Pharmacokinetic and Safety Evaluation of Various Oral Doses of a Novel 1:20 THC:CBD Cannabis Herbal Extract in Dogs
Bibliographic record
Abstract
Objective: To determine the pharmacokinetics (PK) and safety of various oral doses of a Cannabis herbal extract (CHE) containing a 1:20 ratio of THC:CBD in 13 healthy Beagle-cross dogs. Methods: Single-dose PK was assessed after oral administration of CHE at low, medium, or high doses (2, 5, or 10 mg CBD and 0.1, 0.25, or 0.5 mg THC per kg bw, respectively; n=6 per group). Dogs were monitored for adverse events for up to 48 h post-dose. Evaluations of neurological signs, clinical laboratory abnormalities, and other adverse events were performed in two separate study phases; a multiple-dose phase with 12 dogs receiving 5 medium doses (5 mg CBD/kg bw) at 12 h intervals, and a single low-dose (2 mg CBD/kg bw), randomized, blinded, negative controlled study with 13 dogs. Results: Cannabinoids CBD, THC, CBC and metabolites 6-OH-CBD, 7-OH-CBD, 11-OH-THC, and THC-COOH were quantified in plasma. CBD and THC were rapidly absorbed (mean Tmax of 1.9 – 2.3 h) and initially depleted rapidly (mean CBD T1/2 β of 2.3 – 2.6 h). A prolonged elimination phase (mean CBD T1/2 λ of 13.3 – 24.4 h) was observed. CBD and THC concentrations increased in a dose-dependent (non-linear) manner, with disproportionally greater cannabinoid exposure relative to the dose increase. Neurological signs (hyperesthesia or proprioceptive deficits) were noted in 5 of 6 dogs in the high dose group, but only occasionally or rarely in the medium and low dose groups, respectively. Presence and severity of clinical signs correlated with plasma cannabinoid concentrations. Dogs appeared to develop a tolerance to cannabinoid effects after multiple CHE doses, with fewer neurological signs noted after the final (5th) versus first dose. No clinically meaningful changes in blood count or chemistry values occurred after multiple CHE doses. Clinical significance: Dogs tolerated the 1:20 THC:CBD formulation well at low and medium doses, but clinically meaningful neurological signs were observed at high doses. Due to nonproportional increases in plasma cannabinoid concentrations with increasing doses, as well as potential differences in CHE product composition and bioavailability, the possibility of adverse events and dose regimen consistency should be discussed with dog owners.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".