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Record W2094081851 · doi:10.1517/13543784.2013.840289

Investigational drugs for onychomycosis

2013· review· en· W2094081851 on OpenAlexaff
Aditya K. Gupta, Fiona C. Simpson

Bibliographic record

VenueExpert Opinion on Investigational Drugs · 2013
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsTerbinafineMedicineAdverse effectDrugDermatologyDrug developmentPharmacologyClinical trialIntensive care medicineAntifungalItraconazoleInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Onychomycosis is the fungal infection of the nail plate by dermatophytes, yeasts and nondermatophyte molds. The treatment of onychomycosis poses many challenges due to low initial cure rates and a high rate of relapse and recurrence. Oral therapy is limited by adverse events and drug-drug interactions, whereas topical therapy has limited penetrance through the nail plate. AREAS COVERED: New and reformulated drugs are in development for the treatment of onychomycosis. Experimental molecules include both oral and topical azole molecules, topical reformulations of terbinafine, the benzoxaboroles tavaborole and AN2718, the aganocide NVC-422 and the photosensitizer Sylsens B. These drugs are in varying stages of development so results from in vitro studies to Phase III clinical trials are discussed to present a complete picture of the current development pipeline for onychomycosis. EXPERT OPINION: The development of new molecules from familiar and novel classes for both oral and topical administration is encouraging. It is clear that there is currently more emphasis on the development of topical drugs than orals, due to their lower potential for adverse events and drug-drug interactions. The emergence of novel molecular targets is encouraging for the possibility of combination therapy and any future drug-resistant strains of fungi.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.698
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.120
GPT teacher head0.410
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2013
Admission routes1
Has abstractyes

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