(T-109) A Multi-route, Multi-formulation Population Pharmacokinetic Framework for THC and 11-OH-THC Reflecting Real-World Use

Babajide Shenkoya – University of Maryland School of Pharmacy, Baltimore, MD, USA; Michael Tagen – Verdient Science LLC, Denver, Colorado; Linda Klumpers – Verdient Science LLC, Denver, Colorado; University of Vermont, Burlington, Vermont, USA; Ryan Vandrey – Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Mathangi Gopalakrishnan – University of Maryland School of Pharmacy, Baltimore, MD, USA

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Objectives: Few studies have quantitatively characterized the pharmacokinetics (PK) of Δ9-tetrahydrocannabinol (THC) and its active metabolite, 11-hydroxy-THC (11-OH-THC). However, existing PK models are limited by small sample sizes, focusing on a single administration route, or modeling smoked and vaporized THC together under a single inhalational route. This study aims to develop and evaluate a comprehensive PK model for THC and 11-OH-THC by integrating data across multiple routes and formulations commonly encountered in real-world settings.

Methods: Data were pooled from 16 controlled cannabis studies involving administration of THC via intravenous infusion, oral ingestion (brownies, soft gels, tablets), or inhalation (smoking, vaping). A population PK model for THC and its active metabolite, 11-OH-THC, was developed using nonlinear mixed-effects modeling (Pumas v2.6.0). Multiple absorption models were evaluated to describe the complex absorption characteristics from different routes and formulations, and interindividual variability was estimated for key PK parameters. Covariates assessed include weight, age, and formulation. Once the THC model was established, a linked metabolite model for 11-OH-THC was developed, in which metabolite formation was driven by THC clearance. The final parent-metabolite model was verified using standard goodness of fit diagnostics and predictive checks.

Results: A total of 6,289 THC and 5,290 11-OH-THC blood and plasma concentrations were collected from 368 subjects who received doses of THC ranging from 1.25 to 50 mg. As ~70% of data were plasma observations, blood concentrations were converted to plasma equivalents using published whole-blood to plasma THC ratios. About 25% of subjects (n = 30) received oral THC with high-dose CBD (32–38 times the THC dose). THC absorption via smoking and vaping followed a first-order model, with vaping yielding faster peak levels (7.2 vs. 9.5 minutes); absolute bioavailability was 15% and 26%, respectively. Oral absorption was captured by a parallel zero-order and first-order model (Ka = 0.073 h⁻¹), with the latter process accounting for 39% of the dose. Absorption and bioavailability varied by oral formulation: tablets were absorbed within 1.5 hours, whereas brownies and soft gels took more than twice as long. Bioavailability was 8% for brownies and 6% for tablets, while MCT oil-based soft gels showed higher values (~30%). The systemic clearance of THC was ~60 L/h, while 11-OH-THC was cleared more slowly at 21 L/h. Consistent with prior knowledge of CBD inhibition of THC metabolism, high CBD reduced THC and metabolite clearance by 56% and 89%, respectively, consistent with known CBD inhibition of THC metabolism. The fraction of oral THC converted to 11-OH-THC was 48%, with up to 16-fold lower conversion for inhaled and intravenous routes. All model parameters were reliably estimated with %RSE < 30%.

Conclusion: This study leveraged an extensive dataset to develop a robust PK model of THC and 11-OH-THC that addresses key limitations of previous models. By distinguishing inhalation subtypes and capturing formulation-specific oral kinetics, the model provides a valuable framework for predicting cannabinoid exposure across real-world use scenarios.

Citations: N/A

Keywords: Population pharmacokinetics, Cannabis, Tetrahydrocannabinol