Regulatory policies between Brazil, Canada, USA and Portugal (CEE) : a comparison of regulatory requirements taking into consideration the various levels of requirement for the registration of generic drugs in different countries
Bibliographic record
Abstract
Access to medicines with quality and low price constitutes the fundamental principle of health policies in government programs of different countries. Since their introduction, generic medicines were designed to ensure improved access by the populace, given their identical quality, safety and effectiveness when compared to their reference products and also given their much lower cost. Further, upon creation of this new pharmaceutical category, national health regulatory agencies around the world, through their product registration regulations, developed systems to define and enforce the criteria governing generic medicines. To meet the aforementioned requirements of quality, safety and effectiveness, each country - whether or not using international regulations as its regulatory basis – to some degree varied its requirements for the registration of generic medicines in order to ensure its regulatory sovereignty and in some cases to protect its local production. The objective of this work is to demonstrate the differences between generic medicine registration requirements, of the health regulatory agencies of the countries compared herein. To achieve this goal, comparisons were made between relevant pieces of legislation of selected countries and regions. This work contains the effective regulations applied in each comparative region as well as comments and explanations of the procedures adopted by each one. The main conclusion demonstrated through this work is that the administrative information in the submission of dossiers for registration of generic products is presented in different formats in each country. However, the technical essence of these requirements is not so different in that only the required levels of detail present greater or lesser degrees of difficulty.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".