“To patent or not to patent? the case of Novartis’ cancer drug Glivec in India”
Bibliographic record
Abstract
BACKGROUND: Glivec (imatinib mesylate), produced by the pharmaceutical company Novartis, is prescribed in the case of chronic myeloid leukemia, one of the most common blood cancers in eastern countries. After more than a decade of legal battles surrounding its patentability, the Supreme Court of India gave its final decision on April 1st of 2013, rejecting the appeal of the Swiss giant drug manufacturer. In 2006, the Indian Patent Office first refused Glivec's patent under Section 3(d) of the Indian Patent Act arguing that it was only a modified version of an existing drug, Imatinib, and therefore that the drug was not innovative. Novartis replied filing legal challenges against the Indian government but the final verdict in April of 2013 ends the battle. Indeed, the Supreme Court stated that even if the bioavailability of the drug was improved, it did not demonstrate enhanced efficacy and that Glivec was not patentable. METHODS: The research primarily focused on journal, newspaper and magazine articles relevant to the time frame of the lawsuit (from 1994 to 2013) as well as news searches through Google, Factiva, ProQuest, PubMed, and YouTube where press articles from court verdicts were obtained by using the following keywords: "India", "Novartis", "Glivec", "Patent", "Novartis Case", and "Supreme Court of India". The data sources were interpreted and analyzed according to the authors' own prior knowledge and understanding of the exigencies of the TRIPS Agreement. RESULTS: This case illuminates how India is interpreting international law to fit domestic public health needs. CONCLUSIONS: The Novartis case arguably sets an important precedent for the global pharmaceutical industry and ideally will help improve access to lifesaving medicines in the developing world by demanding that patient health needs supersede commercial interests. The Supreme Court of India's decision may affect the interpretation of the article of the TRIPS Agreement, which states members shall be free to determine the appropriate method of implementing the provisions of this Agreement within their own legal system and practice.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".