Transdermal Drug Delivery Systems (TDDS): Recent Advances and Failure Modes
Bibliographic record
Abstract
Transdermal drug delivery systems (TDDS), commonly refered to as "patches", present a nonintrusive technique to provide medication without the need for invasive procedures. These products adhere to the skin and gradually release a specific dosage of medicine at a defined rate into the bloodstream. Compared with other methods of drug delivery, TDDS offer benefits such as reduced invasiveness, convenience for patients, and avoidance of the metabolic processes that occur when drugs are orally consumed. Throughout time, TDDS have been used to provide medications for various medical conditions (such as nicotine, fentanyl, nitroglycerin, and clonidine), and their potential for delivering biologics is currently being explored. This review investigates the current literature on the drug delivery efficacy of medical TDDS through the transdermal route. Additionally, the review addresses potential risks and failure modes associated with TDDS design and development as well as strategies for mitigating such risks. A thorough understanding of failure modes provides a blueprint to mitigate failure and produce high-quality efficacious therapeutics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".