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Record W1769059961 · doi:10.1517/13543776.2015.1086749

A STAT inhibitor patent review: progress since 2011

2015· review· en· W1769059961 on OpenAlexaff
Ping‐Shan Lai, David A. Rosa, Rodolfo F. Gómez‐Biagi, Daniel P. Ball, Andrew E. Shouksmith, Patrick T. Gunning

Bibliographic record

VenueExpert Opinion on Therapeutic Patents · 2015
Typereview
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsDairy Farmers of OntarioUniversity of Toronto
Fundersnot available
KeywordsSTAT5statSH2 domainComputational biologySTAT3Cancer researchBiologyKinasePhosphorylationGenetics

Abstract

fetched live from OpenAlex

INTRODUCTION: The clinical utility of effective direct STAT inhibitors, particularly STAT3 and STAT5, for treating cancer and other diseases is well studied and known. AREAS COVERED: This review will highlight the STAT inhibitor patent literature from 2011 to 2015 inclusive. Emphasis will be placed on inhibitors of the STAT3, STAT5a/b, and STAT1 proteins for cancer treatment. The review will, where suitably investigated, describe the mode and the site of inhibition, list indications that were evaluated, and rank the inhibitor's relative potency among compounds in the same class. The reader will gain an understanding of the diverse set of approaches, used both in academia and industry, to target STAT proteins. EXPERT OPINION: There is still much work to be done to directly target the STAT3 and STAT5 proteins. As yet, there is still no direct STAT3 inhibitor in the clinic. While the SH2 domain remains a popular target for therapeutic intervention, the DNA-binding domain and N-terminal region are now attracting attention as possible sites for inhibition. Multiple putative STAT3 and STAT5 inhibitors have now been patented across a broad spectrum of chemotypes, each with their own advantages and limitations.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.307
GPT teacher head0.441
Teacher spread0.134 · 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 designOther design
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

Citations55
Published2015
Admission routes1
Has abstractyes

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