Availability and Accessibility of Essential Drugs for Rare Disorders in Canada
Bibliographic record
Abstract
In 2021, the Rare Disease Treatment Access Working Group (RDTAWG) of the International Rare Diseases Research Consortium, a European Union funded organization, published a list of medicinal products that they considered to be essential for the treatment of rare conditions. This study assesses the availability and accessibility of the RDTAWG medicines in Canada by comparing whether the rare disorder medicines approved for marketing in the United States also had regulatory approval for the same indication in Canada, and whether those medicines are ultimately covered under the 10 provincial government drug plans and the federal Non-Insured Health Benefits plan for indigenous persons. Data available at the end of August 2021 were accessed from the relevant online drug formularies. Most (85%) of the medicines with regulatory approval in the United States were also approved for the same indication in Canada. However, only just over half were covered by either open or conditional access in government drug plans, with the proportion ranging from under 36% in Manitoba to two-thirds in New Brunswick. Approximately 20% of the medicines had open access in all the plans, whereas the proportion with conditional access ranged from 13% in Manitoba to 45% in Ontario and New Brunswick. The average rate of coverage for medicines for disorders with a prevalence of ≤1 per 100,000 was only 28%, compared with 56% for disorders with a prevalence ranging from >1 case per 100,000 persons up to 1 case per 10,000 persons, and 60% for disorders with a prevalence of >1 case per 10,000 persons. Access to many medicines regarded by experts in the RDTAWG as essential for the welfare of individuals with rare disorders is inadequate to poor in Canada, especially for ultra-rare conditions. The federal Liberals and NDP are keen to introduce some type of national pharmacare. Any program developed by Canada’s governments must ensure that Canadians will have publicly funded access to all rare disorder medicines.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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".