Project Rephetio & systematic prediction of antiepileptic drugs

Presented on January 30, 2017 to Blackfynn by

  • Daniel Himmelstein
  • Pouya Khankhanian

Slides online at

  • Hetnet of biology designed for drug repurposing
  • ~50 thousand nodes
    11 types (labels)
  • ~2.25 million relationships
    24 types
  • integrates 29 public resources
    knowledge from millions of studies
  • the hardest part:
    licensing of publicly available data

Hetionet v1.0

Visualizing Hetionet v1.0

Future: all biomedical knowledge in a single network

  • Teach computers how to read the literature and extract knowledge.
  • Continuously and automatically refine and grow the hetnet.
  • Free from any legal restrictions on reuse. 

Project Rephetio: drug repurposing predictions

  • Hetionet v1.0 contains:
    • 1,538 connected compounds
    • 136 connected diseases
    • 209,168 compound–disease pairs
    • 755 treatments
  • 1,206 compound–disease metapaths with length ≤ 4
  • machine learning classifier
  • predict the probability of treatment for all 209,168 compound–disease pairs (
  • Project online at

Systematic integration of biomedical knowledge prioritizes drugs for repurposing
Daniel S Himmelstein, Antoine Lizee, Christine Hessler, Leo Brueggeman, Sabrina L Chen, Dexter Hadley, Ari Green, Pouya Khankhanian, Sergio E Baranzini
bioRxiv. 2016. DOI: 10.1101/087619

Does bupropion treat nicotine dependence?

  • Bupropion was first approved for depression in 1985
  • In 1997, bupropion was approved for smoking cessation
  • Can we predict this repurposing from Hetionet? The prediction was:





Epilepsy predictions

(browse all predictions at

Discuss at

Evaluating the top 100 epilepsy predictions

Which target genes supported the top epilepsy predictions?

Online at

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To Blackfynn: predicting antiepileptic drugs in Project Rephetio

By Daniel Himmelstein

To Blackfynn: predicting antiepileptic drugs in Project Rephetio

Presentation to Blackfynn in Philadelphia on Monday, January 30, 2017.

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