Bibliographic record
Abstract
This paper examines patent linkage mechanisms—regulatory frameworks that condition pharmaceutical marketing approval for generic and biosimilar drugs on patent status assessments—as a critical intersection between intellectual property protection and public health access. Through comparative jurisdictional analysis of the United States (Hatch-Waxman Act), Canada (PM(NOC) Regulations), China (recent 2021 implementation), and Japan (administrative discretion model), alongside India's principled rejection of linkage, the article evaluates the empirical consequences of patent linkage systems on generic drug market entry timelines, pricing accessibility, and compulsory licensing effectiveness. The analysis demonstrates that while patent linkage theoretically balances innovation incentives with generic competition, empirical evidence reveals systematic delays in generic market entry (2–8 years post-patent expiration in Canada), facilitation of patent evergreening strategies, and measurable healthcare cost increases exceeding $1.5 billion in select drug categories. The paper situates patent linkage within broader TRIPS-plus normative frameworks arising from bilateral trade negotiations, identifies institutional competence conflicts between patent offices and drug regulators, and proposes policy alternatives—including functional separation of patent validity determination and pharmaceutical safety-efficacy assessment—to preserve access-to-medicines objectives while maintaining intellectual property protections. The study concludes that jurisdictions prioritizing pharmaceutical accessibility should maintain institutional boundaries between intellectual property and regulatory authorities while preserving compulsory licensing flexibilities under international law.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".