Webinar: Unlocking the Power of Knowledge Graph-Driven, AI Solutions for Pharma Research
Driving scientific progress and innovation is challenging when crucial research and information are scattered across various—often gated—databases, spanning internal, public and commercial sources.
In this webinar in collaboration with Dimensions (a solution by Digital Science), we will discuss how the latest AI methods in combination with knowledge graph technology can help bring together global research knowledge, public data sets and internal knowledge bases to enhance research, scientific validation and target discovery processes.
During the session, we will focus on two core use cases:
Causal relationship search & discovery to support scientific validation: Using LLMs to precisely identify causal relationships from scientific literature , enrich well-established knowledge graphs, like OpenTargets, and annotate scientific publications in databases like Dimensions.
Target discovery: AI-driven exploration of protein and disease data across multiple public data sources, such as StringDB and OpenTargets, and enrichment with evidence from scientific literature.
In both cases, knowledge graph technology is used to augment existing databases with global research knowledge, allowing users to compare, spot gaps and, crucially, find the relevant literature to ensure scientific validation.
The Dimensions Knowledge Graph, powered by metaphactory, was designed to help perform such analyses by connecting curated, well-established knowledge from public pharma ontologies and structured data sources with global research knowledge and unstructured information found in scientific texts. By leveraging AI, it helps identify and fill gaps in existing data, offering insights that accelerate processes across the entire pharma value chain. This platform allows for seamless integration of internal knowledge, enhancing the ability to validate scientific findings and drive medical progress.
Join us to discover how knowledge graphs and AI can be used to enhance research, scientific validation and target discovery processes and advance progress in pharma!