Agenda Introduction to target identification Knowledge extraction from literature (embedding, clustering, chatbots) Reducing the hallucinations (RAG, Graph RAG) Accessing structured data: impact on scripting and next-gen tools Speakers Prof. Dan Crowther, University of Dundee David Brett, Associate Director of LLMs, Recursion For details of our full Pharma and Life Science AI/ML Training Program […]
Agenda LLM agents Automating DD tasks Speakers Prof. Mike Barnes, Queen Mary University Anniek Myatt, Recursion For details of our full Pharma and Life Science AI/ML Training Program and how to register, please click here.
AI/ML is ubiquitous across the pharma industry, at least as a label. Do all AI/ML activities actually represent artificial intelligence? We will first frame AI and ML separately, and describe why we might want one or the other. With a definition in place, we will highlgiht examples of ML/AI applications across the entire drug discovery […]
Agenda Knowledge graphs as a heterogeneous data store Analysis of knowledge graphs Graph RAG Graph neural networks Understanding complex biological mechanisms of action (MoA) for drugs and diseases is crucial for effective ORC prioritization and target identification. MIDAAS, our Multi-modal Integrated Data, Analytics & Agentic System, leverages GenAI-powered multi-agent systems to enhance this biological understanding. […]
Agenda Automating Drug Development via AI and 3D Printing NLP in Drug Development Speaker Prof. Moe Elbadawi, Queen Mary University For details of our full Pharma and Life Science AI/ML Training Program and how to register, please click here.
