Peer Production and Industrial Cooperation in Biotechnology, Genomics and Proteomics
Summary from the Industrial Cooperation Project:
"The Biotechnology - Genomic and Proteomics sector has enormous potential implications for global health and food security; has well developed variability in practices, with some of the most proprietary alongside some of the most open and collaborative efforts. It therefore is a substantively important area and a potential model for our analysis more broadly. See the BGP Synthesis here and working papers here." (http://cyber.law.harvard.edu/commonsbasedresearch/Biotechnology_-_Genomic_and_Proteomics)
More examples available at Genomic Data Commons:
- External Link: Human Genome Project, http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml
o Products: Data and Tools. Genome sequence available publicly o Governance: funded through the NIH o Comment: Another interesting instance of the commons - the government used the power of funding to mandate open access requirements from the organizations which participated.
- External Link: HapMap, http://www.hapmap.org/
o Products: Data. Coordination between researchers in Canada, China, Japan, Nigeria, United Kingdom and the United States to identify disease-causing genes. Data released into the public domain o Governance: Combination of both public and private organizations (http://www.hapmap.org/groups.html) o Another good instance of commons-based production
- Products: Data. Open consortium to identify all functional elements of the human genome. Data is made publicly available
- Governance: Part of the NIH
- Comment: Perfect instance of commons-based production.
"Inside Biotechnology - Genomics and Proteomics, we found a mixture of commons-based production and more traditional, closed practices depending on the point in the value chain where we looked.
The fields of genomics and proteomics represent a rich research base for an analysis of cooperative behavior and commons-based knowledge generation - there are long-established actors, projects, and cooperative systems, covering most of the classes of products produced by biotech, and across a wide range of tools and knowledge. There is massive investment by public and private players across the research cycle, ranging from fundamental “big science” projects where data is treated as infrastructure to intermediate “translational research” where the basic discoveries are converted to potentially useful health interventions, to marketable products like genetic therapies and diagnostic kits.
“Big science” projects show the most evidence of commons-based effects on industry. The emergence of a commons in “big science genomics” is easiest to see in basic genome sequencing. Via the Human Genome Project (the genome common to all humans), the HapMap (a mapping of the genomic variation that makes us unique individuals), and follow-on projects, big government investments and accompanying public domain rules dramatically affected the industry of genomics, leading to the eventual exit from the market of corporate players like Celera from the business of selling genome databases. The commons in gene sequences also sparked the emergence of commons-based production in functional genome annotation, where the Distributed Annotation System allows for individual observations about the functions of specific gene sequences on disparate computers “snap together” to form a cohesive, parallel-generated view of genomic function.
Most big science happens through government investment in university and its outputs in the data and text products are now open by default (due to the Bermuda Rules and the NIH Public Access Policy), although tools and inventions frequently are subjected to competitive withholding and patenting. We did not observe significant evidence of commons-based industrial disruption in biological materials, research tools, although the Personal Genome Project and the efforts of private foundations investing in disease-specific research as well as a new set of technology transfer “principles” for licensing may create the conditions for such disruption in coming years. The iBridge Network by the Kauffman Foundation is also trying to disrupt the technology transfer market via an e-commerce model, though it is not explicitly a commons-based approach and instead simply focuses on lower transaction costs and increased transparency.
“Translational research” has traditionally been the province of biotechnology startups funded by venture capital, placing a high value on patents and trade secrets and thus has been resistant to commons effects as an industry. There are attempts to create “open source drug discovery” as seen in India, but most of those successes are actually more similar to big science - genotyping organisms versus identifying potential drug targets or potential drug interventions.
However, research on the translational research industry itself indicates not only that the industry is failing under its existing business models but provide tantalizing clues that a commons may be a viable approach: the only factors that correlate to an increase in the rates of drug discovery are those related to the total number of searchers. This research comes at the same time that new, non-profit entities like Sage Bionetworks are moving into the domains traditionally dominated by companies in the industry, explicitly adopting commons-based approaches. Sage is not performing research in order to generate IP, instead performing competitive translational research like target prioritization, drug response stratification, and even clinical studies under a business model in which the “profit” is the right to deposit data and outcomes into a digital commons, and marks a truly disruptive “port” of the commons model into the genomics industrial paradigm.
- ICP Synthesis, http://cyber.law.harvard.edu/commonsbasedresearch/ICP_Sectors
- ICP Working Papers, http://cyber.law.harvard.edu/commonsbasedresearch/ICP_Reports_and_Working_Papers
- Commons based cases in BGP, http://cyber.law.harvard.edu/commonsbasedresearch/Commons_based_cases_in_BGP