When & Why to Use This Skill
This Claude skill provides a comprehensive intelligence platform for tracking the global drug development pipeline. It enables pharmaceutical professionals, investors, and researchers to monitor clinical trials, analyze R&D trends, and perform deep competitive analysis across diseases, molecular targets, and therapeutic mechanisms. By integrating data from clinical registries and regulatory filings, it helps identify market 'white spaces,' assess innovation indices, and predict industry shifts.
Use Cases
- Competitive Intelligence: Monitor rival pharmaceutical companies' pipelines by phase and therapeutic area to anticipate market entry and competitive threats.
- Investment Analysis: Evaluate the commercial potential and success rates of specific drug candidates or biotech portfolios to inform investment strategies.
- Strategic R&D Planning: Identify unmet medical needs and 'white space' opportunities by analyzing regional distribution and attrition rates of current programs.
- Trend Forecasting: Analyze the evolution of emerging modalities like ADCs, PROTACs, and bispecific antibodies to stay ahead of industry innovation trends.
- Business Development: Identify potential licensing or partnership opportunities by filtering companies with high-growth pipelines in specific therapeutic areas.
| name | pipeline-tracker |
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| description | | |
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| Keywords | pipeline, drug development, clinical trials, R&D tracking, competitive landscape |
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| category | Competitive Intelligence |
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| tags | [pipeline, fda, clinical-trials, drug-development, tracking] |
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| version | 1.0.0 |
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| author | Drug Discovery Team |
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Pipeline Tracker Skill
Track global drug development pipeline across diseases, targets, and companies.
Quick Start
/pipeline --target "EGFR" --by-phase
/pipeline --disease "NSCLC" --phase 2,3
/pipeline --company "AstraZeneca" --oncology
/pipeline-trends --compare 2023 vs 2024
Pipeline Overview
By Development Phase
| Phase |
Description |
Count (2024) |
Trend |
| Preclinical |
Before IND |
~15,000 |
↑ 5% |
| Phase 1 |
First-in-human |
~2,500 |
↑ 8% |
| Phase 2 |
Efficacy |
~1,800 |
↑ 6% |
| Phase 3 |
Confirmatory |
~900 |
↑ 10% |
| Registration |
Under review |
~200 |
→ |
| Approved |
Marketed |
~1,500 |
↑ 3% |
By Therapeutic Area
| Area |
Pipeline Share |
Growth |
| Oncology |
38% |
↑ 12% |
| Immunology |
12% |
↑ 8% |
| Neurology |
10% |
↑ 5% |
| Cardiovascular |
8% |
↓ 2% |
| Metabolic |
8% |
↑ 3% |
| Respiratory |
6% |
↑ 4% |
| Infectious |
6% |
↓ 15% |
| Other |
12% |
→ |
Output Structure
# Pipeline Analysis: EGFR Inhibitors (2024)
## Summary
| Metric | Value | vs 2023 |
|--------|-------|--------|
| Total Programs | 245 | ↑ 12% |
| Phase 3 | 18 | ↑ 20% |
| Phase 2 | 42 | ↑ 10% |
| Phase 1 | 67 | ↑ 15% |
| Preclinical | 118 | ↑ 8% |
## By Phase
### Phase 3 Programs
| Drug | Company | Indication | Status |
|------|---------|-----------|--------|
| Lazertinib | J&J | NSCLC 1L | Recruiting |
| Nazartinib | Novartis | NSCLC 2L | Active |
| Amivantamab | J&J | NSCLC | Accelerated |
| Patritumab | Daiichi Sankyo | NSCLC | Recruiting |
| Datopotamab | Merck | NSCLC | Active |
