Prediction of therapeutic value of new drugs approved by health Canada from 2011−2020: A cross-sectional study
Bibliographic record
Abstract
ObjectivesTo examine whether a combination of three characteristics of new drugs – review type, outcome of premarket trials (surrogate or clinical) and first-in-class is associated with significant therapeutic value.DesignCross-sectional analysis of new drugs approved by Health Canada from January 1, 2011 to December 31, 2020.SettingCanada.ParticipantsNew drugs approved by Health Canada for which therapeutic evaluations, trial outcomes and first-in-class status was available.Main outcome measuresDistribution of therapeutic value (major, moderate, little to no) depending on how many of the three characteristics were present for each drug.ResultsHealth Canada approved 340 drugs of which 243 had data available for analysis. If all three characteristics were present 10 out of the 20 drugs had a major therapeutic rating. Conversely if none were present only 2 drugs out of 37 had a major therapeutic rating.ConclusionThis study introduces a new evaluation method for determining whether new drugs will have major therapeutic value that appears to be more successful than relying only on the type of review that drugs receive.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".