Nick Brown

Executive Head of Predictive AI & Data AstraZeneca

His team focuses on using generative AI, knowledge graphs and FAIR data to predict the right safety and right patient dose as early as possible in the drug development process. He joined AstraZeneca over 20 years ago with a genetics and bioinformatics background. He loves to engineer scientific platforms that scale including toxicogenomics analysis, screening high-throughput content and using search to process hundreds of millions of scientific documents in seconds to enable drug repositioning and KOL identification. Additionally, Nick has spent 10 years developing large teams in IT, setting up technology incubation labs for the Chief Technology Office, focusing on connecting the latest external innovation from tech giants, VCs and start-ups to AstraZeneca’s real world business problems. He subsequently built a team of over 100 AI engineers and data scientists to deliver cloud AI platforms and AI services, which included knowledge graphs, deep learning, natural language processing and computer vision. Within R&D, he’s recently lead imaging teams with both wet and dry labs as well as AI & data teams that apply the latest novel machine learning models and explore the use of generative AI to safety assessment and clinical pharmacology. He's always keen to find new collaborations and partnerships.

Conference Day Two - Wednesday 2nd April

2:10 PM Presentation: The Opportunity of GenAI in Pharma & Healthcare

In this session, Nick Brown, Executive Head of Predictive AI & Data, will explore how leveraging knowledge graphs and AI can significantly improve data accuracy, scalability, and enterprise search capabilities within the pharmaceutical industry and beyond. He’ll share first hand examples of how his team uses GenAI & imaging to predict safety, toxicology and clinical challenges. Dive into the complexities of deploying AI at scale by:

·       Leveraging knowledge graphs to enhance data accuracy and scalability across the enterprise

·       Showcasing use cases to that improve our understanding of real-world implementation

·       Exploring what future opportunities exist for drug discovery

Check out the incredible speaker line-up to see who will be joining Nick.

Download The Latest Agenda