Time to completion of conditions required by Health Canada after approving new drugs: A cohort study
Bibliographic record
Abstract
BACKGROUND: To ensure that promising drugs for serious illnesses reach Canadians in a timely manner, Health Canada can approve them conditionally provided companies commit to conducting confirmatory studies to verify the benefits. OBJECTIVE: To determine how long it takes until the conditions are fulfilled and if certain factors affect that length of time. METHODS: A list of conditional approvals for new drugs and new indications for existing drugs to the end of 2024 was compiled from Health Canada databases. Orphan drug status was determined from the US Food and Drug Administration databases. Kaplan-Meier survival curves were constructed to determine how long it took to complete the studies. RESULTS: There were 153 conditional approvals: 91 were fulfilled, 45 have not been fulfilled as of January 18, 2025 and 17 were withdrawn. The median time for fulfillment was 1200 (IQR 777, 1852) days. Orphan drug status and whether the conditional approval was for a new drug or a new indication for an existing drug did not affect the time to completion. CONCLUSIONS: Some NOC/c take considerable time to be fulfilled. Health Canada should require studies to be underway at the time that a NOC/c is granted except in exceptional circumstances and it should be transparent about the completion date for confirmatory studies and provided detailed reports about any delays. In the case of delays that cannot be justified it should be given the power to impose significant financial penalties on manufacturers through the NOC/c pathway being converted from a policy into legislation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".