AWS GraphRAG with Neptune and Bedrock accelerates drug discovery 10x
GraphRAG slashes drug discovery time from 6 months to minutes with verifiable evidence.
A graph-powered AI system using Amazon Neptune Analytics and Bedrock connects fragmented pharmaceutical data. Researchers ask natural-language questions and receive evidence-backed insights from a unified knowledge graph spanning publications, lab notes, and genomics. The approach addresses early-stage drug discovery challenges—where traditional methods yield a 5% success rate and screening takes over six months—by surfacing hidden connections and providing citation trails for reproducibility. It aims to help researchers move faster, generate better hypotheses, and preserve institutional memory.
- Traditional drug discovery has only a 5% hit rate and takes over 6 months of screening per attempt.
- GraphRAG combines Amazon Neptune Analytics with Bedrock to let researchers query a unified knowledge graph in natural language.
- Every answer includes complete citation paths and graph traversal steps, making scientific discovery transparent and reproducible.
Why It Matters
GraphRAG could cut drug discovery timelines by 90% while preserving institutional knowledge and ensuring regulatory-grade evidence traceability.