Track pharmaceutical M&A, licensing, and investment deals. Use for competitive intelligence, market analysis, and identifying partnership opportunities. Keywords: deals, M&A, licensing, partnership, collaboration, acquisition, pharma deals
Scanned 2/12/2026
Install to Claude Code
npx -y skills add huifer/drug-discovery-skills --skill deal-tracker --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: deal-tracker
description: |
Track pharmaceutical M&A, licensing, and investment deals. Use for competitive
intelligence, market analysis, and identifying partnership opportunities.
Keywords: deals, M&A, licensing, partnership, collaboration, acquisition, pharma deals
category: Business Intelligence
tags: [deals, manda, licensing, partnership, investment]
version: 1.0.0
author: Drug Discovery Team
dependencies:
- sec-filings
- press-releases
- deal-databases
---
# Deal Tracker Skill
Track pharmaceutical industry deals, M&A, and partnerships.
## Quick Start
```
/deals --oncology --year 2024
/partnership --type licensing --target "EGFR"
/ma-summary --biotech --threshold 100M
```
## What's Included
| Section | Description | Source |
|---------|-------------|--------|
| Deal Feed | Recent announcements | Press releases, SEC |
| M&A Tracker | Acquisitions and mergers | SEC 8-K, 10-K |
| Licensing Deals | In-licensing, out-licensing | Company announcements |
| Partnerships | R&D collaborations | Press releases |
| Investment | Venture capital, IPO | SEC, exchanges |
## Output Structure
```markdown
# Deal Tracker: Oncology Targets (2024)
## Summary
| Metric | Count | Total Value |
|--------|-------|-------------|
| Total Deals | 127 | $45.2B |
| M&A | 12 | $28.5B |
| Licensing | 89 | $14.3B |
| Partnerships | 26 | $2.4B |
## Recent Deals (Last 30 Days)
### M&A
| Date | Acquirer | Target | Value | Type |
|------|----------|--------|-------|------|
| 2024-12-15 | Pfizer | Seagen | $43B | Acquisition |
| 2024-12-10 | BMS | Mirati | $4.8B | Acquisition |
### Licensing
| Date | Licensee | Licensor | Asset | Upfront | Milestones |
|------|----------|---------|-------|---------|------------|
| 2024-12-08 | AstraZeneca | Hengrui | KRAS G12D | $100M | $800M |
| 2024-12-05 | Merck | Daiichi Sankyo | ADC platform | $300M | $1.5B |
## By Target Class
| Target | Deals | Total Value | Avg Upfront |
|--------|-------|-------------|-------------|
| EGFR | 8 | $1.2B | $85M |
| KRAS | 12 | $2.8B | $120M |
| HER2 | 6 | $950M | $78M |
## By Deal Type
| Type | Count | Total Value | Trend |
|------|-------|-------------|-------|
| Acquisition | 12 | $28.5B | ↑ |
| Asset purchase | 45 | $8.2B | → |
| Platform license | 28 | $5.1B | ↑ |
| Co-development | 18 | $1.8B | → |
| Option agreement | 24 | $2.1B | ↓ |
## Key Observations
1. **M&A resurgence**: 12 biotech acquisitions in H2
2. **ADC momentum**: Antibody-drug conjugates dominate
3. **Early-stage focus**: 60% of deals at preclinical/Phase 1
4. **Oncology dominance**: 70% of deal value in oncology
```
## Deal Types
| Type | Description | Typical Structure |
|------|-------------|-------------------|
| Acquisition | Full company buyout | Cash + stock |
| Asset Purchase | Specific asset(s) | Upfront + milestones |
| Licensing | Rights to develop/sell | Upfront + royalties + milestones |
| Co-development | Joint development | Cost/revenue sharing |
| Collaboration | R&D partnership | Funded research |
| Option | Right to acquire later | Option fee + exercise price |
| Spin-off | Company separation | Share distribution |
## Valuation Ranges
| Stage | Typical Upfront | Total Deal |
|-------|-----------------|------------|
| Preclinical | $10-50M | $100-500M |
| Phase 1 | $30-100M | $200-800M |
| Phase 2 | $50-200M | $500M-2B |
| Phase 3 | $100-500M | $1B-5B |
| Approved | $200M-2B | $2B-10B+ |
## Running Scripts
```bash
# Recent deals feed
python scripts/deal_tracker.py --feed --days 30
# Filter by target
python scripts/deal_tracker.py --target EGFR --include licensing,manda
# Deal summary
python scripts/deal_tracker.py --summary --year 2024 --oncology
# Export to CSV
python scripts/deal_tracker.py --export --format csv --output deals.csv
```
## Requirements
```bash
pip install requests beautifulsoup4 pandas
```
## Reference
- [reference/deal-sources.md](reference/deal-sources.md) - Deal data sources
- [reference/deal-structures.md](reference/deal-structures.md) - Deal structure reference
- [reference/valuation-methods.md](reference/valuation-methods.md) - Valuation methodologies
## Best Practices
1. **Verify from multiple sources**: Cross-check deal values
2. **Track milestones: Monitor deal progression
3. **Understand structure**: Upfront vs milestones vs royalties
4. **Compare benchmarks**: Similar deals for reference
5. **Monitor regulatory**: FTC approval may be required
## Common Pitfalls
| Pitfall | Solution |
|---------|----------|
| Misreported values | Check SEC filings |
| Confusing announced vs closed | Track closing conditions |
| Ignoring milestones | Total value often optimistic |
| Currency confusion | Note USD vs local |
| Double counting | Verify unique deals |
## Limitations
- **Private deals**: Terms often undisclosed
- **Delayed reporting**: SEC filings lag announcements
- **Incomplete milestones**: Many undisclosed
- **Value estimates**: Some values are estimates
- **Geographic bias**: US deals better covered
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