Preformulation Evaluation of Δ9-Tetrahydrocannabinol Prodrugs – a Tool for Establishing Physicochemical Characteristics of Compounds at an Early Stage
Bibliographic record
Abstract
Δ9-Tetrahydrocannabinol (THC, Fig. 1 ) is the primary active ingredient of the plant Cannabis sativa (marijuana) and is responsible for the majority of the pharmacological effects. While THC in marijuana is mainly known for its abuse potential, it also exhibits the therapeutic effects in the treatment of nausea and vomiting during cancer chemotherapy. The only dosage form currently approved by FDA is an oral, soft gelatin capsule (Marinol®). This dosage form is expensive, resulting in inconsistent pharmacological effects and pharmacokinetic profiles. Hence, prodrugs of THC are synthesized for the delivery by transbuccal route. The objective is to enhance the thermal stability and permeation properties of the hemisuccinate ester prodrug of Δ 9 -tetrahydrocannabinol (THC-HS) by complexation with random methylated beta cyclodextrin (RAMEB). An inclusion complex of THC-HS/RAMEB was prepared by freeze-drying THC-HS and cyclodextrin (1:2 and 1:10 ratios). Stability was evaluated at 4°C, 25°C and 40°C in open and closed vials over a period of 1 month. Diffusion of THC-HS from THC-HS/RAMEB complex, across porcine buccal mucosa, was studied at 37°C, using side-by-side diffusion cells. The degradation rate was higher in open vials as compared to closed vials. The permeability of THC-HS/RAMEB (1:2) freeze-dried complex was increased four-fold and that of the 1:10 complex increased two-fold compared to the permeability of the THC-HS alone. The inclusion complex of THC-HS/RAMEB significantly enhances the thermal stability and permeation properties of THC-HS. Effect of temperature on stability of THC-HS: RAMEB complex. Effect of RAMEB on permeability of THC-HS. Acknowledgements: Grant Number P20RR021929 – National Center For Research Resources (NIH/NCRR). References: [1] Munjal M, et al. (2006), AAPS Pharm SciTech, 7(3): E1–E12
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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 | 0.001 | 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) | 0.001 | 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".