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KG based Investigation of Drug Outcome Pairs

Tiffany J. Callahan edited this page Oct 5, 2022 · 2 revisions

Standardizing Knowledge of Drug Effects: An Application of PheKnowLator for Drug Safety


Systems pharmacology aims to describe the effects of a drug at the molecular level, by integrating data from multiple temporal and spatial scales across all levels of biological organization. These data are usually represented as a network or knowledge graph (KG), where nodes are biological entities (e.g., chemical compounds, proteins) and edges indicate relationships between these entities (e.g., interactions, drug-target affinity). Systems pharmacology models have successfully predicted drug side effects, developed precision therapeutics, and facilitated drug repurposing. While promising, the majority of these models focus on single entities providing an incomplete “biological milieu”, which may result in biased models and conclusions that are not biologically plausible.

The goal of the proposed work is to demonstrate how a PheKnowLator KG can be traversed and used to construct features capable of discriminating different kinds of drug-outcome pairs.

Running the Tutorial

Tutorial: Entity Search

In order to run the Entity Search you will need to download and run the

To work with the Notebook.

  • Fork this library:
  • If the notebook titled Entity_Search.ipynb and accompanying script are not in PheKnowLator/notebooks/tutorials/entity_search then download them from the links below to PheKnowLator/notebooks/tutorials/entity_search:
  • Start the Jupyter Notebook by typing jupyter notebook in the terminal from the PheKnowLator directory

Presentations and Related Resources

2022 OHDSI Symposium

A software demonstration presenting this information will be given at the 2022 Annual Observational Health Data Sciences and Informatics (OHDSI). For more information, including videos and a brief report describing the presented material, please see the OHDSI Symposium page dedicated to this project by clicking on the QR-code provided below.

OHDSI 10-Minute Tutorial

In 2022, we gave a 10-minute tutorial to the OHDSI Community. For more information, including links to access the video and slides, click here or watch the recorded tutorial below.

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