IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03976-5.html
   My bibliography  Save this article

Reducing potential dual-use risks in synthetic biology laboratory research: a dynamic model of analysis

Author

Listed:
  • Xi Zhang

    (Tianjin University
    Tianjin University)

  • Te Zhang

    (Tianjin University)

  • Xin Wei

    (Tianjin University
    Communication University of China)

  • Zhanpeng Xiao

    (Tianjin University)

  • Weiwen Zhang

    (Tianjin University
    Tianjin University
    Tianjin University
    Collaborative Innovation Center of Chemical Science and Engineering)

Abstract

Synthetic biology (SynBio) is an interdisciplinary field that includes biology, genomics, engineering, and informatics. The introduction of machine learning technology reduces the requirement for human participation in SynBio research, which may lead to increased biosafety and biosecurity concerns within the complex human–technology-management system in SynBio laboratories compared with traditional biology. The rapid development of SynBio and machine learning technology has added to the systemic complexity of management and technology subsystems, the risks of which remain unclear. To fully understand and address these risks, there is an urgent need to develop a quantitative model. In this study, three-round Delphi interviews were conducted with SynBio experts who have published articles in top journals (e.g., Nature, Science, Cell, etc.) and applied the system dynamics method to build a quantitative analysis model. The model explores the potential risk factors and their complex relationships in the SynBio research. We analyzed three subsystems (biotechnology, information technology, and management), identifying seven key risk factors. Among these, the Average Experience of Newcomers and Tolerable Error Frequency play an essential role in laboratory management. Notably, the biosafety atmosphere has the greatest impact on reducing error rate and increasing safety awareness, as well as on the infrastructure safety of SynBio laboratory. In addition, we also consider the impact of the progressiveness of machine learning in the SynBio research and find that using more advanced machine learning technology leads to lower instrument safety. This study provides a framework for quantifying potential risk factors in SynBio research and lays a theoretical foundation for future laboratory safety management and the development of a global code of conduct for interdisciplinary scientists.

