Improving access to new diagnostics through harmonised regulation: priorities for action
Bibliographic record
Abstract
A new generation of diagnostic tests is being developed for use at the point of care that could save lives and reduce the spread of infectious diseases through early detection and treatment. It is important that patients in developing countries have access to these products at affordable prices and without delay. Regulation of medical products is intended to ensure safety and quality whilst balancing the need for timely access to beneficial new products. Current regulatory oversight of diagnostic tests in developing countries is highly variable and weak regulation allows poor-quality tests to enter the market. However, inefficient or overzealous regulation results in unnecessary delays, increases costs and acts as a barrier to innovation and market entry. Setting international standards and streamlining the regulatory process could reduce these barriers. Four priority activities have been identified where convergence of standards and protocols or joint review of data would be advantageous: (1) adoption of a common registration file for pre-market approval; (2) convergence of quality standards for manufacturing site inspections; (3) use of common evaluation protocols, as well as joint review of data, to reduce unnecessary duplication of lengthy and costly clinical performance studies; and (4) use of networks of laboratories for post-market surveillance in order to monitor ongoing quality of diagnostic devices. The adoption and implementation of such measures in developing countries could accelerate access to new diagnostic tests that are safe and affordable.
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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 | 0.185 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.011 | 0.017 |
| Research integrity | 0.031 | 0.025 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".