Using Python Biopharm to Help Cure Cancer
summary
Claims a production system that links terabytes of assay, manufacturing, and clinical data using FastAPI and Pydantic for auditable schemas, a Neo4j knowledge graph to model biological and operational relationships, and chat-based interfaces that traverse edges rather than just retrieve docs. It reports users adopting a chatbot to regression-test datasets, cutting weeks of PowerPoint preparation to minutes, surfacing causal chains like “What changed?” and “Where have we seen this before?”, and running in regulated, low-latency deployments.
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chapters (8)
- 0:00Introduction
- 3:19Data handling phases
- 7:32Event storming
- 11:59Knowledge graphs
- 15:49Conversational interfaces for scientists
- 19:03AI chatbot testing
- 23:21Data curation importance
- 24:45Q&A
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