
Traditional models using demographics, cognitive scores and imaging have only achieved modest accuracies in the region of 60-70 percent, even with the incorporation of molecular biomarkers that are not routinely available in UK memory clinics.
But as part of initial pilots, the breakthrough status technology has shown to be able to predict conversion to Alzheimer’s disease in subjects classed as MCI with an accuracy of 92 percent and up to 7 years before clinical diagnosis was established in these subjects.
One of the great advantages of the solution is that this was achieved only using commonly acquired patient data in the current clinical pathway for dementia.
These were the patients’ age, gender and clinical T1 structural scans (which are probably the most common type of MRI scans performed in clinical practice) from 1.5 and 3 Tesla MRI scanners, which account for approximately 96 percent of MRI hardware in the NHS.
This makes the solution extendable and affordable for wide use dissemination in the NHS.
The collaboration between AINOSTICS and the AI Centre, is representative of how critical the model of bringing together academia and industry is to advance novel and transformative healthcare technologies such as BR[AI]NTM. The FDA Breakthrough Device Designation will now ensure quicker development, assessment and review of a product that will have an enormous impact on patient care.
Professor Reza Razavi, Director, London Medical Imaging and AI Centre for Value Based Healthcare
BR[AI]N fills an enormous clinical gap for a more thorough, comprehensive treatment pathway for dementia. As part of the collaboration with the AI Centre, AINOSTICS will be given access to clinical data from NHS trusts and hospital partners such as Barts Health and King’s College Hospital. This means AINOSTICS will be able to further develop and validate this critical technology that will impact millions.
Professor Sebastien Ourselin FREng, Deputy Director, London Medical Imaging and AI Centre for Value Based Healthcare
The AI centre also provides AINOSTICS with routes to NHS adoption, accelerating the process of getting the products into clinical practices and the benefits being seen by the patients.
AINOSTICS was founded by Dr Azadbakht when the bid for the AI centre was submitted to Innovate UK/UKRI.
It is one of the ten SME partners at the AI centre, leading the dementia exemplar project.