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https://doi.org/10.33540/1295...
Doctoral thesis . 2022 . Peer-reviewed
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Gene drive technologies: navigating the ethical landscape

Authors: Graeff, Nienke de;

Gene drive technologies: navigating the ethical landscape

Abstract

Gene drives are technologies that modify a particular genetic element in animals or insects so that this genetic element does not follow the typical rules of heredity, and is passed onto future generations with an increased likelihood. Gene drive technologies could be used to tackle intractable problems such as vector-borne diseases like malaria or the biodiversity impact of invasive species. At the same time, the development and governance of gene drives raise a range of ethical questions and concerns that warrant proactive ethical evaluation. In the PhD thesis ‘Gene drive technologies: navigating the ethical landscape’, Nienke de Graeff analyzes these questions and concerns. In Part I, she outlines the ‘ethical landscape’ of gene drive technologies by identifying the associated ethical challenges through literature review and empirical ethical research. Important challenges concern how the uncertainty and risks of these technologies should be navigated, whether it is morally permissible to intervene in nature in this way, and how the development, governance, and potential deployment of gene drive technologies should be guided. In Part II, De Graeff normatively analyzes various of these challenges and provides guidance to navigate them. In Part III, she stipulates recommendations for researchers and policymakers in the gene drive field as well as lessons learned for ethics parallel research as an approach for early ethical guidance of new and emerging technologies more generally.

Country
Netherlands
Related Organizations
Keywords

Bioethics; ethics; gene drives; genetic modification; biotechnology; governance

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green