Delayed access to treatments for rare diseases: Who's to blame?
Bibliographic record
Abstract
The development and commercialization of drugs for rare diseases, termed 'orphan drugs', has historically been economically unattractive. However, because of the introduction of legislation that provides financial and regulatory incentives for the development of orphan drugs, new developments are making their way through the regulatory approval processes. Unfortunately, delays in availability of new drugs for treating rare disease continue to persist. This paper reviews the approach of several regulatory jurisdictions to orphan drugs in an effort to determine their relative effectiveness in providing patient access. Generally speaking, regulatory authorities across jurisdictions have recognized the need to enhance timely access to safe, effective treatment for patients with rare diseases and have been able to shift the approval timelines for access to new care. The greater impediment to orphan drug access appears to be funding, particularly in publicly sponsored health-care systems. Redundancies in federal and provincial reviews of orphan drugs can result in significant delays in access to new drugs. Clearly, more must be done to accelerate access to the treatments so desperately needed by patients. Public payers must be held accountable for their process and decisions--especially for rare disease therapies.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".