Some Numbers behind Canada’s Decision to Adopt an Orphan Drug Policy: US Orphan Drug Approvals in Canada, 1997–2012
Bibliographic record
Abstract
We examined whether access to US-approved orphan drugs in Canada has changed between 1997 (when Canada chose not to adopt an orphan drug policy) and 2012 (when Canada reversed its policy decision). Specifically, we looked at two dimensions of access to US-approved orphan drugs in Canada: (1) regulatory access; and (2) temporal access. Whereas only 63% of US-approved orphan drugs were granted regulatory approval in 1997, we found that regulatory access to US-approved orphan drugs in Canada increased to 74% between 1997 and 2012. However, temporal access to orphan drugs is slower in Canada: in a head-on comparison of 40 matched drugs, only two were submitted and four were approved first in Canada; moreover, the mean review time in Canada (423 days) was longer than that in the US (mean = 341 days), a statistically significant difference (t[39] = 2.04, p = 0.048). These results raise questions about what motivated Canada's apparent shift in orphan drug policy.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".