Microencapsulation for the Therapeutic Delivery of Drugs, Live Mammalian and Bacterial Cells, and Other Biopharmaceutics: Current Status and Future Directions
Bibliographic record
Abstract
Microencapsulation is a technology that has shown significant promise in biotherapeutics, and other applications. It has been proven useful in the immobilization of drugs, live mammalian and bacterial cells and other cells, and other biopharmaceutics molecules, as it can provide material structuration, protection of the enclosed product, and controlled release of the encapsulated contents, all of which can ensure efficient and safe therapeutic effects. This paper is a comprehensive review of microencapsulation and its latest developments in the field. It provides a comprehensive overview of the technology and primary goals of microencapsulation and discusses various processes and techniques involved in microencapsulation including physical, chemical, physicochemical, and other methods involved. It also summarizes the state-of-the-art successes of microencapsulation, specifically with regard to the encapsulation of microorganisms, mammalian cells, drugs, and other biopharmaceutics in various diseases. The limitations and future directions of microencapsulation technologies are also discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".