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Automating Predictive Toxicology Using ComptoxAI.

Joseph D Romano1,2, Yun Hao1, Jason H Moore3

  • 1Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.

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Summary
This summary is machine-generated.

ComptoxAI offers a novel graph-structured knowledge base for computational toxicology research. This AI-powered infrastructure rapidly answers complex toxicology questions, aiding researchers and public health officials.

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Area of Science:

  • Computational toxicology and artificial intelligence
  • Data infrastructure for predictive toxicology
  • Graph-structured knowledge bases

Background:

  • Predictive toxicology research requires advanced data infrastructure.
  • Existing technologies struggle with complex toxicological questions.
  • Computational and artificial intelligence (AI) approaches are emerging in toxicology.

Purpose of the Study:

  • To introduce and showcase ComptoxAI, a new data infrastructure for predictive toxicology.
  • To demonstrate the capabilities of ComptoxAI's graph-structured knowledge base through real-world use-cases.
  • To enable faster and more complex toxicological predictions.

Main Methods:

  • Development of a graph-structured knowledge base integrating diverse public databases.
  • Implementation of specialized modules: 'shortest path', 'expand network', and QSAR dataset generator.
  • Application of these modules to real-world toxicological problems.

Main Results:

  • Successfully identified mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease using the 'shortest path' module.
  • Identified communities linked to dioxin toxicity via the 'expand network' module.
  • Generated a quantitative structure-activity relationship (QSAR) dataset for predicting pregnane X receptor agonism in 4,021 pesticide ingredients.

Conclusions:

  • ComptoxAI's graph-structured knowledge base rapidly answers complex toxicology questions, surpassing previous technologies.
  • The toolkit facilitates prediction of toxicological unknowns and modes of action for various users.
  • ComptoxAI is a free, public, and open-source resource for advancing predictive toxicology research and public health.