Drug Repurposing using Deep Learning on Knowledge Graphs

May 26, 2021 04:25 PM (PT)

Download Slides

Discovering new drugs is a lengthy and expensive process. This means that finding new uses for existing drugs can help create new treatments in less time and with less time. The difficulty is in finding these potential new uses.

How do we find these undiscovered uses for existing drugs?

We can unify the available structured and unstructured data sets into a knowledge graph. This is done by fusing the structured data sets, and performing named entity extraction on the unstructured data sets. Once this is done, we can use deep learning techniques to predict latent relationships.

In this talk we will cover:

  • Building the knowledge graph
  • Predicting latent relationships
  • Using the latent relationships to repurpose existing drugs
In this session watch:
Alexander Thomas, Principal Data Scientist, Wisecube AI
Vishnu Vettrivel, Founder and CEO, Wisecube AI


Alexander Thomas

Alex Thomas is a principal data scientist at Wisecube. He's used natural language processing and machine learning with clinical data, identity data, employer and jobseeker data, and now biochemical...
Read more

Vishnu Vettrivel

Vishnu Vettrivel is the Founder and CTO of Wisecube, a startup focused on accelerating biomedical research using AI. He has decades of experience building Data platforms and teams in healthcare, fi...
Read more