Medical device vigilance systems: India, US, UK, and Australia
Bibliographic record
Abstract
Pooja Gupta, Manthan D Janodia, Puralea C Jagadish, Nayanabhirama UdupaManipal Collge of Pharmaceutical Sciences, Manipal University, Manipal, Karnataka, IndiaAbstract: The term medical device includes a wide category of products ranging from therapeutic medical devices exerting their effects locally such as tissue cutting, wound covering or propping open clogged arteries, to highly sophisticated computerized medical equipment and diagnostic medical devices. To achieve uniformity among the national medical device regulatory systems and increase the access to safe, effective, and clinically beneficial medical technologies, the Global Harmonization Task Force (GHTF) was conceived in 1992 by five members: European Union, United States, Australia, Japan, and Canada. All regulated countries have clearly defined medical devices, as has the GHTF. Although GHTF has tried to achieve harmonization with respect to medical devices, some differences still exist in the national laws of the countries of GHTF. Further, regulated countries have classified medical devices on the basis of their associated risk. In the Indian regulatory system, medical devices are still considered as drugs. In 2006, the Medical Device Regulation Bill was recommended to consolidate laws for medical devices and to establish the Medical Device Regulatory Authority of India. In addition, medical devices are not classified by any Indian regulatory authority. Although India has moved towards harmonizing its medical device regulations with those of regulated countries, this study aims to identify whether India should have a vigilance system in harmony with those of GHTF or develop its own system for medical devices.Keywords: medical device, vigilance, regulatory systems, GHTF, India
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".