JOURNAL ARTICLE
Disclosure of Origin in European Biotechnology Patent Law: A Social Network Analysis Perspective.
Published In: GRUR International: Journal of European & International IP Law, 2024, v. 73, n. 6. P. 510 1 of 3
Database: Legal Source 2 of 3
Authored By: Karimov, Elnur 3 of 3
Abstract
This article examines the requirement of disclosure of origin in European biotechnology patent law through a social network analysis (SNA) of 30 prominent biopiracy cases from South and Southeast Asia, Latin America, and Africa. It finds that, on average, there are approximately 2.5 intermediaries between indigenous and local communities (ILCs)—the primary sources of genetic resources (GRs) and associated traditional knowledge (TK)—and the nodes accused of biopiracy (NABs), such as patent applicants or commercial users. The increasing number of intermediaries over time complicates patent applicants' ability to accurately disclose primary sources, as intermediaries often transform biological materials and associated knowledge, weakening direct ties to original providers. The study suggests that current European patent disclosure requirements, which emphasize primary source information, may be impractical and recommends reconsidering the focus toward secondary sources like ex situ institutions and commercial suppliers, while acknowledging the challenges this poses for enforcing prior informed consent and benefit-sharing mechanisms.
Additional Information
- Source:GRUR International: Journal of European & International IP Law. 2024/06, Vol. 73, Issue 6, p510
- Document Type:Article
- Subject Area:Science
- Publication Date:2024
- ISSN:26328550
- DOI:10.1093/grurint/ikae028
- Accession Number:178089427
- Copyright Statement:Copyright of GRUR International: Journal of European & International IP Law is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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