Adrenaline (epinephrine) microcrystal sublingual tablet formulation: enhanced absorption in a preclinical model
Bibliographic record
Abstract
OBJECTIVES: For anaphylaxis treatment in community settings, adrenaline (epinephrine) administration using an auto-injector in the thigh is universally recommended. Despite this, many people at risk of anaphylaxis in community settings do not carry their prescribed auto-injectors consistently and hesitate to use them when anaphylaxis occurs.The objective of this research was to study the effect of a substantial reduction in adrenaline (Epi) particle size to a few micrometres (Epi microcrystals (Epi-MC)) on enhancing adrenaline dissolution and increasing the rate and extent of sublingual absorption from a previously developed rapidly disintegrating sublingual tablet (RDST) formulation in a validated preclinical model. METHODS: The in-vivo absorption of Epi-MC 20 mg RDSTs and Epi 40 mg RDSTs was evaluated in rabbits. Epi 0.3 mg intramuscular (IM) injection in the thigh and placebo RDSTs were used as positive and negative controls, respectively. KEY FINDINGS: Epimean (standard deviation) area under the plasma concentration vs time curves up to 60 min and Cmax from Epi-MC 20 mg and Epi 40 mg RDSTs did not differ significantly (P > 0.05) from Epi 0.3 mg IM injection. After adrenaline, regardless of route of administration, pharmacokinetic parameters were significantly higher (P < 0.05) than after placebo RDSTs administration (reflecting endogenous adrenaline levels). CONCLUSION: Epi-MC RDSTs facilitated a twofold increase in Epi absorption and a 50% reduction in the sublingual dose. This novel sublingual tablet formulation is potentially useful for the first-aid treatment of anaphylaxis in community settings.
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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 | 0.000 |
| 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 | 0.001 |
| 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".