AINOSTICS granted FDA Breakthrough Device Designation

"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

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

We would like to thank and congratulate our team at AINOSTICS and our collaborators who have assisted us in achieving this significant milestone."