Clay and Polymer-Based Composites Applied to Drug Release: A Scientific and Technological Prospection
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Bibliographic record
Abstract
There has been a growing trend in recent years for the development of hybrid materials, called composites, based on clay and polymers, whose innovative properties render them attractive for drug release. The objective of this manuscript was to conduct a review of original articles on this topic published over the last decade and of the body of patents related to these carriers. A scientific prospection was carried out spanning the period from 2005 to 2015 on the Web of Science database. The technological prospection encompassed the United States Patent and Trademark Office, the European Patent Office, the World International Patent Office and the National Institute of Industrial Property databases, filtering patents with the code A61K. The survey revealed a rise in the number of publications over the past decade, confirming the potential of these hybrids for use in pharmaceutical technology. Through interaction between polymer and clay, the mechanical and thermal properties of composites are enhanced, promoting stable, controlled drugs release in biological media. The most cited clays analyzed in the articles was montmorillonite, owing to its high surface area and capacity for ion exchange. The polymeric part is commonly obtained by copolymerization, particularly using acrylate derivatives. The hybrid materials are obtained mainly in particulate form on a nanometric scale, attaining a modified release profile often sensitive to stimuli in the media. A low number of patents related to the topic were found. The World International Patent Office had the highest number of lodged patents, while Japan was the country which published the most patents. A need to broaden the application of this technology to include more therapeutic classes was identified. Moreover, the absence of regulation of nanomaterials might explain the disparity between scientific and technological output. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it