Real-Time Chemical, Microbiological, and Physical Stability of Extemporaneously Compounded Amiloride Nasal Spray Over 90 Days at Refrigerated and Room Temperatures.
Bibliographic record
Abstract
Amiloride is a commonly known FDA-approved diuretic used to treat hypertension and congestive heart failure. In more recent years, it has been postulated that it might also serve as an anxiolytic agent due to its agonistic effects on acid-sensing ion channels (ASIC). An intranasal administration of an extemporaneously compounded amiloride would allow for easy and rapid access to the site of action to alleviate symptoms of anxiety and other related disorders. However, compounded patient-preparations do not have the chemical stability or pre-formulation characterization that typical manufactured dosage forms have. The purpose of this study was to assess the real-time chemical, microbiological, and physical stability of extemporaneously compounded amiloride nasal spray over the course of 90 days. This was accomplished via a validated, high-performance liquid chromatography (HPLC) method at designated and appropriate time points to reveal that amiloride remained highly chemically stable over 50 days at 4 and 20 degrees Celsius and retained sufficient stability after 90 days from initial compounding. Additionally, the physical stability of the solution when combined with the preservative benzyl alcohol was confirmed via visual inspection, pH monitoring, and measuring of turbidity.
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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 | 0.001 |
| 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".