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Brenda M. Simon, "The Pathologies of Biomedical ‘Data-Generating’ Patents: Leveraging Intellectual Property and Big Data to Extend Market Power"

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Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.

This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.

The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.

Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.

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Brenda M. Simon, "The Pathologies of Biomedical ‘Data-Generating’ Patents: Leveraging Intellectual Property and Big Data to Extend Market Power"

  1. 1. Data-Generating Patents [forthcoming 111 NORTHWESTERN LAW REVIEW __ (2017)] Brenda M. Simon Associate Professor, TJSL Non-Resident Fellow, Stanford Law School Ted Sichelman Professor, USD Law May 6, 2016
  2. 2. — Data-Generating Patents: — Patented inventions that by design generate valuable data by their operation or use.
  3. 3. Overview — The Phenomenon of Data Generating Patents and Their Legal and Economic Effects — Discerning the Problematic from the Unproblematic — Recommendations 3
  4. 4. Trade Secrets and Patents — Substitution Theory — Economic Complements 4
  5. 5. Data-Generating Patents — Patented inventions that by design generate valuable data by their operation or use. — Examples 5
  6. 6. Possible Concerns — Patent principles are in an uneasy tension with protecting this type of data — Effects on limiting disclosure — Innovation balance possibly altered 6
  7. 7. Possible Concerns — Traditional trade secret safeguards generally do not apply to data generated from patented inventions — Reverse engineering restricted — Independent discovery limited 7
  8. 8. Possible Concerns — Data-generating patents may be leveraged to provide additional market power in the generation of trade secrets — Is there a need for additional legal protection to incentivize the production of this kind of information? 8
  9. 9. Discerning Problematic from Unproblematic Data-Generating Inventions — Use of data in unforeseeable markets — Preemptive effect on marketplace competition for the data 9
  10. 10. Discerning Problematic from Unproblematic Data-Generating Inventions — Unforeseeable Data Markets: — Examines whether the patent provides the ability to use data in an area that is not directly related to the market covered by the patented invention — The greater the extent to which the invention allows for use of data in unforeseeable markets, the more likely the invention is problematic 10
  11. 11. Discerning Problematic from Unproblematic Data-Generating Inventions — Data Market Preemption: — Examines the effect on competition in the market for the data — not the preemptive effect of the invention itself — The greater the preemptive effect on marketplace competition related to the data, the more likely the invention is problematic 11
  12. 12. Scenario 3 Likely Unproblematic Scenario 2 Very Likely Problematic Data Market Preemption Scenario 1 Likely Problematic Scenario 4 Very Likely Unproblematic Discerning Problematic from Unproblematic Data-Generating Inventions
  13. 13. Proposals to Address Problematic Data- Generating Patents — Innovation-related concerns — Disclosure-related concerns — No ideal solution, but ex post generally preferable to ex ante 13
  14. 14. Discussion — brendamsimon(at)gmail.com — tsichelman(at)sandiego.edu 14

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