A semi-mechanistic pharmacometrics model to quantitatively characterize delta-9-tetrahydrocannabinol (THC) and its metabolites’ disposition among oral cannabis users
Authors: Li Peizhi , An Guohua 
Published: February 2025

Objectives: Over the past decades, cannabis consumption has surged, raising concerns about driving under the influence (DUI) [1,2]. Presently, there is no standardized cannabis DUI law in the US; some states employ "zero tolerance" while others set per se limits (e.g., 5 ng/ml blood THC concentrations) derived from occasional cannabis smokers [3]. Yet, due to three THC PK/PD issues: route-dependent PK, prolonged detection in frequent users, and the complex relationship between THC PK and PD, we hypothesize that current per se cutoffs may not adequately distinguish impaired cannabis DUI offenders from non-impaired individuals. To enhance cannabis DUI laws, the first step is to address those issues through a population PK/PD model. Current published models mainly focus on THC inhalation from occasional users; often with insufficient time range (e.g., up to 5.3 hr [4]), potentially inadequately reflecting real-world scenarios. Thus, a robust pop-PK model exploring oral THC with an extended sampling time is needed to bridge the gap. Methods : All oral and IV data for the model development were digitized from eleven published clinical studies on THC and its metabolites' concentration-time profiles. The pop-PK model was implemented using NONMEM (Version 7.4.3) interfaced with Pirana. Model selection criteria included physiological plausibility, goodness-of-fit plots, stability of parameter estimates, and objective function value. Results: Among the models tested, the final semi-mechanistic model simultaneously and quantitatively characterizes THC and its major metabolites’ disposition. It comprises three components: 1) a THC 3-compartment model with a first-order metabolic rate constant (Kgut) to address the first-pass metabolism and an adipose compartment with a partition coefficient (Kp) to describe the THC-fat cell partitioning process; 2) an 11-OH-THC 3-compartment model featuring an adipose compartment with Kp; 3) a THC-COOH 2-compartment model. This model not only demonstrates good fitting and estimates but also characterizes THC and its metabolites PK up to 24 hours. For instance, the estimated THC volume of distribution is 277 L, consistent with THC's lipophilic nature, underscoring the model's physiological plausibility. The model is validated by the simulation with the dose regimen from two clinical studies [5,6]. The simulated PK curves closely align with observed concentrations from these studies, validating the feasibility and practicality of the current model. Conclusions: This semi-mechanistic model serves as a foundation for further refinements. Comprehensive Monte Carlo simulations will be conducted to determine appropriate per se limits for THC and its metabolites in frequent and occasional oral users. Finally, with the current model as a first step, we aim to build a robust pop PK/PD model to establish appropriate per se limits for cannabis users across various doses, routes, and frequencies.Citations: [1] Cox, Emily J et al. “A marijuana-drug interaction primer: Precipitants, pharmacology, and pharmacokinetics.” Pharmacology & therapeutics vol. 201 (2019): 25-38. doi:10.1016/j.pharmthera.2019.05.001[2] Logan, Barry K. “Marijuana and Driving Impairment.” Marijuana and the Cannabinoids, edited by Mahmoud A. ElSohly, Humana Press, 2007, pp. 277–93. DOI.org (Crossref), https://doi.org/10.1007/978-1-59259-947-9_12.[3] Compton, R. "Marijuana-Impaired Driving: A Report to Congress." NHTSA, (2017), www.nhtsa.gov/sites/nhtsa.gov/files/documents/812440-marijuana-impaired-driving-report-to-congress.pdf.[4] Liyanage, Marlon et al. “Variable Delta-9-Tetrahydrocannabinol Pharmacokinetics and Pharmacodynamics After Cannabis Smoking in Regular Users.” Therapeutic drug monitoring vol. 45,5 (2023): 689-696. doi:10.1097/FTD.0000000000001104[5] Goodwin, Robert S et al. “Delta(9)-tetrahydrocannabinol, 11-hydroxy-delta(9)-tetrahydrocannabinol and 11-nor-9-carboxy-delta(9)-tetrahydrocannabinol in human plasma after controlled oral administration of cannabinoids.” Therapeutic drug monitoring vol. 28,4 (2006): 545-51. doi:10.1097/00007691-200608000-00010[6] Schwilke, Eugene W et al. “Delta9-tetrahydrocannabinol (THC), 11-hydroxy-THC, and 11-nor-9-carboxy-THC plasma pharmacokinetics during and after continuous high-dose oral THC.” Clinical chemistry vol. 55,12 (2009): 2180-9. doi:10.1373/clinchem.2008.122119