A Comparison of the Drug Approval Process in the United States and Canada
Bibliographic record
Abstract
The drug approval process is comparative between the United States and Canada. Without the drug approval process, consumers would be experiencing severe health consequences, therefore, the approval process is expensive, time-consuming, and lengthy for pharmaceutical companies to ensure the compound is safe and effective for its intended use. The electronic databases utilized to recognize applicable published articles from Embase/Ovid and PubMed. The keywords utilized to recognize the pertinent articles were the following: Drug Approval, Drug Development, Food and Drug Administration, United States, Canada, and Pharmaceuticals. The research articles excluded were: non-drug, including vaccines approval process, international regulatory organizations, articles that weren’t relevant to the study, and articles that are not in English language. There was no limit on the date the articles were published. There are more similarities than differences in the drug approval process between Canada and the United States. Both countries contain a regulatory organization (Health Canada; FDA) that review and approve novel drugs to ensure safety and efficacy prior to marketing. Pharmaceutical companies must submit an IND application prior to the inception of clinical trials in humans. Drug approval by FDA is similar to Health Canada, where they develop guidance recommendations to assist pharma companies in complying with regulations. The majority of the published articles focus on the comparison of the drug approval process between the United States and other countries, little-to-no articles discussed the advantages/disadvantages of the drug approval process and how the length of the approval process effects patient population.
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 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 | 0.013 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.028 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".