A Preliminary Pharmacokinetic Comparison of Δ-9 Tetrahydrocannabinol and Cannabidiol Extract Versus Oromucosal Spray in Healthy Men and Women
Bibliographic record
Abstract
Aim: Few studies have directly compared the bioavailability of different cannabinoid formulations. Our goal was to assess the pharmacokinetic parameters and relative bioavailability of two Δ9-tetrahydrocannabinol:cannabidiol (THC:CBD) formulations: orally administered THC:CBD extract and oromucosally administered nabiximols. Methods: This pilot crossover study counterbalanced (1) 1 mL of orally administered THC:CBD extract (10 mg/mL each of THC and CBD in grapeseed oil) and (2) oromucosally administered nabiximols (four sprays of 2.7 mg THC and 2.5 mg CBD per spray, for a total dose of 10.8 mg THC and 10 mg CBD). Blood samples were obtained pre-dose and at 16 post-dose timepoints over 24 h. Pharmacokinetic parameters were calculated for THC, 11-hydroxy-tetrahydrocannabinol (11-OH-THC), and CBD. Results: Twelve occasional cannabis users (6 male, 6 female) were tested under fasting conditions. C max for THC and CBD was significantly higher with significantly shorter half-lives for THC:CBD extract versus nabiximols. C max for nabiximols was significantly higher in males compared with females. Under both treatment conditions, THC and CBD were undetectable by 24 h post-dose, and 11-OH-THC was markedly reduced from its peak. No serious adverse events were reported. Conclusions: Little is known about the comparative pharmacokinetics of commercially available cannabis products. This pilot study shows that the extract formulation achieved higher THC and CBD concentrations within a shorter time frame than nabiximols. These findings may have implications for clinical populations using these formulations therapeutically. Future studies should examine multiple doses in the context of therapeutic outcomes to characterize the relative clinical utility of these formulations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".