Epinephrine for the treatment of anaphylaxis: do all 40 mg sublingual epinephrine tablet formulations with similar <i>in vitro</i> characteristics have the same bioavailability?
Bibliographic record
Abstract
Epinephrine autoinjectors are underutilized in the first aid emergency treatment of anaphylaxis in the community; so non-invasive sublingual epinephrine administration is being proposed. In order to determine the effect of changing excipients on the bioavailability of sublingual epinephrine, four distinct fast-disintegrating epinephrine 40 mg tablet formulations, A, B, C and D, were manufactured using direct compression. All formulations were evaluated for tablet hardness (H), disintegration time (DT) and wetting time (WT). In a prospective 5-way crossover study, four sublingual formulations and epinephrine 0.3 mg i.m. as a control were tested sequentially in a validated rabbit model. Blood samples were collected before dosing and at intervals afterwards. Epinephrine plasma concentrations were measured using HPLC-EC. All tablet formulations met USP standards for weight variation and content uniformity, and resulted in similar mean H, DT and WT (n=6). The area under the curve (AUC), maximum concentration (C(max)) and time at which C(max) was achieved (T(max)) did not differ significantly after the sublingual administration of formulation A and epinephrine 0.3 mg i.m. The AUC after B, C and D were significantly lower (p<0.05) than after epinephrine 0.3 mg i.m. These results suggest that the selection of excipients used in these tablet formulations can affect the bioavailability of sublingually administered epinephrine.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".