Clinical Expert Panel on Monitoring Potential Lung Toxicity of Inhaled Oligonucleotides: Consensus Points and Recommendations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.112 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.033 | 0.020 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".