Commentary: Expedited Regulatory Review of Low-Value Drugs
Bibliographic record
Abstract
Lexchin has criticized Health Canada' s recently published draft guidance on accelerated drug review, expressing concern over agency conflicts of interest and observing that priority review and notice of compliance with conditions correlate poorly with therapeutic benefit.Although agency operations may be imperfect, perhaps the most important finding of Lexchin' s research is that only 11% of newly approved drugs provide meaningful benefit over standard treatments.To improve the expedited review process in light of these findings, we suggest eliminating user fees and fully funding the review process with public monies, reserving the use of expedited approval pathways for when preliminary measures of benefit are so large that traditional approval thresholds can be met earlier in the clinical trial process, improving labelling to quantitatively communicate drug benefits and risks, and avoiding the use of titles such as "priority" review, which could imply a magnitude of clinical superiority that has not been established. RésuméLexchin a critiqué la version provisoire des lignes directrices de Santé Canada sur l' examen accéléré des médicaments, publiée récemment, en se disant préoccupé par les conflits d'intérêt de l'institution et en observant qu'il y a une faible corrélation entre, d' une part, DISCUSSION AND DEBATE[36] HEALTHCARE POLICY Vol.15 No.4, 2020 l' examen prioritaire et les avis de conformité avec conditions et, d' autre part, les avantages thérapeutiques.Bien que les activités de l'institution soient imparfaites, la principale découverte de Lexchin est sans doute que seuls 11 % des médicaments nouvellement approuvés apportent un avantage significatif par rapport aux traitements habituels.Pour améliorer le processus d' examen à la lumière des résultats de Lexchin, nous proposons d'éliminer les frais de service et de financer entièrement le processus d' examen avec les fonds publics, tout en réservant les voies d' approbation accélérées pour les cas où le constat préliminaire des avantages est si important que les seuils d' approbation traditionnels peuvent être atteints plus tôt au cours de la phase d' essai clinique, en améliorant l'étiquetage pour communiquer quantitativement les avantages et risques liés aux médicaments et en évitant l' utilisation d'énoncés tels qu' « examen prioritaire » lesquels portent à croire à un degré de supériorité clinique qui n' a pas été établi.
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 | 0.030 | 0.174 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.013 | 0.003 |
| Research integrity | 0.138 | 0.101 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".