Deal Tracker Skill

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

Output Structure

# 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

Valuation Ranges

Running Scripts

# 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

pip install requests beautifulsoup4 pandas

Reference

• reference/​deal-sources.md - Deal data sources
• reference/​deal-structures.md - Deal structure reference
• 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

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