Suggested Citation

  • Xi Zhang & Te Zhang & Xin Wei & Zhanpeng Xiao & Weiwen Zhang, 2024. "Reducing potential dual-use risks in synthetic biology laboratory research: a dynamic model of analysis," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03976-5
    DOI: 10.1057/s41599-024-03976-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03976-5
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-024-03976-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kirsten Martin, 2019. "Ethical Implications and Accountability of Algorithms," Journal of Business Ethics, Springer, vol. 160(4), pages 835-850, December.
    2. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    3. Bin Long & Bart Fischer & Yining Zeng & Zoe Amerigian & Qiang Li & Henry Bryant & Man Li & Susie Y. Dai & Joshua S. Yuan, 2022. "Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Fenling Feng & Chengguang Liu & Jiaqi Zhang, 2020. "China's Railway Transportation Safety Regulation System Based on Evolutionary Game Theory and System Dynamics," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1944-1966, October.
    5. Emmanuel Garbolino & Jean‐Pierre Chery & Franck Guarnieri, 2016. "A Simplified Approach to Risk Assessment Based on System Dynamics: An Industrial Case Study," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 16-29, January.
    6. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    7. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    8. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    9. Tran Thao & Fabien Labroussaa & Nadine Ebert & Philip V’kovski & Hanspeter Stalder & Jasmine Portmann & Jenna Kelly & Silvio Steiner & Melle Holwerda & Annika Kratzel & Mitra Gultom & Kimberly Schmied, 2020. "Rapid reconstruction of SARS-CoV-2 using a synthetic genomics platform," Nature, Nature, vol. 582(7813), pages 561-565, June.
    10. Shu Zhang & Xinyu Hua & Ganghai Huang & Xiuzhi Shi & Dandan Li, 2022. "What Influences Miners’ Safety Risk Perception?," IJERPH, MDPI, vol. 19(7), pages 1-14, March.
    11. Lei Pei & Michele Garfinkel & Markus Schmidt, 2022. "Bottlenecks and opportunities for synthetic biology biosafety standards," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
    12. Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2020. "Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1258-1278, June.
    13. Fankang Meng & Tom Ellis, 2020. "The second decade of synthetic biology: 2010–2020," Nature Communications, Nature, vol. 11(1), pages 1-4, December.
    14. Laihao Ma & Xiaoxue Ma & Jingwen Zhang & Qing Yang & Kai Wei, 2021. "A Methodology for Dynamic Assessment of Laboratory Safety by SEM-SD," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    15. Tijana Radivojević & Zak Costello & Kenneth Workman & Hector Garcia Martin, 2020. "A machine learning Automated Recommendation Tool for synthetic biology," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    16. Benjamin Burger & Phillip M. Maffettone & Vladimir V. Gusev & Catherine M. Aitchison & Yang Bai & Xiaoyan Wang & Xiaobo Li & Ben M. Alston & Buyi Li & Rob Clowes & Nicola Rankin & Brandon Harris & Rei, 2020. "A mobile robotic chemist," Nature, Nature, vol. 583(7815), pages 237-241, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Frevel, Nicolas & Beiderbeck, Daniel & Schmidt, Sascha L., 2022. "The impact of technology on sports – A prospective study," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    2. Singh, Saurabh & Morya, Raj & Jaiswal, Durgesh Kumar & Keerthana, S. & Kim, Sang-Hyoun & Manimekalai, R. & Prudêncio de Araujo Pereira, Arthur & Verma, Jay Prakash, 2024. "Innovations and advances in enzymatic deconstruction of biomass and their sustainability analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    3. Qianxiang Zhu & Yuanqing Qin & Chunjie Zhou & Weiwei Gao, 2018. "Extended multilevel flow model-based dynamic risk assessment for cybersecurity protection in industrial production systems," International Journal of Distributed Sensor Networks, , vol. 14(6), pages 15501477187, June.
    4. Peppel, Marcel & Ringbeck, Jürgen & Spinler, Stefan, 2022. "How will last-mile delivery be shaped in 2040? A Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    5. Shoukohyar, Sajjad & Seddigh, Mohammad Reza, 2020. "Uncovering the dark and bright sides of implementing collaborative forecasting throughout sustainable supply chains: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    6. Beiderbeck, Daniel & Evans, Nicolas & Frevel, Nicolas & Schmidt, Sascha L., 2023. "The impact of technology on the future of football – A global Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    7. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    8. Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2020. "Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 818-841, April.
    9. Niyi Ogunbiyi & Artie Basukoski & Thierry Chaussalet, 2021. "An Exploration of Ethical Decision Making with Intelligence Augmentation," Social Sciences, MDPI, vol. 10(2), pages 1-14, February.
    10. Gundula Glowka & Andreas Kallmünzer & Anita Zehrer, 2021. "Enterprise risk management in small and medium family enterprises: the role of family involvement and CEO tenure," International Entrepreneurship and Management Journal, Springer, vol. 17(3), pages 1213-1231, September.
    11. Ali Zackery & Joseph Amankwah-Amoah & Zahra Heidari Darani & Shiva Ghasemi, 2022. "COVID-19 Research in Business and Management: A Review and Future Research Agenda," Sustainability, MDPI, vol. 14(16), pages 1-32, August.
    12. Benischke, Mirko H. & Guldiken, Orhun & Doh, Jonathan P. & Martin, Geoffrey & Zhang, Yanze, 2022. "Towards a behavioral theory of MNC response to political risk and uncertainty: The role of CEO wealth at risk," Journal of World Business, Elsevier, vol. 57(1).
    13. Jinyi Hu, 2023. "Linguistic Multiple-Attribute Decision Making Based on Regret Theory and Minimax-DEA," Mathematics, MDPI, vol. 11(20), pages 1-14, October.
    14. Krista M. Milich & Natalie Fisher & Gisela Sobral, 2024. "Effective public health messaging for university students: lessons learned to increase adherence to safety guidelines during a pandemic," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    15. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    16. Saurabh Pratap & Sunil Kumar Jauhar & Yash Daultani & Sanjoy Kumar Paul, 2023. "Benchmarking sustainable E‐commerce enterprises based on evolving customer expectations amidst COVID‐19 pandemic," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 736-752, January.
    17. Mohammad Ali Yamin, 2021. "Investigating the Drivers of Supply Chain Resilience in the Wake of the COVID-19 Pandemic: Empirical Evidence from an Emerging Economy," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    18. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    19. Laihao Ma & Xiaoxue Ma & Jingwen Zhang & Qing Yang & Kai Wei, 2021. "Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China," IJERPH, MDPI, vol. 18(13), pages 1-17, July.
    20. Patricia A. Norberg & Daniel R. Horne, 2024. "When the bridge is not human: Algorithmic interference in forming social relationships through the manipulation of weak ties," Journal of Consumer Affairs, Wiley Blackwell, vol. 58(2), pages 606-629, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03976-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.