Cannabis effects on driving longitudinal control with and without alcohol

Hartman, Rebecca L.; Brown, Timothy L.; Milavetz, Gary; Spurgin, Andrew; Pierce, Russell S.; Gorelick, David A.; Gaffney, Gary R.; Huestis, Marilyn A.

doi:10.1002/jat.3295

Cited by 89 publications

(65 citation statements)

References 40 publications

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“…Complete population pharmacokinetic models of THC and its metabolites are important for better interpretation of sparse observational data commonly obtained from individuals in studies of cannabis users across a variety of areas of interest such as medical, recreational and forensic . For instance, a blood sample that only has measurable THCCOOH can yield estimates of daily THC consumption and exposure, assuming chronic use and approximate steady‐state conditions (C SS ), using the basic clinical pharmacokinetic principle of:

C_{SS} = dosing rate / elimination clearance

If the measured [THCCOOH] is 100 ng/mL, then from Table the THCCOOH ‘dosing rate’ equals approximately (100 ng/mL × 43.2 L/hr) 4320 μg/hr or 3834 μg/hr after correcting for the ratio of THC and THCCOOH molecular weights.…”

Section: Discussionmentioning

confidence: 99%

“…The blue circles represent the observed data for THC (a and b), 11-OH-THC (c and d) and THCCOOH (e and f) concentrations for the low and high doses for the first 12 h and THCCOOH (g and h) for the full 168 h of blood sampling. The black lines represent the 95 th , 50 th and 5 th percentiles of the simulated concentrations at each time point Complete population pharmacokinetic models of THC and its metabolites are important for better interpretation of sparse observational data commonly obtained from individuals in studies of cannabis users across a variety of areas of interest such as medical, recreational and forensic 22,26. For instance, a blood sample that only has measurable THCCOOH can yield estimates of daily THC con-THCCOOH] is 100 ng/mL, then fromTable 2the THCCOOH 'dosing rate' equals approximately (100 ng/mL × 43.2 L/hr) 4320 μg/hr or 3834 μg/hr after correcting for the ratio of THC and THCCOOH molecular weights.…”

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confidence: 99%

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Population pharmacokinetic modeling of plasma Δ9‐tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration

Sempio

Huestis

Mikulich‐Gilbertson

et al. 2020

Brit J Clinical Pharma

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Aims Population pharmacokinetic models of Δ9‐tetrahydrocannabinol (THC) have been developed for THC plasma and blood concentration data. Often, only the metabolites of THC are measurable when blood samples are obtained. Therefore, we performed a population pharmacokinetic analysis of THC, 11‐OH‐THC and THCCOOH plasma concentration data from a Phase I clinical trial of THC smoking. Methods Frequently obtained plasma THC, 11‐OH‐THC and THCCOOH concentration data were obtained over 168 h from 6 subjects who smoked low (15.8 mg) and high dose (33.8 mg) THC cigarettes on 2 occasions. Bayesian estimates of the THC pharmacokinetic model from each individual for each dose were fixed prior to the sequential pharmacokinetic analysis of the metabolites. Results A 3‐compartment model of THC was developed that has a steady‐state volume of distribution (VdSS) of 3401 ± 788 L and a clearance of 0.72 ± 0.10 L/min. 11‐OH‐THC was characterized by 50 ± 6% of the THC being directly cleared to a 3‐compartment model with a VdSS of 415.2 ± 4.3 L and clearance of 0.78 ± 0.05 L/min. The THCCOOH model shared the central compartment of the 11‐OH‐THC model with a VdSS of 29.1 ± 0.05 L and a clearance of 0.12 ± 0.02 L/min. First order kinetics were observed for THC and THCCOOH between the low and high doses, but a nonlinear pattern was observed for 11‐OH‐THC. Conclusion We describe the pharmacokinetics of THC, 11‐OH‐THC and THCCOOH including inter‐ and intraindividual variability of the parameter estimates of the model.

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C_{SS} = dosing rate / elimination clearance

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Population pharmacokinetic modeling of plasma Δ9‐tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration

Sempio

Huestis

Mikulich‐Gilbertson

et al. 2020

Brit J Clinical Pharma

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“…4,5 In addition, it has been associated with impairment in other complex tasks requiring neurocognitive and neuromotor skills 6,7 that are likely to be involved in driving safely. Marijuana exposure has also been associated with reduced speed and greater headway, 4,8 which indicates some degree of awareness of marijuana-related impairment and a tendency to compensate. 8 …”

mentioning

confidence: 99%

“…Marijuana exposure has also been associated with reduced speed and greater headway, 4,8 which indicates some degree of awareness of marijuana-related impairment and a tendency to compensate. 8 …”

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confidence: 99%

US Traffic Fatalities, 1985–2014, and Their Relationship to Medical Marijuana Laws

et al. 2017

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Objectives To determine the association of medical marijuana laws (MMLs) with traffic fatality rates. Methods Using data from the 1985–2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. Results On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associated with traffic fatality reductions in those aged 25 to 44 years. Conclusions Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of the MML–traffic fatalities association, suggesting moderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented.

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“…The most common methods for determining cannabis usage detect Δ 9 -THC. [6, 7, 12–21] Devices that detect Δ 9 -THC in the breath are currently being developed and have many advantages. Breath sampling is attractive because it is non-invasive, can be portable, and has been shown to indicate recent use within 0.5 hours to 2 hours.…”

Section: Introductionmentioning

confidence: 99%

Determination of cannabinoid vapor pressures to aid in vapor phase detection of intoxication

Lovestead

Bruno

2017

Forensic Chemistry

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The quest for a reliable means to detect cannabis intoxication with a breathalyzer is ongoing. To design such a device, it is important to understand the fundamental thermodynamics of the compounds of interest. The vapor pressures of two important cannabinoids, cannabidiol (CBD) and Δ9-tetrahydrocannabinol (Δ9-THC), are presented, as well as the predicted normal boiling temperature (NBT) and the predicted critical constants (these predictions are dependent on the vapor pressure data). The critical constants are typically necessary to develop an equation of state (EOS). EOS-based models can provide estimations of thermophysical properties for compounds to aid in designing processes and devices. An ultra-sensitive, quantitative, trace dynamic headspace analysis sampling called porous layered open tubular-cryoadsorption (PLOT-cryo) was used to measure vapor pressures of these compounds. PLOT-cryo affords short experiment durations compared to more traditional techniques for vapor pressure determination (minutes versus days). Additionally, PLOT-cryo has the inherent ability to stabilize labile solutes because collection is done at reduced temperature. The measured vapor pressures are approximately 2 orders of magnitude lower than those measured for n-eicosane, which has a similar molecular mass. Thus, the difference in polarity of these molecules must be impacting the vapor pressure dramatically. The vapor pressure measurements are presented in the form of Clausius-Clapeyron (or van’t Hoff) equation plots. The predicted vapor pressures that would be expected at near ambient conditions (25 °C) are also presented.

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Cannabis effects on driving longitudinal control with and without alcohol

Cited by 89 publications

References 40 publications

Population pharmacokinetic modeling of plasma Δ9‐tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration

Population pharmacokinetic modeling of plasma Δ9‐tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration

US Traffic Fatalities, 1985–2014, and Their Relationship to Medical Marijuana Laws

Determination of cannabinoid vapor pressures to aid in vapor phase detection of intoxication

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