A review of the efficacy and safety of nanoparticle-based oral insulin delivery systems
Bibliographic record
Abstract
Nanotechnology is providing new and innovative means to detect, diagnose, and treat disease. In this regard, numerous nanoparticle-based approaches have been taken in an effort to develop an effective oral insulin therapy for the treatment of diabetes. This review summarizes efficacy data from studies that have evaluated oral insulin therapies in experimental models. Also provided here is an overview of the limited safety data that have been reported in these studies. To date, the most promising approaches for nanoparticle-based oral insulin therapy appear to involve the incorporation of insulin into complex multilayered nanoparticles that are mucoadhesive, biodegradable, biocompatible, and acid protected and into nanoparticles that are designed to take advantage of the vitamin B(12) uptake pathway. It is anticipated that the continued investigation and optimization of nanoparticle-based formulations for oral delivery of insulin will lead to a much sought-after noninvasive treatment for diabetes. Such investigations also may provide insight into the use of nanoparticle-based formulations for peptide- and protein-based oral treatment of other diseases and for various food-related purposes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".