Dual use of artificial-intelligence-powered drug discovery

  title={Dual use of artificial-intelligence-powered drug discovery},
  author={Fabio L. Urbina and Filippa Lentzos and C{\'e}dric Invernizzi and Sean Ekins},
  journal={Nature Machine Intelligence},
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… 
The perils of machine learning in designing new chemicals and materials
[...]the need is obvious when you consider that less than 1% of the chemicals registered for commercial use in the United States have undergone toxicity characterization, whether they are used for
Perspective: The Rapidly Expanding Need for Biosecurity by Design
Here, features of “Biosecurity by Design” approaches are described, including the application of risk/benefit analysis and risk mitigation, post-COVID opportunities, and ethical global norms in the progression of biodesign and growing bioeconomies.
Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design
This work proposes a hierarchical latent distribution to enhance one of the most successful deep learning models, the Transformer, to accommodate ambiguities and data distributions and demonstrates its generative capabilities on property-based molecule design, outperforming existing work.
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder
The ultimate goal of various fields is to directly generate molecules with desired properties, such as water-soluble molecules in drug development and molecules suitable for organic light-emitting
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
SignNet and BasisNet are introduced — new neural architectures that are invariant to all requisite symmetries and hence process collections of eigenspaces in a principled manner and can approximate any continuous function of eigenvectors with the proper invariances.
Neural Implicit Manifold Learning for Topology-Aware Generative Modelling
Constrained energy-based models are introduced, which use a constrained variant of Langevin dynamics to train and sample within a learned manifold and can learn manifold-supported distributions with complex topologies more accurately than pushforward models.
Vorbereitung auf Anschläge mit hochtoxischen Substanzen im öffentlichen Raum
Der Einsatz von chemischen Stoffen in terroristischen Szenarien ist nach den bekannt gewordenen Ereignissen der letzten Jahre überall und insbesondere auch in der westlichen Welt zu befürchten. Zum
Current and Near-Term AI as a Potential Existential Risk Factor
This paper problematise the notion that current and near-term artificial intelligence technologies have the potential to contribute to existential risk by acting as intermediate risk factors, and that this potential is not limited to the unaligned AGI scenario.
Dual Use
  • M. Wildner
  • Medicine
    Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
  • 2022


REINVENT 2.0: An AI Tool for De Novo Drug Design
This application note aims to offer the community a production-ready tool for de novo design, called REINVENT, which can be effectively applied on drug discovery projects that are striving to resolve either exploration or exploitation problems while navigating the chemical space.
The ToxCast program for prioritizing toxicity testing of environmental chemicals.
The ToxCast program will evaluate chemical properties and bioactivity profiles across a broad spectrum of data domains: physical-chemical, predicted biological activities based on existing structure-activity models, biochemical properties based on HTS Assays, cell-based phenotypic assays, and genomic and metabolomic analyses of cells.
Institutionalising Ethics in AI through Broader Impact Requirements
In this Perspective, a governance initiative by one of the world’s largest AI conferences is reflected on and insights are gained regarding effective community-based governance and the role and responsibility of the AI research community more broadly.
A robotic platform for flow synthesis of organic compounds informed by AI planning
An approach toward automated, scalable synthesis that combines techniques in artificial intelligence (AI) for planning and robotics for execution is described, representing a milestone on the path toward fully autonomous chemical synthesis.
Organisation for the Prohibition of Chemical Weapons. The Hague Ethical Guidelines
  • 2021
The New Yorker https://www.newyorker.com/tech/ annals-of-technology/who-should-stop-unethical-ai (2021)
  • 2021
Spiez Convergence Conference
  • Environ . Health Perspect .
  • 2021