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Crowdsourcing Genomics: Exploring Precision FDA

13 Pages Posted: 14 Aug 2017  

Jordan Paradise

Loyola University Chicago School of Law

Date Written: August 11, 2017

Abstract

Times and technologies are a changin’ in the era of precision medicine. In May 2017, the U.S. Food and Drug Administration (FDA) approved the first cancer treatment based on a genetic biomarker rather than the tissue of origin. One month later, the agency approved a companion diagnostic panel that utilizes next generation sequencing (NGS) to simultaneously screen a genetic sample for 23 cancer genes, three of which have FDA-approved therapies for non-small cell lung cancer. Together, these developments represent a “seismic shift” in the field of oncology and illustrate the tremendous promise for medicine facilitated by NGS. However, innovative NGS research and data-sharing models depart in significant ways from traditional research and development relationships in the life sciences, potentially raising a host of novel legal questions.

NGS is getting cheaper and easier, yet generates an overwhelming amount of genomic information. Current NGS technologies utilize various emerging high-throughput platforms to sequence millions of small DNA fragments in parallel rather than relying on conventional DNA sequencing methods. Once sequenced, bioinformatics analyses enable the fragments to be mapped onto a reference human genome, flagging unexpected variations in DNA, often called genetic variants. Today, an entire individual genome can be sequenced using NGS for about $1,000, compared to over $10 million in 2008. As for time, what can now be done in one day took over a decade to accomplish with previous Sanger biochemistry sequencing. While the immense reduction in cost and time is impressive, experts caution that the large amount of genetic variants identified using NGS “will not always be targets for particular disease.” In fact, “[t]he sheer magnitude of the information that we’ll find on the genetic and molecular level is going to far surpass our capacity to run clinical trials.” In order to generate robust evidence linking NGS-identified genetic variants and related biomarkers to disease, and to therapeutic efficacy and drug response, there is much work to be done.

Medical research, and cancer research specifically, has recently embraced open-source, crowdsourcing models to address and solve the NGS research challenges by tapping into “the collective wisdom and resources of the scientific community.” One example is Asymmetrex’s crowdsourcing campaign initiated in April 2015, targeted at cell biologists, tissue engineers, and regenerative medicine physicians. The company used social media to announce the project and ultimately share its histone variant H2A biomarker, called H2A.Z asymmetry, with qualified respondents. In exchange, respondents agreed to test the new biomarker tool to identify and count stem cells and report back with findings and data points. The goal was to generate the information quicker and cheaper, possibly with an eye on eventual approval and marketing of the technology. At the very least, the initiative contributed to the company’s patent-protected intellectual property portfolio relating to the H2A biomarker.

Industry is not the only source of crowdsourcing for genomic inquiry and exploration. Academic medical institutions, research consortia, patient advocacy groups, and others are creating crowdsourcing platforms based on tools to detect, collect, and evaluate genetic and genomic information. Regulators are even getting into the NGS game – the FDA launched the online portal precisionFDA in December 2015, providing “a community platform for NGS assay evaluation and regulatory science exploration.” Deciphering information generated and published on this crowdsourced, cloud-based site may be integral to biomarker identification, industry standard setting, clinical trial development, and, ultimately, regulatory assessment and adaptability.

The growth of NGS crowdsourcing models necessarily means widespread collaborations of academic medical centers, researchers, patients and patient advocates, private foundations, medical product innovators, and regulators. Not all of which subscribe to the same norms and expectations in the sharing economy. Emerging questions surrounding the expansion of players facilitated by NGS crowdsourcing involve identification and management of complex conflicts of interest, proper incentive structures, access to and sharing of research samples and health information, inventorship status and patent rights, payments and contractual agreements, licensing terms, and eventual profit share. This article contributes to the conversation by exploring the precisionFDA online crowdsourcing platform in terms of: (A) use and functionality; and (B) legal disclaimers and terms. It then offers several modest reflections on the legal and regulatory implications.

Suggested Citation

Paradise, Jordan, Crowdsourcing Genomics: Exploring Precision FDA (August 11, 2017). Available at SSRN: https://ssrn.com/abstract=3017395

Jordan K. Paradise (Contact Author)

Loyola University Chicago School of Law ( email )

25 E. Pearson
Chicago, IL 60611
United States

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