Dual use of artificial-intelligence-powered drug discovery – Nature.com

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.
Nature Machine Intelligence (2022)
16 Altmetric
Metrics details
An international security conference explored how artificial intelligence (AI) technologies for drug discovery could be misused for de novo design of biochemical weapons. A thought experiment evolved into a computational proof.
The Swiss Federal Institute for NBC (nuclear, biological and chemical) Protection —Spiez Laboratory— convenes the ‘convergence’ conference series1 set up by the Swiss government to identify developments in chemistry, biology and enabling technologies that may have implications for the Chemical and Biological Weapons Conventions. Meeting every two years, the conferences bring together an international group of scientific and disarmament experts to explore the current state of the art in the chemical and biological fields and their trajectories, to think through potential security implications and to consider how these implications can most effectively be managed internationally. The meeting convenes for three days of discussion on the possibilities of harm, should the intent be there, from cutting-edge chemical and biological technologies. Our drug discovery company received an invitation to contribute a presentation on how AI technologies for drug discovery could potentially be misused.
This is a preview of subscription content

Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals

Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Spiez Convergence Conference https://www.spiezlab.admin.ch/en/home/meta/refconvergence.html (2021).
Urbina, F., Lowden, C. T., Culberson, J. C. & Ekins, S. https://doi.org/10.33774/chemrxiv-2021-nlwvs (2021).
Mansouri, K. et al. Environ. Health Perspect. 129, 047013 (2021).
Article  Google Scholar 
Blaschke, T. et al. J. Chem. Inf. Model. 60, 5918–5922 (2020).
Article  Google Scholar 
National Research Council Committee on Toxicology. https://www.ncbi.nlm.nih.gov/books/NBK233724/ (National Academies Press, 1997).
Aroniadou-Anderjaska, V., Apland, J. P., Figueiredo, T. H., De Araujo Furtado, M. & Braga, M. F. Neuropharmacology 181, 108298 (2020).
Article  Google Scholar 
Genheden, S. et al. J. Cheminform. 12, 70 (2020).
Article  Google Scholar 
Coley, C. W. et al. Science 365, eaax1566 (2019).
Article  Google Scholar 
Dix, D. J. et al. Toxicol. Sci. 95, 5–12 (2007).
Article  Google Scholar 
Hutson, M. The New Yorker https://www.newyorker.com/tech/annals-of-technology/who-should-stop-unethical-ai (2021).
Brown, T. B. et al. Preprint at arXiv https://arxiv.org/abs/2005.14165 (2020).
Prunkl, C. E. A. et al. Nat. Mach. Intell. 3, 104–110 (2021).
Article  Google Scholar 
Organisation for the Prohibition of Chemical Weapons. The Hague Ethical Guidelines https://www.opcw.org/hague-ethical-guidelines (2021).
Download references
We are grateful to the organizers and participants of the Spiez Convergence conference 2021 for their feedback and questions. C.I. contributed to this article in his personal capacity. The views expressed in this article are those of the authors only and do not necessarily represent the position or opinion of Spiez Laboratory or the Swiss Government. We kindly acknowledge US National Institutes of Health funding under grant R44GM122196-02A1 from the National Institute of General Medical Sciences and 1R43ES031038-01 and 1R43ES033855-01 from the National Institute of Environmental Health Sciences for our machine learning software development and applications. Research reported in this publication was supported by the National Institute of Environmental Health Sciences of the National Institutes of Health under grants R43ES031038 and 1R43ES033855-01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Collaborations Pharmaceuticals, Inc., Raleigh, NC, USA
Fabio Urbina & Sean Ekins
Department of War Studies and Department of Global Health & Social Medicine, King’s College London, London, UK
Filippa Lentzos
Spiez Laboratory, Federal Department of Defence, Civil Protection and Sports, Spiez, Switzerland
Cédric Invernizzi
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
Correspondence to Sean Ekins.
F.U. and S.E. work for Collaborations Pharmaceuticals, Inc. F.L. and C.I. have no conflicts of interest.
Nature Machine Intelligence thanks Gisbert Schneider and Carina Prunkl for their contribution to the peer review of this work.
Reprints and Permissions
Urbina, F., Lentzos, F., Invernizzi, C. et al. Dual use of artificial-intelligence-powered drug discovery. Nat Mach Intell (2022). https://doi.org/10.1038/s42256-022-00465-9
Download citation
Published: 07 March 2022
DOI: https://doi.org/10.1038/s42256-022-00465-9
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Advanced search
Nature Machine Intelligence (Nat Mach Intell) ISSN 2522-5839 (online)
© 2022 Springer Nature Limited
Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.


Add a Comment

Your email address will not be published. Required fields are marked *