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Record W2907787788 · doi:10.1177/0020731418821007

Health Canada’s Use of its Notice of Compliance With Conditions Drug Approval Policy: A Retrospective Cohort Analysis

2018· article· en· W2907787788 on OpenAlexaffabout
Joel Lexchin

Bibliographic record

VenueInternational Journal of Health Services · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsYork University
Fundersnot available
KeywordsNoticeMedicineGeneric drugDrugCohortRetrospective cohort studyCancer drugsBusinessPharmacologyLawSurgeryPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

Health Canada has developed its Notice of Compliance with conditions (NOC/c) policy to get promising new drugs for serious diseases to market faster than would be possible through its standard approval process. Companies can receive an NOC/c for a new drug or a new indication based on incomplete evidence in return for agreeing to conduct post-market studies. This paper investigates the additional therapeutic gain from drugs approved under this policy, the percent of drugs that have fulfilled their conditions, and the length of time for fulfillment. From the inception of the policy in 1998 to the end of 2017, 89 new drugs and new indications for existing drugs received an NOC/c. Therapeutic evaluations were available for 78 of the drugs, and 54 offered only minimal or no gains over existing products. Fifty NOC/c were fulfilled, 31 were not fulfilled, and 8 were withdrawn. The median time to fulfillment was 1,040 days. Twelve NOC/c took more than 5 years to fulfill their conditions. The unfulfilled NOC/c had been issued for a median of 1,161 days, and 10 had been issued more than 5 years. The value of the NOC/c policy to patients is uncertain.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.188
GPT teacher head0.437
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2018
Admission routes2
Has abstractyes

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