Carcinogenicity risk assessment of romosozumab: A review of scientific weight-of-evidence and findings in a rat lifetime pharmacology study
Bibliographic record
Abstract
monoclonal antibody that binds and blocks the action of sclerostin, a protein secreted by the osteocyte and an extracellular inhibitor of canonical Wnt signaling. Blockade of sclerostin binding to low-density lipoprotein receptor-related proteins 5 and 6 (LRP5 and LRP6) allows Wnt ligands to activate canonical Wnt signaling in bone, increasing bone formation and decreasing bone resorption, making sclerostin an attractive target for osteoporosis therapy. Because romosozumab is a bone-forming agent and an activator of canonical Wnt signaling, questions have arisen regarding a potential carcinogenic risk. Weight-of-evidence factors used in the assessment of human carcinogenic risk of romosozumab included features of canonical Wnt signaling, expression pattern of sclerostin, phenotype of loss-of-function mutations in humans and mice, mode and mechanism of action of romosozumab, and findings from romosozumab chronic toxicity studies in rats and monkeys. Although the weight-of-evidence factors supported that romosozumab would pose a low carcinogenic risk to humans, the carcinogenic potential of romosozumab was assessed in a rat lifetime study. There were no romosozumab-related effects on tumor incidence in rats. The findings of the lifetime study and the weight-of-evidence factors collectively indicate that romosozumab administration would not pose a carcinogenic risk to humans.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".