Thomas K. Henthorn (1), George S. Wang (2), Greg Dooley (2), Ashley Brooks-Russell (1), Julia Wrobel (3), Sarah Limbacher (1), Michael Kosnett (1)
1) University of Colorado Anschutz Medical Campus, USA (2) Colorado State University, USA (3) Emory University, USA
Introduction: Estimating THC exposure is key to examining the public health implications of cannabis consumption.[1] Cannabis legalization has increased the diversity of delivery methods and potency of products available, which affects public health outcomes[2], yet characterizing THC exposure by gravimetric and use frequency methods is difficult[3]. Because of the diversity of cannabis delivery methods, observed user variability of inhalation efficiency and titrated effects[4, 5], a more accurate methodology for estimating THC dose is needed.
To better understand real world THC pharmacokinetics, studies should allow subjects to use their own cannabis product and consume it in their usual manner. We studied the PK of THC in occasional and daily users, smoking or vaping their preferred, commercially available cannabis product according to their usual pattern of consumption.
Distribution pharmacokinetics show little interindividual variability (IIV) as these processes are determined by physiologic factors, such as tissue mass and blood flow,[6] as well as physicochemical factors such as tissue:blood partitioning and protein binding.[7] Therefore, a population PK analysis with dense, precisely-timed blood THC concentrations should demonstrate that IIV of drug distribution parameters was small and that the estimated bioavailable inhaled dose had large IIV.
Objectives:
- Obtain dense, precisely-timed blood THC concentrations from occasional and daily cannabis smokers and vapers
- Estimate PK parameters characterizing drug early distribution and IIV
- Estimate inhaled dose and IIV
- Conduct covariate analysis to determine whether THC usage pattern (occasional versus daily) or method of consumption (smoking versus vaporization) explains dosage variability
Methods: THC concentrations were obtained for 135 minutes in 30 subjects stratified by: 10 occasional users (< 3 times per week) and 10 daily users all of whom normally smoked high concentration flower (15-30%) and 10 daily users who normally inhaled THC concentrates (60-90%). All subjects were instructed to smoke/inhale the product they supplied themselves, ad libitum, in the manner they usually employed, and to the endpoint they usually desired. Blood THC concentrations were measured using a validated LC-MS/MS method. Using Phoenix NMLE 8.4, parameters for a 3-compartment population pharmacokinetic model were estimated along with an estimate of the bioavailable inhaled dose which were compared to the physically measured dose used during the study session. Covariates were tested in a stepwise manner.
Results: Central and rapidly equilibrating volumes of distribution of a 3-compartment model were estimated (19.9±1.2 L, 51.6±4.7 L, respectively) as well as intercompartmental clearances to rapid and slow equilibrating peripheral compartments (1.65±0.14 L/min and 1.75±0.10 L/min, respectively). The slow volume of distribution and elimination clearance were fixed to estimates we determined previously from the population pharmacokinetic model (3372 L and 0.72 L/min, respectively)[8]. Peak blood THC concentrations varied by nearly 100-fold among the 30 subjects. There was a poor correlation between estimated bioavailable dose and the weighed, combusted THC amount (r2=0.07). Covariate analysis revealed that occasional cannabis users inhaled significantly less THC than daily users despite having used similar, physically weighed THC doses.
Conclusions: 3-compartment pharmacokinetics of THC did not differ among the subjects in this study using real world conditions and the early phase kinetics were similar to those previously described using low potency cannabis products.[5, 8] These analyses suggest covariate-driven adjustments can be made to weighed THC doses, based on usage pattern. In addition, PK-driven dose estimation improves the accuracy of THC exposure of inhaled cannabis products over the physical method of weighing the combusted product.
References: [1] Martin-Willett, R., et al., Brain Behav, 2020. 10(1): p. e01486.
[2] Cinnamon Bidwell, L., et al., Addict Behav Rep, 2018. 8: p. 102-106.
[3] Prince, M.A., et al., Psychol Addict Behav, 2018. 32(4): p. 426-433.
[4] Bidwell, L.C., et al., JAMA Psychiatry, 2020.
[5] Heuberger, J.A., et al., Clin Pharmacokinet, 2015. 54(2): p. 209-19.
[6] Krejcie, T.C., et al., J Pharmacol Exp Ther, 1994. 269(2): p. 609-16.
[7] Garzone, P.D. and A.J. Atkinson, Jr., Clin Pharmacol Ther, 2012. 92(4): p. 419-21.
[8] Sempio, C., et al., Br J Clin Pharmacol, 2020. 86(3): p. 611-619.
Reference: PAGE 32 (2024) Abstr 10789 [www.page-meeting.org/?abstract=10789]
Poster: Real-world data (RWD) in pharmacometrics