New Chemical Entity Data Exclusivity Periods for Pharmaceuticals
Bibliographic record
Abstract
Abstract This chapter examines data and market exclusivity frameworks across Australia, Canada, the United States, and the EU, focusing on new chemical entities, active components, and the reclassification of medicinal products. Australia provides five years of protection for protected information under section 25A of the Therapeutic Goods Act 1989. It details Canada’s regime, granting eight years of protection for innovative drugs, a six-year bar on generic filings, and a six-month extension for paediatric use. The chapter discusses the FDA’s treatment of single enantiomers under the Federal Food, Drug, and Cosmetic Act, where enantiomers like esomeprazole are generally ineligible for five-year NCE exclusivity. Italy and the Netherlands implement EU rules on switching from prescription medicine to non-prescription medicine, with Italy granting one year of data exclusivity for ‘significant’ tests and the Netherlands applying a harmonised eight-year data exclusivity plus two years of market exclusivity.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.014 |
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".