Delayed access to treatments for rare diseases: Who's to blame?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.008 |
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 it