Using Population Pharmacokinetic Modeling to Estimate Exposure to Δ9-tetrahydrocannabinol in an Observational Study of Cannabis Smokers in Colorado

2021 
BACKGROUND Self-report questionnaires, weighing products consumed, and Δ9-tetrahydrocannabinol (THC) biomarkers are established techniques for estimating cannabis exposure. Population pharmacokinetic modeling of plasma THC and metabolite concentrations by incorporating self-reported and weighed products as covariates could improve estimates of THC exposure in regular cannabis users. METHODS In this naturalistic study, blood samples were obtained from 36 regular smokers of cannabis for analysis of THC and its two metabolites at four time points: recruitment and during an experimental mobile laboratory assessment that included three time points: before, immediately after, and one hour after ad libitum legal market flower use. These data were analyzed using an established model of population pharmacokinetics developed from laboratory-controlled cannabis administration data. Elimination and metabolite production clearances were estimated for each subject as well as their daily THC doses and the dose consumed during the ad libitum event. RESULTS A statistically significant correlation existed between the daily THC dose estimated by self-report questionnaire and population pharmacokinetic modeling (correlation coefficient = 0.79, p<0.05) between the weighed cannabis smoked ad libitum and that estimated by population pharmacokinetic modeling (correlation coefficient = 0.71, p<0.05). CONCLUSION Inclusion of self-reported questionnaire data of THC consumption improved pharmacokinetic model-derived estimates based on measured THC and metabolite concentrations. Additionally, the pharmacokinetic-derived dose estimates for the ad libitum smoking event underestimated the THC consumption compared to the weighed amount smoked. Thus, the subjects in this study, who smoked ad libitum, and used cannabis products with high concentrations of THC were less efficient (lower bioavailability) compared to computer-paced smokers of low potency, NIDA cannabis in a laboratory setting.
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