How researchers can analyze biomedical literature in minutes using Amazon Bedrock

This article presents an open-source AWS solution that automates biomedical literature analysis for researchers, reducing manual review time from 3-5 days to under 5 minutes per paper.

• Amazon Bedrock Data Automation extracts structured content from PDFs, preserving tables and section boundaries as markdown
• AWS Step Functions orchestrates a five-stage pipeline: document extraction, relevance filtering, biomarker extraction, outcome analysis, and summarization
• Claude via Amazon Bedrock determines paper relevance and performs intelligent analysis without manual intervention
• Evidence-mapping feature links summary claims back to exact locations in original PDFs using bounding box coordinates
• Prompts stored in DynamoDB enable researchers to tune analysis for different conditions without code changes
• Results accessible through React-based frontend with gene browsing, bookmarking, and analysis history tracking
• Fully serverless architecture deployed via AWS CDK; open-source code available on GitHub

The solution transforms biomedical research by automating complex document analysis, enabling researchers to focus on interpretation and decision-making rather than manual data extraction.