By Dr. Rahul Kushwah, Interim CEO, Predictmedix
Drug testing technology has existed for years, using saliva, urine, blood and even hair samples to determine the presence of cannabis compounds in a person’s system, detecting THC-related biomarkers that in many cases indicate use even if the individual hasn’t consumed cannabis for several weeks.
New technologies are now addressing the need for previously unavailable non-invasive technology that can reliably detect real-time impairment from cannabis. With the increasing use of legal cannabis, companies and researchers are rapidly advancing these technologies that will enable healthcare systems, employers, and law enforcement to quickly determine whether a person is functionally impaired.
Current methodologies for inferring active cannabis impairment have typically involved rapid drug tests and field testing. Blood and oral THC biomarker tests are often used to identify cannabis impairment in workplaces and in the field. Alternatively, observations, simple physical tests, and questions given by trained personnel similar to those used for drunk drivers can also be used to make an informed assessment of whether someone is “high”.
However, both methodologies have serious potential flaws. Because of differing metabolizing rates and reactions to cannabis, THC-related biomarkers in a person’s body at a given time are a relatively poor indicator of cannabis-induced impairment. Research has also shown that field sobriety tests are unreliable indicators of marijuana intoxication, and can lead to inaccurate and potentially biased conclusions by those trained to detect impairment. Furthermore, drug tests are absurdly costly to an organization, requiring thousands of recurring testing kits and salaries for personnel to administer tests.
Today, researchers and technology companies are racing to fill the need for the accurate detection of cannabis impairment, without penalizing legal users.
Earlier this year, researchers at the Massachusetts General Hospital found a noninvasive brain imaging procedure to be an objective and reliable way to identify individuals whose performance has been impaired by THC. The technique uses imaging technology known as functional near-infrared spectroscopy (fNIRS) to measure brain activation patterns that correlate to impairment from THC intoxication.
While the method requires further study, researchers believe brain-based testing can be done in the field with small, portable, battery-powered units with the potential to make a meaningful contribution to safety on highways and in the workplace.
PredictMedix PMEDPMEDF has been deploying its Safe Entry Stations at global events for some time – using artificial intelligence (AI) and multispectral cameras to analyze physiological data patterns and predict a variety of health issues including infectious diseases such as COVID-19. Using the same proprietary AI technology, the Company recently conducted a study to detect alcohol and cannabis impairment as subjects passed through the station using a multiparametric approach to identify unique features from multispectral imaging and voice analysis.
The results demonstrated a 79-87% efficacy in the identification of cannabis impairment (depending on the amount of cannabis consumed by the subject). The Company is now using the results to further fine-tune the AI algorithms and is seeking classification of the technology as a class II medical device in the US.
With ongoing global legalization efforts for cannabis use and the proliferation of users, the race for a rapid cannabis impairment detection technology will continue to intensify. The lack of impairment specificity from traditional THC biomarker tests is further pushing the need for the introduction of reliable, noninvasive products using cutting-edge technology such as AI and multi-spectral imaging.
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