Description of original award (Fiscal Year 2022, $1,450,809)
Cannabis induces executive function deficits that make drivers more likely to be involved in crashes than unimpaired drivers, yet, to date, there is no means to chemically detect impairment at the roadside. Currently, it is impossible to draw a correlation between driving impairment and delta-9-terahydrocannabinol (Δ9THC) concentration in blood, which is the most reliable matrix with which to determine recent cannabis use. Non-invasive, breath-based detection of recent cannabis use has been proposed as an alternative based on the observation that Δ9THC spikes, then decreases following cannabis consumption. However, users may retain Δ9THC in their breath despite abstinence; therefore, a maximum Δ9THC concentration in breath must be established, which, again, is not possible. To resolve the challenges of determining recent cannabis use from a single breath sample, we propose a paradigm shift: two breath samples spaced a short interval apart. Recent cannabis use would be distinguished from abstinence by a slope consistent with acute cannabis elimination. Preliminary work by another team provides support for this approach: Lynch et al. reported Δ9THC in breath samples collected at 15-minute intervals over three hours. Our analysis of their data shows promising consistency for both occasional and frequent users in the rate that Δ9THC decreases in breath samples over a three hour period. We will investigate the feasibility of a two-point measurement that could be implemented at the roadside. We propose to collect breath samples from occasional and frequent cannabis users at 10-minute intervals during acute cannabis elimination, similar to the previous work, and during periods of abstinence, which has not been examined. The proposed paradigm shift depends on consistency in the collection of breath samples, therefore numerical modeling will characterize the influence of human (e.g. flowrate and volume) and device factors to improve the reproducibility of aerosol particle collection. We will analyze breath samples for Δ9THC, its metabolites, and other cannabinoids with high sensitivity analytical methods. We will employ urine analysis to classify users into occasional and frequent use populations and blood analysis to verify compliance with study protocols. Comprehensive statistical analyses will compare elimination profiles and abstinence profiles with different intervals (e.g., 10 minutes vs. 20 minutes) and will examine the multivariate response. The positive impact of this research on public safety will be a practical path towards a method that could be implemented at the roadside to chemically determine recent cannabis use.
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