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Primary Outcome Measures:
Secondary Outcome Measures:

  • Driving Simulation Measuring Speed Deviation [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    Participants will be instructed to maintain their speed. The primary outcome is speed deviation in miles per hour.

  • Driving Simulation Measuring Divided attention [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    Participants will be instructed to respond to divided attention stimuli in two corners of the monitor. The primary outcome is percentage accuracy on the divided attention tasks.

  • Driving Simulation Measuring Car Following – Coherence [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    The outcome is coherence between the participant and lead cars (a general correlation [0-1] of the participant’s ability to accurately track the speed variations of the lead car).

  • Driving Simulation Measuring Car Following – reaction time to changes in the lead car’s speed. [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    The outcome is time delay in milliseconds (reaction time to changes in the lead car’s speed.

  • Driving Simulation Measuring Car Following – distance from the lead car. [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    The outcome is distance (number of meters) from the lead car.

  • Driving Simulation Measuring Multi-tasking (Surrogate Reference Task [SuRT])- accuracy [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    The outcome accuracy on the SuRT is measured in standard deviation of lateral deviation (SDLP) during this more challenging divided attention task.

  • Driving Simulation Measuring Multi-tasking (Surrogate Reference Task [SuRT])- response latency. [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    The outcome response latency on the SuRT is measured in milliseconds during this more challenging divided attention task.

  • Driving Simulation Measuring Crash avoidance/decision-making [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: Yes ]

    In order to assess treatment effects during routine and non-routine events the investigator will include scenarios addressing 1) the “yellow light dilemma”, wherein individuals need to respond to a yellow light onset by abruptly braking (risking a rear-end collision), or go through the intersection (risking running a red light). This will measured dichotomously; crash avoidance yes or no.

  • Performance-based tablet assessment: Critical Tracking [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    Participants will use a stylus on an iPad to overcome built-in error in horizontal deviation from a midpoint by increases as a function of time. The primary outcome is the average lambda-c across 5 trials.

  • Performance-based tablet assessment: Time estimation [ Time Frame: change from baseline of the five estimates of time estimation every 60 minutes for 7 hours ] [ Designated as safety issue: No ]

    Cannabis can affect time perception and estimation. Deficits in temporal processing could have significant implications for driving, for example in estimating the amount of time available to pass through a yellow light, or anticipating cross- traffic. The investigator will thus administer a brief measure of time estimation. Five trials, with randomly generated durations ranging from 5 to 30s (e.g., 7, 11, 29, 14, 23 seconds), will be generated. During each assessment, participants will complete the five trials. The primary outcome is the difference in time between actual 30 second intervals and guesstimates made by the participant.

  • Performance-based tablet assessment: Balance [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    Individuals may exhibit increased body sway when taking cannabis. To assess balance, participants will hold the iPad to their chest with their arms crossed, and their postural sway will be assessed while: 1) standing on both feet with eyes closed and 2) on a single foot and raising the other leg with the knee bent at 45 degrees, with eyes closed. Sway will be calculated using the iPad triaxial accelerometer.

  • Performance-based tablet assessment: Visual Spatial Learning Test [ Time Frame: participants will be followed for the duration of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 7 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    Cannabis can affect memory acutely. The investigator will assess short term memory using a visual-spatial learning test (VSLT). The test requires the subject to a) memorize 5 designs that are difficult to verbally encode, b) recognize them among a group of 10 distractors (5 foils) and c) recall the correct placement of these designs on a 4 X 4 matrix. Participants will complete one trial. The outcome is the number of figures correctly identified.

  • Identification of Recent Cannabis Intake Using Whole Blood [ Time Frame: change from baseline of the concentrations of cannabinoids every 60 minutes for 7 hours ] [ Designated as safety issue: No ]

    It has been hypothesized that several cannabinoids (e.g., THC-glucuronide, cannabidiol and cannabinol) might be useful for estimating the last time of cannabis intake. This follows from the finding that analytes of these cannabinoids, at observed Cmax, were not detected beyond 2 h after smoking, rendering them possible candidates for markers of recent cannabis smoking. The outcome will be the concentration of each cannabinoid expressed in nanograms per milliliter.

  • Assays for Oral Fluid Cannabidiol [ Time Frame: participants will be followed for the first 5 hours of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 4 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    The investigator will employ the Quantisal M collection device (Alere Inc., 9975 Summers Ridge Rd, San Diego, CA 92121) to collect and store saliva samples. Using ultra-performance liquid chromatography (UPLC) and tandem mass spectrometry (MS/MS), the levels of cannabidiol in the oral fluid samples will be determined in nanograms per milliliter.

