Understanding Featurization in Machine Learning for Genetic Analysis

Today we’re joined by Kim Branson, the SVP and global head of artificial intelligence and machine learning at GSK. 

We cover a lot of ground in our conversation, starting with a breakdown of GSK’s core pharmaceutical business, and how ML/AI fits into that equation, use cases that appear using genetics data as a data source, including sequential learning for drug discovery. We also explore the 500 billion node knowledge graph Kim’s team built to mine scientific literature, and their “AI Hub”, the ML/AI infrastructure team that handles all tooling and engineering problems within their organization. Finally, we explore their recent cancer research collaboration with King’s College, which is tasked with understanding the individualized needs of high- and low-risk cancer patients using ML/AI amongst other technologies. 

The complete show notes for this episode can be found at twimlai.com/go/536.