Our team behind the scenes at SXSW | Building a Disease Specific Knowledge Base


In part two of our SXSW series, our team shows how we use AI and machine learning to better understand specific diseases - in this case, Glioblastoma (GBM), the most common and aggressive form of brain cancer.

Given the complexity of a savage disease like GBM, a scientist alone could not read up on all the research that has been done to understand it. At BenevolentAI, we have developed a biomedical knowledge base to contextualise all the relevant information and relationships between diseases, genes, drugs and other important research that has already been published.

Our knowledge graph pulls out all the relevant links to ongoing and completed clinical trials, existing compounds that have been tested against the disease, and the underlying biological connections known to be associated with the disease. Together, these biological facts represent all that is known to be true about a disease today. 

Our technology platform helps us understand diseases like GBM by sitting on top of this knowledge base and answering two fundamental questions, i) what do we know about the disease today? and ii) where are the gaps in that knowledge base?


Watch our team demonstrate how algorithms can analyse this knowledge and reason across it to provide scientists and researchers with capabilities beyond human insight.


Up next

Target Identification, Literature Knowledge Inference