Agent skill
patent-landscape
Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical IP, tracking competitor patents, or assessing freedom to operate for drug development. Provides comprehensive patent analysis and strategic insights for life sciences innovation.
Stars
163
Forks
31
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/patent-landscape
Metadata
Additional technical details for this skill
- version
- 1.0
- skill author
- AIPOCH
SKILL.md
Biotech Patent Landscape Analyzer
Analyze biotech and pharmaceutical patent landscapes to identify opportunities, assess competition, and guide R&D strategy.
Quick Start
python
from scripts.patent_landscape import PatentLandscapeAnalyzer
analyzer = PatentLandscapeAnalyzer()
# Analyze therapeutic area
landscape = analyzer.analyze(
therapeutic_area="CAR-T cell therapy",
date_range="2020-2024",
assignees=["Novartis", "Kite Pharma", "Juno Therapeutics"]
)
Core Capabilities
1. Patent Search & Analysis
python
results = analyzer.search_patents(
keywords=["CRISPR", "gene editing", "therapeutic"],
classification="C12N15/113", # IPC class
jurisdictions=["US", "EP", "WO"]
)
Search Strategies:
- Keyword-based: Technical terms + synonyms
- Classification-based: IPC/CPC codes
- Citation-based: Forward/backward citations
- Assignee-based: Company portfolios
2. White Space Analysis
python
opportunities = analyzer.identify_white_spaces(
technology="Antibody-drug conjugates",
target_diseases=["breast cancer", "lung cancer"],
existing_claims=landscape
)
White Space Opportunities:
- Underserved disease indications
- Novel combination therapies
- Alternative delivery mechanisms
- Geographical gaps (emerging markets)
3. Competitor Intelligence
python
competitors = analyzer.analyze_competitors(
companies=["Pfizer", "Moderna", "BioNTech"],
focus_area="mRNA vaccines"
)
Competitor Metrics:
| Metric | Description |
|---|---|
| Portfolio size | Total active patents |
| Filing velocity | Recent filing trends |
| Geographic coverage | Jurisdiction strategy |
| Technology focus | Core vs. peripheral areas |
| Partnership patterns | Collaboration trends |
4. Freedom to Operate (FTO) Assessment
python
fto = analyzer.assess_fto(
product_concept="Bispecific antibody targeting PD-1 and CTLA-4",
jurisdictions=["US", "EU", "Japan"]
)
FTO Analysis Steps:
- Identify relevant patent claims
- Map claims to product features
- Assess validity of blocking patents
- Design around options
- Licensing recommendations
CLI Usage
bash
# Generate patent landscape report
python scripts/patent_landscape.py \
--query "immuno-oncology checkpoint inhibitors" \
--output landscape_report.pdf \
--format comprehensive
# Quick FTO check
python scripts/patent_landscape.py \
--fto "product_description.txt" \
--jurisdictions US EP JP
Data Sources
- USPTO (United States)
- EPO (Europe)
- WIPO (Global)
- JPO (Japan)
- CNIPA (China)
References
references/ipc-classifications.md- IPC/CPC codes for biotechreferences/patent-search-strategies.md- Advanced search techniquesexamples/landscape-reports/- Sample reports
Skill ID: 204 | Version: 1.0 | License: MIT
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