Talk @ ISWC 2022

I had the pleasure to contribute to the ISWC 2022 conference through a sponsored talk on on Driving Scientific Discovery with Knowledge Graphs and AI in Life Sciences in the Industry track.

Driving Scientific Discovery with Knowledge Graphs and AI in Life Sciences

Thom Pijnenburg

Abstract

Across industry and academia, knowledge graphs are increasingly being adopted for modelling relational data. They support the development of predictive models for various tasks, including information retrieval, question answering and knowledge base completion.   In drug discovery, while the investments in R&D have been increasing, the field has seen a decreasing rate of new therapies reaching the market. In-silico approaches to optimising the development process are desired enabling the development of treatments that would otherwise remain prohibitively expensive.   Knowledge graphs have the potential to accelerate scientific discovery by aiding hypothesis generation and providing predictions through machine learning. In drug discovery this could lead to recommendations of viable new therapeutic avenues. This talk will show an application of knowledge graphs in life sciences at Elsevier and machine learning approaches to link prediction.