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Record W1824984326 · doi:10.1089/nat.2012.0345

Clinical Expert Panel on Monitoring Potential Lung Toxicity of Inhaled Oligonucleotides: Consensus Points and Recommendations

2012· article· en· W1824984326 on OpenAlexaff
Eric W.F.W. Alton, Homer A. Boushey, Holger Garn, Francis H. Green, Michael R. Hodges, Richard J. Martin, Robert Murdoch, Harald Renz, Stephen B. Shrewsbury, Rosanne Séguin, Graham D. Johnson, Joel D. Parry, Jeff Tepper, Paolo Renzi, Joy Cavagnaro

Bibliographic record

VenueNucleic Acid Therapeutics · 2012
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsPharmaxis (Canada)Université de MontréalUniversity of Calgary
Fundersnot available
KeywordsToxicityInhalationMedicineIntensive care medicineOligonucleotideIdentification (biology)Risk analysis (engineering)PharmacologyBioinformaticsBiologyInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Oligonucleotides (ONs) are an emerging class of drugs being developed for the treatment of a wide variety of diseases including the treatment of respiratory diseases by the inhalation route. As a class, their toxicity on human lungs has not been fully characterized, and predictive toxicity biomarkers have not been identified. To that end, identification of sensitive methods and biomarkers that can detect toxicity in humans before any long term and/or irreversible side effects occur would be helpful. In light of the public's greater interests, the Inhalation Subcommittee of the Oligonucleotide Safety Working Group (OSWG) held expert panel discussions focusing on the potential toxicity of inhaled ONs and assessing the strengths and weaknesses of different monitoring techniques for use during the clinical evaluation of inhaled ON candidates. This white paper summarizes the key discussions and captures the panelists' perspectives and recommendations which, we propose, could be used as a framework to guide both industry and regulatory scientists in future clinical research to characterize and monitor the short and long term lung response to inhaled ONs.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.661

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 integrity0.0000.001
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 head0.159
GPT teacher head0.444
Teacher spread0.285 · 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 designOther design
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

Citations25
Published2012
Admission routes1
Has abstractyes

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