GraphTalk Pharma & Life Sciences

  • Length: 7 hr 20 min
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Chapters 14

  1. Play from Welcome & Opening Keynote: Augmented AI - Building Contextual Intelligence with Knowledge Graphs (Dr. Alexander Jarasch, Neo4j)
  2. Play from Stage 1 R&D: Bayer - Knowledge Graph Reasoning and GraphRAG for Early Target Discovery (Vladislav Kim)
  3. Play from Stage 1 R&D: KWS Group - From Graph to Gene (Bjoern Oest Hansen)
  4. Play from Stage 1 R&D: BASF - Knowledge Graphs for Non-Model Plants (Brent Murphy)
  5. Play from Stage 1 R&D: Q&A Panel
  6. Play from Stage 2 Clinical: Insel Spital Bern - From Free Text to Knowledge Graphs (Dr. Olga Endrich & Dr. Karen Triep)
  7. Play from Stage 2 Clinical: Sandoz - Graph-Based Analysis of Delayed Competition Through Patent Data (Dr. Peeyush Sahu)
  8. Play from Stage 2 Clinical: Q&A Panel
  9. Play from Knowledge Graph of Drugs Data for Swiss Healthcare System (Christian Franke, SwissDRG)
  10. Play from MedQGraph: TMKGs for AI-Driven Healthcare Insights (Ishan Chaudhary & Isaac Ritharson, Northeastern University)
  11. Play from Stage 3 Supply Chain: Supply Chain Insights, Without the Training Manual: Agents on a Pharma Context Graph - Boehringer Ingelheim (Mambwe Mumba)
  12. Play from Stage 3 Supply Chain: Financial Returns from Context Graph & AI (Jonathan W. Lowe, Amalgo LLC)
  13. Play from Stage 3 Supply Chain: Q&A Panel
  14. Play from Technical Deep Dive: Preparing Your Context Graph for GenAI (Niels De Jong & Jean-Marc Guerin, Neo4j)

AI experimentation is over. Production is the new bar - and in pharma and life sciences, knowledge graphs are what get you there.
Fragmented data kills GenAI impact. Without connected, explainable context, models hallucinate, pilots stall, and trust erodes. Knowledge graphs unify scientific literature, omics, clinical trials, and real-world evidence into a structured reasoning layer that makes AI grounded, traceable, and actually useful.
At GraphTalk Pharma & Life Sciences we follow the full pharma product lifecycle:
🔬 R&D: accelerating discovery and target identification
🏥 Clinical: explainable, data-driven decisions
🚚 Supply Chain: resilience and operational intelligence
Real use cases. Real organizations. Real production deployments on Neo4j.

Watch live and leave knowing exactly where knowledge graphs fit in your AI strategy.

Resources mentioned

GenAI & GraphRAGKnowledge graphs

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