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The repositioning of the anti-fungal agent ciclopirox olamine as a novel therapeutic agent for the treatment of haematologic malignancy

2010· article· en· W2138288799 on OpenAlexaff
Scott J. Weir, Lavonne Patton, Katherine D. Castle, Lian Rajewski, Jim Kasper, Aaron D. Schimmer

Bibliographic record

VenueJournal of Clinical Pharmacy and Therapeutics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPolyamine Metabolism and Applications
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer Research
Fundersnot available
KeywordsMedicinePharmacology

Abstract

fetched live from OpenAlex

WHAT IS KNOWN AND OBJECTIVE: 6-Cyclohexyl-1-hydroxy-4-methyl-2(1H)-pyridone (ciclopirox) and specifically its olamine salt 6-cyclohexyl-1-hydroxy-4-methyl-2(1H)-pyridone 2-aminoethanol salt (ciclopirox olamine) are anti-fungal agents currently used for the treatment of mild to moderate cutaneous fungal infection. Our objective is to comment on the opportunity to rapidly reposition ciclopirox and its olamine for the treatment of haematologic malignancy by leveraging its prior published toxicology and pharmacology data. COMMENT: Ciclopirox olamine chelates intracellular iron and displays preclinical efficacy in the treatment of haematologic malignancy. Currently, an ongoing study is evaluating topical ciclopirox olamine for the treatment of cervical cancer. Doses of ciclopirox olaine required for a systemic anti-cancer effect appear pharmacologically achievable. However, caution is required as at the highest doses tested in animal toxicology studies, irreversible cardiac degeneration was observed. WHAT IS NEW AND CONCLUSION: The existing pharmacology and toxicology data suggest that systemic ciclopirox olamine could be repositioned as a new investigational anti-cancer agent. The available pharmacology and toxicology data should aid in the design of phase I clinical trials of this agent in patients with refractory haematologic malignancies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.078
GPT teacher head0.419
Teacher spread0.341 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations39
Published2010
Admission routes1
Has abstractyes

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