Web content editor Ian Bolland caught up with Cognetivity COO Dr Tom Sawyer following results from its research and development programme into its Integrated Cognitive Assessment (ICA) platform.
The results were published in the academic journal Scientific Reports. The paper describes results from key studies validating the effectiveness of the ICA’s unique approach of using a rapid visual categorisation task for detecting changes in cognitive performance and its potential for use in early detection of mental disorders.
Further results, presented at the AD/PD meeting in Lisbon in April showed a strong correlation between scores on Cognetivity’s ICA test and levels of neurofilament light (NfL) in the blood of Multiple Sclerosis (MS) patients. This is an especially notable development, as this allows the relationship between cognitive performance as measured by the ICA and a disease biomarker to be established. Dr Sawyer spoke about the correlation with NfL.
What do these results mean for Cognetivity as a company?
These results really help to establish a strong biological basis to our measurement of cognitive function. As neurofilament light (NfL) is a protein, the presence of which in body fluids is caused by axons in the brain’s white matter falling apart, it represents a powerful measure of neuronal damage. The measurement is literally bits of damaged brain cells that are detectable in blood, so these data help us to start to understand the relationship between cognitive scores as captured using our integrated cognitive assessment (ICA) platform and the progression of physical damage to the brain. Understanding the relationship between disease progression in terms of its biology / physiology and cognitive function helps to demonstrate Cognetivity’s ability to generate results that are meaningful in terms of actual degradation in the brain. This is of vital importance in our ability to improve the predictive capability of the platform through our use of advanced artificial intelligence. As NfL levels in blood have been linked with a number of conditions such as Alzheimer’s, MS and concussion, the ability of a non-invasive, fast and sensitive test to detect the early onset of these and other conditions involving damage to the brain would have considerable clinical benefit.
Does it allow them to further develop the technology or possibly go a different way with it?
As well as increase the confidence that the ICA can predict damage to brain cells, these results also open up the potential for the ICA to be used as an endpoint in clinical studies, to also relate, through AI, patterns in subjects’ responses to specific conditions and to the level of advancement of these in terms of actual damage. The area of clinical trials for therapeutics for diseases such as Alzheimer’s has a need for more sensitive, repeatable measures to detect the often subtle effects of the drug candidate on subjects’ disease progression, and there is growing awareness that currently used tests are not sufficiently sensitive or repeatable to capture these signals. It is important for cognitive tests that are to be used in this area to show a relationship with biomarkers such as NfL or other established biomarkers in order to gain acceptance for use in clinical trials of this type. Cognetivity plans to continue to develop our capability in this area, and hopefully help in the search for a drug that can finally treat Alzheimer’s disease, rather than just the symptoms.
Can the recent results surrounding MS mean that it can also be detected like signs of dementia?
It is our belief that we will be able to start to detect distinct signatures in a subject’s results of a number of conditions, which would be able to give a likelihood of any cognitive impairment being due to a specific reason, such as the subject suffering from MS. In the first instance, for any disease that causes cognitive decline, one would want to first identify that this was happening, then look to explain it by diagnosing the cause. The ability of a test such as ours to initially detect this impairment at a very early stage enables diagnosis to happen much more efficiently and earlier by the use of current pathways in healthcare systems, which will have a significant impact both on the efficiency of the system and on improved outcomes for patients. The use of data would then be able to help to point the specialist in the right direction by predicting the cause of the problem. Given Cognetivity’s high-quality data on MS patients, these can be used to develop the AI models that can become these aids to diagnosis, obviously to be developed within regulatory frameworks for clinical products.
Is the technology increasingly likely to be used in a preventative format?
By detecting the very earliest signs of disease we can then look to prevent the advance of the condition, through a number of techniques, from drugs through to behavioural and lifestyle changes. To use an example of Alzheimer’s disease – there are currently a number of drugs in advanced clinical trials which are aimed to stop the advance of the disease, but none that are capable of re-growing already damaged brains. If these drugs are approved, then what will be vital will be very early diagnosis, in order to stop the disease’s progress and prevent further damage. An area that Cognetivity is also working on is that of personal cognitive monitoring, to be able to track your own “brain health”. By taking ownership of this and adjusting your lifestyle and habits to keep your brain healthy, users are encouraged to maintain habits that reduce the risk of conditions that affect cognitive function, with a resulting reduction in the incidence of these through preventative activities