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Record W4361004400 · doi:10.26434/chemrxiv-2023-zdt5s

Rational design, synthesis, and characterization of a solid Δ9-tetrahydrocannabinol (THC) nanoformulation suitable for “microdosing” applications

2023· preprint· en· W4361004400 on OpenAlexafffund
Abhinandan Banerjee, William Charles Hosie, Ana Carolina Terso Ventura, Kasra Razmkhah, Joseph Bautista, Afeson Beyene, Justin F. Binder, John F. Trant

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Windsor
KeywordsChromatographyChemistryPotencyZeta potentialHomogenizerMaterials scienceNanotechnologyNanoparticleBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Background: This paper highlights the formulation of a solid THC-loaded ingestible prepared from pure THC distillate. A THC ethanol-assisted cannabinoid nanoemulsion (EACNE) was created without the need for specialized emulsification equipment such as a high-pressure homogenizer or a microfluidizer. Stress-testing was performed on the EACNE to evaluate its chemical and colloidal stability under the influence of different environmental factors, encompassing both physical and chemical stressors. Subsequently, the EACNE was converted to a solid powdery material while still retaining its THC potency, and suited for “microdosing” applications. Methods: An ethanol-assisted emulsification method was used to generate a THC nanoemulsion. The EACNE was fully characterized, imaged, and subjected to stress-tests. The EACNE was then mixed with a solid matrix material post facto and lyophilized to create a solid ingestible substance. Upon ball-milling, a dense powdery material was obtained. Flow properties and thermal properties of this material were recorded. Potency of the material was evaluated in triplicate using HPLC and correlated with the potency of the starting EACNE. Results: EACNE had an average lipid droplet size of ca. 190 nm, with a polydispersity index (PDI) of 0.15, and an average droplet zeta potential of -49±10 mV. The nanoemulsion was colloidally stable for at least 6 weeks, with no meaningful change in cannabinoid potency over the experimental period, as determined by HPLC analysis. The EACNE remained stable when subjected to physical stresses such as heat, freeze/thaw cycles, carbonation, dilution to beverage concentrations, high sucrose concentrations, and a pH range between 5-8. The effect of undesirable events during the lyophilization of the EACNE were minimized by ball-milling the resulting solid. The microencapsulated EACNE demonstrated limited free-flowing behaviour but was freely redispersible in water without any visible phase separation. Conclusions: A solvent-mediated emulsification protocol creates a THC-loaded nanoemulsion that can subsequently be converted to a water-soluble powder. These materials are particularly suited for THC “microdosing”, a practice that might decouple the health benefits of THC from its psychotropic effects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.049
GPT teacher head0.321
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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