With the reduction of cannabis restrictions, the number of individuals driving or performing other safety-sensitive tasks after recent cannabis consumption is going inevitably to increase. Nowadays, various methods are used to identify cannabis-impaired drivers involving sobriety tests or considering the amount of the psychotropic cannabis component Δ9 -tetrahydrocannabinol (D9-THC) and its metabolites in blood or oral fluids. In some countries, a common approach is zero-tolerance, so that any amount of D9-THC and metabolites such as 11-OH-THC or 11-COOH-THC is not permitted. In other places the per se approach is applied, involving the possibility of driving at or below a certain predetermined concentration threshold, like a legal blood alcohol concentration (BAC) limit.
A recent review highlighted that the per se approach presents some limitations and that blood and saliva concentrations are relatively poor indicators of cannabis/THC-induced impairment. [1] The relationships between the measure of driving performance and THC-related biomarkers is more complex than the evident correlation of car crash risk and the limit set for BAC. Rather than only measuring THC levels in blood and oral fluid, the subjective perception of intoxication and driving impairment have been examined, correlating these with the objective measure of impairment through meta-regression analysis. A meta analysis assesses multiple studies in the scientific literature to gauge trends.
This method highlighted the importance of finding the optimal strategy to assess the capability of driving after recent cannabis use without considering only the per se limit. Even if linear relationships between blood THC, 11-OH-THC and 11-COOH-THC and saliva THC concentrations have been associated with impairment of driving-related cognitive skills in occasional cannabis users, the residual heterogeneity found in the results suggests a shortcoming in the prediction of impairment based only on THC-biomarkers. (Heterogeneity in a meta-analysis provides a measure of the differences in outcomes between the studies evaluated.)
Moreover, measuring THC concentrations in blood does not provide information on THC concentrations in the brain which would most likely correlate with actual impairment; the correlation between impairment and blood THC concentration demonstrated a ‘very weak’ relationship after both ingestion and inhalation of THC. Notably, the levels of the inactive metabolite 11-COOH-THC were found moderately higher, and provided the ‘strongest’ albeit still ‘moderate’ correlation, signalling possible differences in the pharmacokinetics of THC, 11-OH-THC and 11-COOH-THC.
For this reason, with the current per se limits used to identify impairment, some individuals could be considered as impaired drivers even if it is not the case and vice versa. Considering the differences within occasional and regular cannabis users, a more effective and validated regulatory method to assess cannabis impairment is needed. Regular users demonstrate a reduced sensitivity to the intoxicating effects of cannabis, but a prolonged presence of THC-related biomarkers, such as 11-COOH-THC, in biological matrices, beyond any timeframe of impairment.
The researchers call for more evaluation of medical cannabis patients, regular consumers who have been prescribed cannabis. This demographic is clearly not exempt from driving sobriety tests, and yet, they may have been prescribed cannabis to alleviate medical conditions such as pain that could otherwise be inhibitive to driving. They also suggest that cannabis consumers wait 3 to 10 hours depending on the dose and administration route before driving or performing other “safety-sensitive” tasks.
Reference:
[1] McCartney D, Arkell TR, Irwin C, Kevin RC, McGregor IS. Are blood and oral fluid Δ9-tetrahydrocannabinol (THC) and metabolite concentrations related to impairment? A meta-regression analysis. Neurosci Biobehav Rev. 2022;134:104433. [journal impact factor = 8.989; times cited = 1]
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