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Evolution of Patenting in GMOs and Innovation Appropriability : Implications for Agriculture

Evolution of Patenting in GMOs and Innovation Appropriability : Implications for Agriculture Maria Ester Dal- Poz .-Faculty, School of Applied Sciences – University of Campinas – UNICAMP, José Maria Jardim Ferreira da Silveira- Faculty, Institute of Economics , UNICAMP.

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Evolution of Patenting in GMOs and Innovation Appropriability : Implications for Agriculture

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  1. Evolution of Patenting in GMOs and Innovation Appropriability: Implications for Agriculture • Maria Ester Dal-Poz.-Faculty, School of Applied Sciences – University of Campinas – UNICAMP, • José Maria Jardim Ferreira da Silveira-Faculty, Institute of Economics, UNICAMP. • ViniciusEduardo Ferrari.-Ph.D. Candidate, Institute of Economics– UNICAMP • Fabio Kenji Masago-Researcher, M.Sc. Institute of Computer Sciences,– UNICAMP. • Paper presented at the 17th ICABR Conference • “Innovation and Policy for the Bioeconomy” • Ravello (Italy): June 18 - 21, 2013

  2. Goals and some hypothesis • Mapping the technological trajectories on transgenic plants (TTP, from now on) applying a methodology based on network analysis.; • identify firms and the strategies conducted in the environment of agriculture innovation systems (FUGLIE;SCHIMMELPFENING, 2010); • TTPs identified by the methodology are related to the building of mechanisms of technological appropriability(DOSI, 1982); • The firms that achieve successful strategies – a complex combination of the building of intangible complementary assets, protected by patenting, and a strong focus on market – have had gain market share, causing huge impacts of seed industry all over the world. (MOSCHINI;YEROKIN, 2007; MOSCHINI, 2010; LOPEZ, 2009).

  3. Methodology : steps Step 1: Building the Network: Odissey’s robot (, OPCS, by Masago, 2013), based on complex queries; Main Network Indicators: a) number of patents from the search; density; b) k-neighbors by citation of the patents from the search; c) in-degree: frequency; Setp 2 Applying the HCHC criteria(high cited high connected): k-core-20, to build a sub-network of patents connected with at least degree 20 (Batagelj, 2003); Step 3 Identifying Patents with high in-degree (cited patents) with a strong path. Indicators: geodesicaldistance 1, higher centrality degrees and proximity prestige indicators in a directed network; Step 4 Back to the Step 1, load the ThomsonInnovation (trade mark) with the same patents to build the Themescape: patent lexicographical landscapes. Refining trajectories based on Themescape: plotting patents from Step 3 on themescape' maps: crossing patents, subjects and firms to identify competences and domains. (see Jackson, 2009; Goyal, 2006)

  4. Search strategy: queries by selected promoters • Network map: built by Patents from the search plus patents that are identified because they cited those patents from the search (derived patents); • Initially search only on USPTO (patents granted); Derwent World Patent Index at the end the steps to refine the understanding of the technological trajectory. • Patents with the key-words: 559 • Derived patents: 2106 • Number of vertex: 2665 • Number of Arcs: 9756 • Network density: 0,0013741696668525937 (1/1000 connections are done)

  5. The challenge: identifytrajectoriesfromthe original network

  6. ReturnedPatents (withthekey-words) byyear:

  7. The full network analysis • Shows the 1990’s increasing efforts on GMOs leading to a intense patenting activity; • From the 2000’: patenting activities declining, but M&A are intense involving firms that had patented in the 90’s; • There is a changing in the nature of the patents in the 2000: they cited patents whose content is related to "enabling technologies" , but they were closely related to Plant breeders rights; • (seeGraff, ZilbermanandBenett, 2010, in Plant Science)

  8. Sub-network with k-core 20: a thick net • Vertex: 37 • Arcs: 438 • Density: 0.32882883 • Average degree: 23.67567568 (forcefully over 20) • Índices: • • Betweenness Centralization: 0,01512346 (very high) • • All Closeness Centralization: 0,23007190 • • See I the next slide, the timeline (red, returned patents; green, derived)

  9. 1990 1991 1996 1998 1999 2000 2001 2002 2004 2005 2006 2009 2010 1993 1994 1992

  10. Results from the k-core 20 net • High density indicators : mature technology; • There is a group of central patents strongly connected; • Closeness Indicators: the main patents are close in the sub- network and in the original (correspondence) ; • The main returned patents (with key-words) were from the nineties; • Main “enabling technologies”: insertion of genes, vectors of expression, plasmids, promoters, anti-sense, aiming HT, DR, Protein enrichment were protected during the 90-99 period (filled and granted during this period). • From the year 2000 to 2012, the majority are derived patents (with no key-words) • Patents to protect GMO Maize Varieties (closer to the final market).

  11. 1990 1991 1996 1999 2000 2002 2006 2009 1993 1994 1992 Dekalb Dekalb Dekalb Calgene Monsanto Monsanto Dekalb Monsanto Monsanto Dekalb Commonwealth & Lubrizol Dekalb Dekalb RockefellerUniv Other Inventors Jefferson Richard

  12. Refining TT: using themescape • Graphic images (final steps of the methodology • Legend: • Green bullets: returned patents (with key-words) • Circles: technology clusters

  13. Promoters CaMV 35S; 35S OR ubiquitin Glyphosate-resistantplants 4940835 5110732 5188642 5352605 5034322 7064248 7615685 6399861 6025545 5550318 5290924 5268463 5001060 5188958 5874265 5919675

  14. 1990 1991 1996 1999 2000 2002 2006 2009 1993 1994 1992 Dekalb Dekalb Dekalb Calgene Monsanto Monsanto Dekalb Monsanto Monsanto Dekalb Commonwealth & Lubrizol Dekalb Dekalb RockefellerUniv Other Inventors Jefferson Richard

  15. Refining TT • Cluster A: Dna Transcription and expression of genes and processes • Cluster B: Stability and fertility related to TH (RR Soy) • Clusters C and D: Dna promoters: linked to A, because a genetic modified organism must be fertile and stable to generate a GMO variety. • There is a cross citing activity between trajectories • Bt genes are not dominant in the net. It means that these technologies rely on the enabling technologies, aiming the seed market diversification. • .

  16. Schumpeterian Technologies: innovation and market power (Mark II?) • Patents related to the Enabling Technologies (4940835; 5352605; 5034322; 5001060) show the higher index of closeness of the network; • Patent 5554798: First GM Corn, 1996, cites the “key enabling patents”‘ and has been cited by GM corn patents from this year on; • They are close to the patents of GM cultivars, granted recently to the leading companies (geodesic distance 1); • From economic point of view, these linkages reveals deterrence in the GM seed market; (Tirole, 1988). • . (seealsoDasguptaand Stiglitz, 1980)

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