  • Assays for Oral Fluid Cannabinol [ Time Frame: participants will be followed for the first 5 hours of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 4 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    The investigator will employ the Quantisal M collection device (Alere Inc., 9975 Summers Ridge Rd, San Diego, CA 92121) to collect and store saliva samples. Using ultra-performance liquid chromatography (UPLC) and tandem mass spectrometry (MS/MS), the levels of cannabinol in the oral fluid samples will be determined in nanograms per milliliter.

  • Assays for Oral Fluid THC-glucuronide [ Time Frame: participants will be followed for the first 5 hours of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 4 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    The investigator will employ the Quantisal M collection device (Alere Inc., 9975 Summers Ridge Rd, San Diego, CA 92121) to collect and store saliva samples. Using ultra-performance liquid chromatography (UPLC) and tandem mass spectrometry (MS/MS), the levels of THC-glucuronide in the oral fluid samples will be determined in nanograms per milliliter.

  • Assays of THC in Breath Specimens [ Time Frame: participants will be followed for the first 4 hours of an 8 hour human laboratory experiment, and the outcome will be measured once before they receive study medication and then for 3 hours thereafter on an every 60 minute basis ] [ Designated as safety issue: No ]

    Exhaled breath has recently been identified as a matrix for the detection of drugs of abuse including THC. This technology is based on a collecting device, the SensAbues Drug Trap®, that has a filter which traps aerosols from breath. These aerosols mimic the blood in terms of the content of certain substances including THC which will be measured in picograms per ml.

There are several studies that suggest higher doses of whole-blood Δ9-THC concentration are associated with increased crash risk and crash culpability. However, attempts to define a cut-off point for blood Δ9-THC levels have proven to be challenging. Unlike alcohol, for which a level can be reasonably measured using a breathalyzer (and confirmed with a blood test), detection of a cut-off point for intoxication related to Δ9-THC concentration has eluded scientific verification. Recent evidence suggests blood Δ9-THC concentrations of 2-5 ng/mL are associated with substantial driving impairment, particularly in occasional smokers. Others have countered that this level leads to false positives, particularly in heavy cannabis users inasmuch as THC may be detectable in their blood specimens for 12-24 hours after inhalation. Given that 12 to 24 hours is well beyond the likely period of driving impairment, this would appear to be a justifiable objection to a per se cut-off point for a Δ9-THC concentration indicative of impairment. Maximal driving impairment is found 20 to 40 minutes after smoking, and the risk of driving impairment decreases significantly after 2.5 hours, at least in those who smoke 18 mg Δ9-THC or less, the dose often used experimentally to duplicate a single joint. Other studies, however, report residual MVA crash risk when cannabis is used within 4 hours prior to driving.

The roadside examination using the Standardized Field Sobriety Test (SFST) for proof of cannabis-related impairment has not been an ideal alternative to blood levels. Originally devised to evaluate impairment under the influence of alcohol, the SFST is comprised of three examinations administered in a standardized manner by law enforcement officers. The ‘Horizontal Gaze Nystagmus’ (HGN), the ‘One Leg Stand’ (OLS) and the ‘Walk and Turn’ test (WAT) require a person to follow instructions and perform motor activities. During the assessments, officers observe and record signs of impairment. In one study, Δ9-THC produced impairments on overall SFST performance in only 50 % of the participants. In a separate study involving acute administration of cannabis, only 30% of people failed the SFST. This discrepancy in rate of failure was thought to be in part due to the participant’s cannabis use history. The reported frequency of cannabis use varied from once a week to once every 2-6 months in the study where there was a failure on the SFST by 50% of the participants. The other study included more frequent users who smoked cannabis on at least four occasions per week. Previous studies demonstrated that heavy cannabis users develop tolerance to the impairing effects of Δ9-THC on neurocognitive measures. The same phenomena apparently holds for the SFST.

Based upon the above, another means is needed to help law enforcement officers discern driving under the influence of cannabis. One future possibility is the development of performance-based measures of cannabis-related impairments. This will include testing of critical tracking, time estimation, balance and visual spatial memory learning. The investigators have selected brief measures in order to be practicably administered repeatedly over a short time period, as well as tests that have the potential to translate to a tablet-based format, should there be benefit in possibly including these in future performance-based measures for use in the field by law enforcement officers (e.g., a cannabis-focused field sobriety test).