Claude-skill-registry competitor-landscape
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/competitor-landscape" ~/.claude/skills/majiayu000-claude-skill-registry-competitor-landscape && rm -rf "$T"
manifest:
skills/data/competitor-landscape/SKILL.mdsource content
Competitor Landscape Skill
Comprehensive competitive intelligence for drug development decisions.
Quick Start
/competitor EGFR inhibitors /competitor-landscape KRAS G12C drugs Compare all EGFR TKIs in clinical development Who's developing GLP-1R agonists for obesity?
What's Included
| Section | Description | Data Source |
|---|---|---|
| Market Overview | Approved drugs, pipeline count, market size | Aggregated |
| Competitive Map | Company-by-portfolio breakdown | PharmaProjects |
| Mechanism Analysis | MOA classification, differentiation | ChEMBL, literature |
| Clinical Status | Phase distribution, readouts, timelines | ClinicalTrials.gov |
| Key Players | Company profiles, partnerships, deals | Company data |
| Differentiation | Competitive positioning, white space | Analysis |
Output Structure
# EGFR Inhibitors - Competitive Landscape ## Executive Summary The EGFR inhibitor market is mature but evolving. 9 drugs approved with 3rd-generation TKIs dominating. Pipeline focuses on resistance mechanisms and CNS penetration. Key battleground: 4th-generation agents for C797S. ## Market Overview | Metric | Value | |--------|-------| | Approved Drugs | 9 (5 TKIs, 4 antibodies) | | In Development | 34 candidates (21 clinical) | | Market Size | $12B globally (2023) | | Key Companies | AstraZeneca, Roche, Boehringer | ## 1. Competitive Map by Company ### AstraZeneca (Leader) | Drug | Type | Phase | Differentiation | |------|------|-------|----------------| | Osimertinib | 3rd-gen TKI | Approved | Standard of care | | AZD9291 + savolitinib | Combo | III | MET amp resistance | ### Roche | Drug | Type | Phase | Status | |------|------|-------|--------| | Erlotinib | 1st-gen TKI | Approved | Generic | | Tiragolumab + atezo | TIGIT + EGFR | III | Combo | [... more companies ...] ## 2. Approved Drugs Analysis | Drug | Company | Launch | Type | Key Indication | Sales 2023 | |------|---------|--------|------|----------------|------------| | Osimertinib | AstraZeneca | 2015 | 3rd-gen TKI | NSCLC 1st line | $5.8B | | Erlotinib | Astellas | 2004 | 1st-gen TKI | NSCLC 2nd line | $0.3B | | Gefitinib | AstraZeneca | 2003 | 1st-gen TKI | NSCLC | $0.2B | | Necitumumab | Eli Lilly | 2015 | Antibody | Squamous NSCLC | Discontinued | | Amivantamab | J&J | 2021 | Bispecific | Exon20ins | $0.2B | ## 3. Pipeline by Development Phase ### Phase III | Drug | Company | Differentiation | Readout | |------|---------|----------------|---------| | Lazertinib | Yuhan/J&J | 3rd-gen, WT sparing | 2024 H2 | | Nazartinib | Novartis | CNS active | 2024 Q3 | | Patritumab deruxtecan | Daiichi Sankyo | ADC | 2025 | ### Phase II | Drug | Company | Mechanism | Novelty | |------|---------|-----------|---------| | BLU-945 | Blueprint | 4th-gen (C797S) | First-in-class | | BPI-9016M | Betta | 4th-gen | C797S focus | | ... | ... | ... | ... | ## 4. Mechanism of Action Classification | Class | Count | Status | |-------|-------|--------| | 1st-gen TKI | 3 approved | Generic | | 2nd-gen TKI | 2 approved | Mature | | 3rd-gen TKI | 3 approved | Dominant | | 4th-gen TKI | 5 in clinic | Emerging | | Antibodies | 4 approved | Niche | | Bispecifics | 3 in clinic | Emerging | | ADCs | 4 in clinic | Hot area | ## 5. Key Development Trends ### 2023-2024 Trends 1. **4th-generation TKIs**: Focus on C797S resistance mutation 2. **CNS penetration**: Critical for brain mets 3. **Combination therapies**: EGFR + MET, EGFR + chemotherapy 4. **ADC approach**: HER3-ADC, MET-ADC combinations 5. **Bispecifics**: Amivantamab leading ### White Space Opportunities | Area | Rationale | |------|-----------| | 4th-gen TKI | C797S mutation unaddressed | | Brain mets | High unmet need | | Early detection | Neoadjuvant setting | | Resistance combo | MET amp, HER3 upregulation | ## 6. Company Profiles ### AstraZeneca (Market Leader) - **Portfolio**: Osimertinib (core), Tagrisso + chemoprev (adjuvant) - **Strategy**: Extend osimertinib lifecycle (adjuvant, combo) - **Strengths**: First-mover, brand recognition - **Weaknesses**: Patent cliff approaching ### Emerging Players - **Blueprint Medicines**: 4th-gen TKI leader (BLU-945) - **J&J**: Combo strategy (lazertinib + EGFR/c-MET bispecific) - **Daiichi Sankyo**: ADC approach (patritumab deruxtecan) ## 7. Investment & Deals (Recent) | Deal | Type | Value | Year | |------|------|-------|------| | J&J / Yuhan | Licensing | $1.2B | 2018 | | Merck / Daiichi Sankyo | Combo partnership | $4.5B | 2023 | | BMS / Turning Point | Acquisition | $4.1B | 2023 | ## 8. Go/No-Go Considerations ### Green Light Signals - C797S mutation space open - CNS penetration unmet - Combination approaches working ### Red Light Signals - 3rd-gen crowded - Generic erosion (1st/2nd gen) - High clinical trial costs ### Yellow Light Signals - 4th-gen clinical risk (first-in-class) - Combination regulatory complexity
Examples
Drug Class Analysis
/competitor EGFR TKIs /competitor GLP-1R agonists /competitor PCSK9 inhibitors
Disease Area Analysis
/competitor NSCLC therapies Compare Alzheimer's drugs in development /competitor obesity medications --phase 2-3
Company Portfolio
What is AstraZeneca's oncology pipeline? Compare Roche vs Novartis in hematology /competitor "Company Name" portfolio
Mechanism Focus
/competitor KRAS G12C inhibitors Compare all PROTAC degraders in clinic /competitor antibody-drug conjugates
Running Scripts
# Fetch competitive landscape data python scripts/fetch_competitor_data.py "EGFR inhibitors" --output data.json # Include clinical trials python scripts/fetch_competitor_data.py "KRAS" --clinical-trials -o full.json # Company-specific python scripts/fetch_competitor_data.py --company "AstraZeneca" --indication oncology
Requirements
pip install requests pandas lxml
Additional Resources
Best Practices
- Be specific: Use drug class names (e.g., "3rd-gen EGFR TKI")
- Define scope: Specify indication, phase, or company
- Compare: Ask for competitive positioning
- Look for white space: Ask about unaddressed areas
Common Pitfalls
| Pitfall | Solution |
|---|---|
| Too broad | Specify drug class or indication |
| Missing context | Include disease area |
| Outdated pipeline | Check date of data |
| Public vs private | Public sources only |