Comparison of oncology drug approval between Health Canada and the US Food and Drug Administration
Bibliographic record
Abstract
BACKGROUND: The drug approval timeline is a lengthy process that often varies between countries. The objective of this study was to delineate the Canadian drug approval timeline for oncology drugs and to compare the time to drug approval between Health Canada (HC) and the US Food and Drug Administration (FDA). METHODS: In total, 54 antineoplastic drugs that were approved by the FDA between 1989 and 2012 were reviewed. For each drug, the following milestones were determined: the dates of submission and approval for both the FDA and HC and the dates of availability on provincial drug formularies in Canadian provinces and territories. The time intervals between the aforementioned milestones were calculated. RESULTS: Of 54 FDA-approved drugs, 49 drugs were approved by HC at the time of the current study. The median time from submission to approval was 9 months (interquartile range [IQR], 6-14.5 months) for the FDA and 12 months (IQR, 10-21.1 months) for HC (P < .0006). The time from HC approval to the placement of a drug on a provincial drug formulary was a median of 16.7 months (IQR, 5.9-27.2 months), and there was no interprovincial variability among the 5 Canadian provinces that were analyzed (P = .5). CONCLUSIONS: The time from HC submission to HC approval takes 3 months longer than the same time interval for the FDA. To the authors' knowledge, this is the first documentation of the time required to bring an oncology drug from HC submission to placement on a provincial drug formulary.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".