aws-samples Deep Literature Review
When to use this skill
- Developer asks "find papers about X" or "what's the latest research on Y?"
- Developer needs to build an evidence summary from multiple publications
- Developer wants to extract specific data from a paper or PDF
- Developer needs to search across biomedical literature and databases
- Developer asks about systematic literature review workflows
MCP Server: biomni-research
This server provides tools for biomedical database queries including literature-related functionality. Tools are discovered automatically via the MCP protocol.
Quick setup (after deployment):
cd mcp-servers/agentcore-gateway/biomni-research-tools
source get-token.sh
claude mcp add --transport http biomni-research "$BIOMNI_GATEWAY_URL" --header "Authorization: Bearer $BIOMNI_MCP_TOKEN"
Search Strategy
Choosing the Right Approach
| Research Type | Query approach (via biomni-research) |
|---|---|
| Clinical evidence (trials, outcomes) | Query ClinicalTrials database |
| Variant significance | Query ClinVar + gnomAD |
| Drug safety / regulatory | Query OpenFDA |
| Protein biology | Query UniProt + InterPro |
| Cancer genomics | Query cBioPortal + GEO |
| Pathway mechanisms | Query Reactome + Open Targets |
Effective Query Construction
All tools accept natural language prompts. Be specific:
"Find pathogenic BRCA1 variants associated with breast cancer"
"EGFR T790M resistance mutation frequency in Asian populations"
"CDK4/6 inhibitors clinical trials phase 3 breast cancer"
"TP53 expression in hepatocellular carcinoma datasets"
Literature Review Workflows
Workflow 1: Rapid Evidence Summary
Goal: Quickly assess the state of evidence on a topic.
- Broad database search: Query relevant databases for the topic
- Cross-reference: Check multiple databases for consistency
- Extract details: Use PDF extraction tool for full-text papers
- Synthesize: Combine database evidence with extracted findings
Workflow 2: Competitive Intelligence (Drug Development)
- Find clinical trials: Query ClinicalTrials for "drug/target phase 2 phase 3 results"
- Check target biology: Query Open Targets + UniProt for target validation
- Regulatory context: Query OpenFDA for drug safety signals
- Extract details: Use PDF extraction for advisory briefing documents
Workflow 3: Systematic Literature Search
- Define PICO: Population, Intervention, Comparison, Outcome
- Multi-database search: Query ClinVar + ClinicalTrials + Open Targets
- Cross-reference: Compare findings across databases for consistency
- Validate: Check population frequencies (gnomAD) for genomic findings
Workflow 4: Technology Landscape
- Foundational biology: Query UniProt + Reactome for mechanism
- Clinical translation: Query ClinicalTrials for applications
- Cancer data: Query cBioPortal for mutation/expression profiles
- Regulatory status: Query OpenFDA for approved therapies
Tips
- Be specific with organisms: Always specify "human" to avoid cross-species results
- Use standard identifiers: Gene symbols (BRCA1), UniProt IDs (P38398), RS numbers (rs80357906)
- Start broad, narrow down: First query identifies the entity → follow-up gets specific data
- Cross-validate: If a finding appears across multiple database tools, it's more reliable
- Extract strategically: Only use PDF extraction when you need methods details or specific data points
Combining with Other Skills
Literature review is most powerful when combined with other database queries:
- Find variant: Query ClinVar for "EGFR T790M pathogenic"
- Check frequency: Query gnomAD for "EGFR T790M population frequency"
- Check pathways: Query Reactome for "EGFR signaling cascade"
- Find trials: Query ClinicalTrials for "EGFR T790M osimertinib"
This multi-database feedback loop produces comprehensive evidence packages.