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