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Transdermal Drug Delivery Systems (TDDS): Recent Advances and Failure Modes

2024· review· en· W4403114996 on OpenAlex
Mohsen Ghaferi, Seyed Ebrahim Alavi, Khanh Phan, Howard I. Maibach, Yousuf Mohammed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Pharmaceutics · 2024
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsFraser Institute
Fundersnot available
KeywordsTransdermalDrug deliveryPharmacologyDrugMedicinePharmaceutical technologyChemistryChromatography

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.123
GPT teacher head0.466
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it