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Development of community of practice to support quantitative risk assessment for synthetic biology products: contaminant bioremediation and invasive carp control as cases

Author

Listed:
  • Benjamin D. Trump

    (ORISE
    US Army Engineer Research and Development Center, Environmental Laboratory)

  • Christy Foran

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Taylor Rycroft

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Matthew D. Wood

    (US Army Corps of Engineers, Engineer Research and Development Center
    Aptima, Inc.)

  • Nirzwan Bandolin

    (Office of the Secretary of Defense)

  • Mariana Cains

    (Indiana University Bloomington)

  • Timothy Cary

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Fiona Crocker

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Nicholas A. Friedenberg

    (Applied Biomathematics)

  • Patrick Gurian

    (Drexel University)

  • Kerry Hamilton

    (Arizona State University)

  • Jan Jeffrey Hoover

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Corey Meyer

    (Gryphon Scientific, LLC)

  • Kaytee Pokrzywinski

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Ryan Ritterson

    (Gryphon Scientific, LLC)

  • Paul Schulte

    (National Institute for Occupational Safety and Health)

  • Christopher Warner

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Edward Perkins

    (US Army Corps of Engineers, Engineer Research and Development Center)

  • Igor Linkov

    (US Army Corps of Engineers, Engineer Research and Development Center)

Abstract

Synthetic biology has the potential for a broad array of applications. However, realization of this potential is challenged by the paucity of relevant data for conventional risk assessment protocols, a limitation due to to the relative nascence of the field, as well as the poorly characterized and prioritized hazard, exposure, and dose–response considerations associated with the development and use of synthetic biology-derived organisms. Where quantitative risk assessment approaches are necessarily to fulfill regulatory requirements for review of products containing genetically modified organisms, this paper reviews one potential avenue for early-stage quantitative risk assessment for biosafety considerations of synthetic biology organism deployment into the environment. Building from discussion from a March 2018 US Army Engineer Research and Development Center workshop on developing such quantitative risk assessment for synthetic biology, this paper reviews the findings and discussion of workshop participants. This paper concludes that, while synthetic biology risk assessment and governance will continue to refine and develop in the coming years, a quantitative framework that builds from existing practice is one potentially beneficial option for risk assessors that must contend with the technology’s limited hazard characterization or exposure assessment considerations in the near term.

Suggested Citation

  • Benjamin D. Trump & Christy Foran & Taylor Rycroft & Matthew D. Wood & Nirzwan Bandolin & Mariana Cains & Timothy Cary & Fiona Crocker & Nicholas A. Friedenberg & Patrick Gurian & Kerry Hamilton & Jan, 2018. "Development of community of practice to support quantitative risk assessment for synthetic biology products: contaminant bioremediation and invasive carp control as cases," Environment Systems and Decisions, Springer, vol. 38(4), pages 517-527, December.
    • Handle: RePEc:spr:envsyd:v:38:y:2018:i:4:d:10.1007_s10669-018-9710-9
    DOI: 10.1007/s10669-018-9710-9
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    References listed on IDEAS

    as
    1. Trump, Benjamin D., 2017. "Synthetic biology regulation and governance: Lessons from TAPIC for the United States, European Union, and Singapore," Health Policy, Elsevier, vol. 121(11), pages 1139-1146.
    2. Zielinski, D.P. & Voller, VR. & Sorensen, P.W., 2018. "A physiologically inspired agent-based approach to model upstream passage of invasive fish at a lock-and-dam," Ecological Modelling, Elsevier, vol. 382(C), pages 18-32.
    3. Vrishali Subramanian & Elena Semenzin & Danail Hristozov & Esther Zondervan-van den Beuken & Igor Linkov & Antonio Marcomini, 2015. "Review of decision analytic tools for sustainable nanotechnology," Environment Systems and Decisions, Springer, vol. 35(1), pages 29-41, March.
    4. José Manuel Palma‐Oliveira & Benjamin D. Trump & Matthew D. Wood & Igor Linkov, 2018. "Community‐Driven Hypothesis Testing: A Solution for the Tragedy of the Anticommons," Risk Analysis, John Wiley & Sons, vol. 38(3), pages 620-634, March.
    5. Andreas Klinke & Ortwin Renn, 2012. "Adaptive and integrative governance on risk and uncertainty," Journal of Risk Research, Taylor & Francis Journals, vol. 15(3), pages 273-292, March.
    6. Igor Linkov & Benjamin D. Trump & Elke Anklam & David Berube & Patrick Boisseasu & Christopher Cummings & Scott Ferson & Marie-Valentine Florin & Bernard Goldstein & Danail Hristozov & Keld Alstrup Je, 2018. "Comparative, collaborative, and integrative risk governance for emerging technologies," Environment Systems and Decisions, Springer, vol. 38(2), pages 170-176, June.
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    Cited by:

    1. Zachary A. Collier & James H. Lambert & Igor Linkov, 2018. "Systems modeling techniques for data analysis, decision making, and risk governance," Environment Systems and Decisions, Springer, vol. 38(4), pages 431-432, December.

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