The evolving role of oral insulin in the treatment of diabetes using a novel RapidMist? System
Bibliographic record
Abstract
The inability of subcutaneous (sc) insulin to effectively, safely and painlessly control postprandial glucose levels has encouraged the exploration of alternate methods of insulin delivery. Recently, a novel drug delivery system, based on a unique liquid aerosol formulation, has been developed. This system allows precise insulin dose delivery via a simple, cosmetically acceptable metered dose inhaler in the form of fine aerosolized droplets directed into the mouth. The system introduces a fine-particle aerosol at high velocity into the patient's breath; the mouth deposition is dramatically increased compared with conventional technology. This oral aerosol formulation is rapidly absorbed through the buccal mucosal lining and in the oropharynx regions, and it provides the plasma insulin levels necessary to control postprandial glucose rise in diabetic patients. This novel, pain-free, oral insulin formulation has a critical series of attributes: rapid absorption, a simple (user-friendly) administration technique, precise dosing control (comparable to injection within one unit), and bolus delivery of drug. This review describes the recent results of clinical studies (in type 1 and type 2 diabetic patients) by comparing the efficacy of Oralin (oral insulin spray) versus sc injected insulin and placebo arms. A simplified means for prandial insulin delivery, such as that offered by this technique, will significantly reduce the incidence of key complications by allowing increased patient compliance for consistent drug administration in order to regulate patients' blood glucose levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".