Postmarket Safety Communication for Protection of Public Health: A Comparison of Regulatory Policy in Australia, Canada, the European Union, and the United States
Bibliographic record
Abstract
In the wake of the withdrawal of the nonsteroidal anti-inflammatory drug rofecoxib, regulators worldwide reconsidered their approach to postmarket safety. Many have since adopted a "life cycle" approach to regulation of medicines, facilitating faster approval of new medicines while planning for potential postmarket safety issues. A crucial aspect of postmarket safety is the effective and timely communication of emerging risk information using postmarket safety advisories, commonly issued as letters to healthcare professionals, drug safety bulletins, media alerts, and website announcements. Yet regulators differ in their use of postmarket safety advisories. We examined the capacity of regulators in the United States, Europe, Canada, and Australia to warn about postmarket safety issues through safety advisories by assessing their governance, legislative authority, risk communication capabilities, and transparency.
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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 | 0.041 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".