Stability of Commercially Available Glucagon Formulation for Dual-Hormone Artificial Pancreas Clinical Use
Bibliographic record
Abstract
Background: Available glucagon formulations are approved for immediate use after reconstitution for severe hypoglycemia emergency treatment. However, they are used in dual-hormone artificial pancreas (insulin and glucagon) studies through subcutaneous infusion pumps over 24 h. Chemical and physical stability of such glucagon use have not been reported in a comprehensive manner. Materials and Methods: Recombinant Glucagon DNA (Eli Lilly) was used. Compatibility and sterility of glucagon delivery through subcutaneous pump systems were verified. Glucagon degradation through liquid chromatography with tandem mass spectrometry (LC-MS/MS), fibrillation using intrinsic tryptophan fluorescence shift, and bioactivity through a cell-protein kinase A-based fluorescent bioassay were assessed over a range of different physical conditions (temperature, movement, and air bubbles). Results: Subcutaneous infusion pump systems administered glucagon in sterile conditions and with comparable accuracy to insulin delivery; mean absolute relative difference of actual versus expected weights were 1.2% ± 1.1% for glucagon and 1.1% ± 0.5% for insulin ( P = 0.9). In comparison to freshly reconstituted samples, glucagon analyzed through LC-MS/MS was intact at 93.0% ± 7.0% after 24 h ( P = 0.42) and 83.04% ± 6.0% after 48 h ( P = 0.02) of incubation in pumps at 32°C. Peak wavelengths for Trp fluorescence did not differ from samples exposed to air bubbles or movement whether incubated (in infusion sets for 24 h at 32°) immediately or 24- and 48-h poststorage at 4°C ( P = 0.10, 0.70 and 0.80, respectively) and no significant differences in bioactivity (shifts in EC 50 ) were found for the same conditions ( P = 0.13, 0.83, and 0.63). Conclusion: Available glucagon formulations are chemically and physically stable, as well as compatible with delivery through subcutaneous infusion pumps over 24 h and can be used in long-term clinical trials.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".