Embracing Dynamic Models for Gene Drive Management. Issue 3 (March 2021)

• Record Type: Journal Article
• Authors: Golnar, Andrew J.; Ruell, Emily; Lloyd, Alun L.; Pepin, Kim M.
• Is Part Of: Trends in biotechnology. Volume 39:Issue 3(2021)
• Page Start: 211
• Page End: 214
• Publication Date: 2021-03
• Subjects: gene drive -- risk assessment -- regulation -- GMO -- population genetics -- decision-making -- uncertainty; Biotechnology -- Periodicals; Biochemical engineering -- Periodicals; Genetic engineering -- Periodicals; Industrial microbiology -- Periodicals; 660.605
• DOI: 10.1016/j.tibtech.2020.08.011
• Languages: English
• ISSNs: 0167-7799

Abstract

Abstract : Robust methods of predicting how gene drive systems will interact with ecosystems is essential for safe deployment of gene drive technology. We describe how quantitative tools can reduce risk uncertainty, streamline empirical research, guide risk management, and promote cross-sector collaboration throughout the process of gene drive technology development and implementation.