Webinar

Large Language Models in the Real World p2, a Pistoia Alliance and Biorelate co-hosted webinar

June 26, 2024 04:00 PM Europe/London

Following a very well-received panel discussion in March, the speakers return by popular demand to continue the conversation:
We know enough about the LLM technology at this time to move it from popular hype into production. We are, however, still at the beginning of this journey. What does biopharma research need to focus on to ensure they are implementing LLMs effectively? How do we benchmark and standardise best practices for LLM usage? Join knowledge management thought leaders from AbbVie, Roche and Biorelate to take the LLM conversation forward from ‘if and why’ to ‘how, what, when and where.’

Join us for our webinar in which the panelists will discuss applications of Large Language Models in pharmaceutical R&D.

SPEAKERS:

Daniel Jamieson, Biorelate 

Etzard Stolte, Roche 

Jon Stevens, Abbvie 

Vladimir Makarov

AI and ML Centre of Excellence Program, Pistoia Alliance, Inc.

Highly creative professional with business development and start-up experience in informatics and biotechnology. PhD in computational biology (Baylor College of Medicine), MBA (Pepperdine University). Former adjunct faculty at California State University and the University of Maryland.

Dr Etzard Stolte

Global Head Knowledge Management, Roche

Technical executive at the interface of Life- & Computer-Sciences, with a deep experience in defining and delivering strategic, scientific, and operational agendas on a global level.

Jon Stevens

AI Language Capability Lead, Information Research, AbbVie

I am a computational linguist, cognitive scientist and NLP software developer specializing in computational models of meaning and context.

Dr Daniel Jamieson

CEO, Biorelate

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.

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