Harnessing AI to identify causal relationships and enhance research and scientific validation in pharma

The knowledge needed for developing new drugs is spread across different databases, including internal, public and commercial sources. Having additional relevant knowledge can offer a significant advantage and drive medical progress. This talk discusses how the latest AI methods can help find gaps between curated and well-established knowledge in knowledge graphs and the unstructured knowledge in scientific texts. During the session, we will provide examples of how existing databases, like OpenTargets, can be enriched by using AI to identify causal relationships in scientific documents. With Knowledge Graph technology, these relationships are used to augment existing databases, allowing users to compare, spot gaps and, crucially, find the relevant literature to ensure scientific validation. Our product Dimensions Knowledge Graph was designed to help perform such gap analyses more effectively, but also allow customers to integrate their internal knowledge and data into the analysis process. Join us to discover how knowledge graphs and AI can be used to enhance research and scientific validation processes and advance progress in pharma.