Is AI neurotechnology a game-changer in mental health research?

Understanding the effects of medicine on an individual is usually based on qualitative research in the form of patient questionnaires. While quantitative brainwave analysis is commonly used in neurology research, it is not commercially available and is often confined to labs and hospitals. 

Now, Artificial Intelligence (AI) and neurotechnology company Zentrela is bringing its brainwave technology to the European market in an effort to create the largest database of the psychoactive effects of cannabis.

While current drug tests can tell if a person has the psychoactive compound THC in their blood - they cannot objectively determine if a person is feeling the psychoactive effects. This new technology could now be a gamechanger for quickly and objectively determining if the medicine is having a cognitive impact.

The technology is now paving the way for research into the impacts of not only cannabis but other types of wellness and health products such as anxiety and depression medication, providing a cost-effective alternative to lengthy clinical trials. 

Understanding the effects of cannabis

Israel Gasperin, founder and CEO of Zentrela has been working with chief scientific officer Dr Dan Bosnyak, a neuroscientist at McMaster University, out of his lab in Canada for the past five years to combine machine learning and AI for brainwave analysis. 

Their brainchild, the Cognalyzer, is a portable non-invasive electroencephalogram (EEG) device that scans the brainwaves of an individual and uses AI to objectively quantify if a person is experiencing any psychoactive effects. In other words, the team has created a standardised measurement of how impaired a person is from their cannabis consumption.

Canada’s legalisation of cannabis in 2018 made the country a perfect testing ground for the technology.

“We knew that the existing drug test, which is based on fluid analysis, doesn't work to reliably determine cannabis impaired driving,” explained Gasperin. “So, we introduced this new concept to the Ontario government, specifically the Ontario Brain Institute and the Ontario Center of Innovation. 

“Thanks to their support, we raised $1 million in non diluted funds and were able to fully develop a commercially viable EEG test. Originally it was going to be used for safety and law enforcement, using the technology in police stations.

“Thanks to these funds, we were able to contract an independent Clinical Research Organization and train them to administer the EEG test. Through our AI, we were able to analyse it and determine if the data was collected before or after the consumption of cannabis with unprecedented accuracy.”

Zentrela has since published two peer reviewed papers that demonstrated the efficacy of the technology for objectively determining the strength of cannabis psychoactive effects.

The first tested the sensitivity, specificity and accuracy of the device, and the second assessed the relationship between the magnitude of the device’s predictions and the reported subjective drug effects of cannabis.

“We are now enabling so many new ways of conducting research that are more accessible and much faster than the traditional clinical trial model,” said Gasperin. “It's opening up possibilities to come up with new investigations.”

One such investigation, Gasperin explained, is conducting studies to determine the threshold that should be used to determine if a person should be driving or not - at what point they no longer feel the psychoactive effects.

“Based on that, the government or insurance companies can start making more accurate and informed decisions in terms of how to promote responsible consumption,” Gasperin commented.

Gasperin emphasised that, with the emergence of the cannabis market in the European Union, there is an urgent need to generate accurate and reliable information on the effects of cannabis to enable Europeans to make informed purchase and consumption decisions.

Innovating research and clinical trials

As well as providing health professionals with the opportunity to better prescribe cannabis products and the right dose for individual patients, the combination of EEG, AI and machine learning can create accurate and rapid results, which could dramatically impact research and clinical trials. 

Gasperin explains that the technology provides a new way of conducting human trials for research that can be completed in three months rather than 18 months.

The brainwave analysis technology is not confined to cannabis, but can be applied to any medicine that can impact the brain, helping to monitor brain biomarkers like stress and relaxation objectively. 

“We have found that we can use our technology to not only determine the intoxicating effects of cannabis, but also to determine its impact on emotional states and how it helps to alter or regulate them,” explained Gasperin.

“This is the type of research that we are already developing and in parallel to research hospitals, such as Quebec Research Hospital and CHUM.

“So, the next AI solutions that we are about to deploy by the end of this year are about quantifying all of these mental states, because our vision is to continue helping medical cannabis companies to prove how effective their products are at reducing anxiety and reducing depression.

“What we are doing today is partnering with research hospitals, universities and laboratories to help build these EEG data sets from their own research, and, what we are building is replicable to any other wellness, medical, psychedelic, psychoactive, or pharmaceutical solution that impacts the brain.

“Because of our lack of understanding of brain functionality, it has so far been difficult to quantify mental states. It is our long term vision, once we have developed this full library of AI solutions, to quantify whether someone is “high” or not, “drunk” or not, experiencing a psychedelic effect or not, and then to quantify emotions. 

“Are you sad, or are you angry? Are you experiencing fear, or are you happy and relaxed or sleepy? This will transform the definition of anxiety, depression and PTSD, for example. I think that clinical trials will lead to those conclusions down the road, and in the future, it could even possibly go towards diagnosis.”