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Dual use of artificial-intelligence-powered drug discovery

Nature Machine Intelligence volume 4, pages 189–191 (2022)Cite this article

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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.

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Fig. 1: A t-SNE plot visualization of the LD50 dataset and top 2,000 MegaSyn AI-generated and predicted toxic molecules illustrating VX.

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Acknowledgements

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.

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Authors and Affiliations

  1. Collaborations Pharmaceuticals, Inc., Raleigh, NC, USA

    Fabio Urbina & Sean Ekins

  2. Department of War Studies and Department of Global Health & Social Medicine, King’s College London, London, UK

    Filippa Lentzos

  3. Spiez Laboratory, Federal Department of Defence, Civil Protection and Sports, Spiez, Switzerland

    Cédric Invernizzi

Authors
  1. Fabio Urbina
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  2. Filippa Lentzos
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  3. Cédric Invernizzi
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  4. Sean Ekins
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Corresponding author

Correspondence to Sean Ekins.

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Competing interests

F.U. and S.E. work for Collaborations Pharmaceuticals, Inc. F.L. and C.I. have no conflicts of interest.

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Nature Machine Intelligence thanks Gisbert Schneider and Carina Prunkl for their contribution to the peer review of this work.

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Urbina, F., Lentzos, F., Invernizzi, C. et al. Dual use of artificial-intelligence-powered drug discovery. Nat Mach Intell 4, 189–191 (2022). https://doi.org/10.1038/s42256-022-00465-9

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