Webinar
How to get the best out of RAG for scientific research
January 22, 2025 03:30 PM Europe/London
The webinar will be held Weds Jan 22 2025 at 3.30-4.30pm GMT, 10.30-11.30am EST, 7.30-8.30am PST, 4.30-5.30pm CET
Many biopharma organisations are struggling with the challenges of poorly implemented GenAI and RAG, often related to not being able to clearly reference where information has come from and thus not being able to trust the resulting data. How can data quality be better prioritised in RAG implementation?
This panel discussion webinar features RAG experts speaking to the perspectives of both best practices for 'doing RAG' (Jim Webber, Chief Scientist at Neo4j) as well as experts in the field implementing RAG for biopharma research (Krishna Bulusu, AstraZeneca). Daniel Jamieson, CEO at Biorelate, will chair a discussion that dives into the present and future of RAG in scientific research settings. This is a not-to-miss discussion for anyone in data science at biopharma organisations seeking to optimise their RAG strategy and usage.
Jim Webber
Dr. Jim Webber is Neo4j’s Chief Scientist and Visiting Professor at Newcastle University. At Neo4j, Jim leads the Systems Research Group, working on a variety of database systems research topics including query languages and runtimes, scale, and fault-tolerance. He also co-authored several books on graph technology including Graph Databases - 1st and 2nd Editions (O’Reilly), Graph Databases for Dummies (Wiley), and Building Knowledge Graphs (O’Reilly).
Prior to Neo4j, Jim worked on fault-tolerant distributed systems. First at Newcastle University startup Arjuna and then for a variety of clients for global consulting firm ThoughtWorks. Along the way Jim co-authored the distrubuted systems books REST in Practice (O’Reilly) and Developing Enterprise Web Services - An Architect’s Guide (Prentice-Hall).
Daniel Jamieson
Dr Daniel Jamieson founded Biorelate after supporting the successful identification of drug repurposing opportunities with Pfizer in a groundbreaking project to curate the first-ever knowledge graph to represent the pain interactome.
Michaël Ughetto
Michaël Ughetto is a Director of AI Strategy & Innovation for R&D IT at AstraZeneca, where he leads the team responsible for the Biological Insights Knowledge Graph (BIKG). Coming from a background in experimental particle physics, Michaël has shifted his focus to data science and machine learning, applying these skills to drug discovery. Since joining AstraZeneca in 2019, he has worked on using recommender systems and graph data science to help choose drug targets. His current work involves creating new tools to help with different stages of drug development, from finding targets to discovering biomarkers. Last year, the BIKG team released the first version of its AI-assisted chatbot for AstraZeneca’s R&D scientists, making it easier and faster to access knowledge from BIKG, the literature, and many other data sources.