Nano-engineered electro-responsive drug delivery systems
Bibliographic record
Abstract
Stimuli-responsive drug delivery systems can release therapeutic agents when actuated by an appropriate stimulus, whether endogenous or exogenous. Interestingly, exogenous stimuli are completely dissociated from the patient's physiology and can be precisely controlled externally in magnitude, in space, and in time. They can therefore constitute more reproducible means of controlling the release of therapeutics from appropriately responsive delivery systems. One stimulus which has long attracted attention is the application of an electric potential, and most electro-responsive drug delivery systems reported to date have been based on intrinsically conducting polymers. These systems, however, are limited by slow drug release and low drug loading. These challenges are currently driving the development of new electro-responsive delivery systems with higher responsiveness and drug loading, by implementing concepts of nano-engineering into their structure. This review will focus on this exciting and most recent direction taken in this field by first discussing drug delivery from electro-responsive films containing nano-scaled features, and then nanoscale dispersed/colloidal electro-responsive drug delivery systems, such as nanoparticles, micelles, and vesicular structures.
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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 | 0.000 |
| 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 | 0.001 |
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".