| ... | ... | ... | ... |
### Phase 2 Programs
| Drug | Company | Indication | Differentiation |
|------|---------|-----------|-----------------|
| JDQ443 | J&J | NSCLC | CNS-penetrant |
| BPI-301 | BridgeBio | CRC | Selective |
| ... | ... | ... | ... |
## By Company
### Top 10 Companies by EGFR Pipeline
| Rank | Company | Phase 3 | Phase 2 | Phase 1 | Total |
|------|---------|---------|---------|---------|-------|
| 1 | AstraZeneca | 2 | 3 | 5 | 10 |
| 2 | J&J | 3 | 4 | 3 | 10 |
| 3 | Merck | 2 | 2 | 4 | 8 |
| 4 | Roche | 1 | 3 | 3 | 7 |
| 5 | BeiGene | 1 | 2 | 4 | 7 |
| ... | ... | ... | ... | ... | ... |
## By Mechanism
| Mechanism | Count | Trend |
|-----------|-------|-------|
| 3rd-gen TKI | 45 | ↑ |
| 4th-gen TKI (C797S) | 12 | ↑↑ |
| Bi-specific | 8 | ↑↑ |
| ADC | 15 | ↑↑ |
| Allosteric | 5 | → |
| PROTAC | 3 | ↑ |
## Pipeline Trends
### 3-Year Evolution
| Year | Phase 3 | Phase 2 | Phase 1 | Total |
|------|---------|---------|---------|-------|
| 2022 | 12 | 35 | 52 | 198 |
| 2023 | 15 | 38 | 58 | 219 |
| 2024 | 18 | 42 | 67 | 245 |
**Growth Rate**: 11% CAGR
### Key Trends
1. **4th-generation expansion**: Targeting C797S resistance
2. **ADC surge**: Antibody-drug conjugates gaining
3. **CNS focus**: Brain metastasis programs
4. **Combination trials**: 40% in combinations
## Regional Distribution
| Region | Phase 3 | Phase 2 | Phase 1 |
|--------|---------|---------|---------|
| United States | 45% | 38% | 42% |
| China | 30% | 35% | 38% |
| Europe | 25% | 20% | 18% |
| Japan | 12% | 8% | 10% |
| Rest of World | 8% | 5% | 5% |
## Innovation Assessment
### Novel Mechanisms by Phase
| Mechanism | Phase 3 | Phase 2 | Phase 1 | Preclinical |
|-----------|---------|---------|---------|------------|
| 4th-gen TKI | 3 | 5 | 4 | 8 |
| ADC | 4 | 6 | 5 | 12 |
| Bispecific | 2 | 3 | 3 | 6 |
| PROTAC | 0 | 1 | 0 | 5 |
| Allosteric | 0 | 2 | 3 | 4 |
**Innovation Index**: 32% novel mechanisms
## Competitive Dynamics
### Success Rate by Phase
| Transition | Rate | Analysis |
|------------|------|----------|
| Preclinical → Phase 1 | 15% | High risk |
| Phase 1 → Phase 2 | 60% | Improved |
| Phase 2 → Phase 3 | 35% | Major hurdle |
| Phase 3 → Approval | 65% | Strong pipeline |
### Attrition Analysis
| Reason | Phase 2 | Phase 3 |
|--------|---------|---------|
| Efficacy | 45% | 40% |
| Safety | 25% | 35% |
| Commercial | 15% | 20% |
| Strategic | 10% | 5% |
## Opportunities
### White Space
| Area | Programs | Opportunity |
|------|----------|------------|
| C797S + S1278 double mutant | 0 | High |
| Brain metastasis focus | 3 | High |
| Oral 4th-gen | 2 | Medium |
| Adjuvant setting | 4 | Medium |
## Recommendations
### For New Entrants
**Avoid**: Crowded 3rd-gen space
**Consider**:
1. **CNS-penetrant 4th-gen**: 3 programs total
2. **Double mutant coverage**: Unmet need
3. **Combination-ready**: Biomarker-selected
4. **Neoadjuvant setting**: Earlier treatment
### For Investors
**Hot Areas**:
- 4th-gen TKI (resistance focus)
- ADC platforms (established targets)
- CNS programs (large unmet need)
**Rising Stars**:
- Revolution (RMC-4630)
- BridgeBio (BPI-301)
- Cullinan (PROTAC)
Running Scripts
# Target pipeline
python scripts/pipeline_tracker.py --target EGFR --by-phase
# Disease pipeline
python scripts/pipeline_tracker.py --disease "NSCLC" --phase 2,3
# Company pipeline
python scripts/pipeline_tracker.py --company "AstraZeneca" --oncology
# Trend analysis
python scripts/pipeline_tracker.py --trends 2022-2024 --target "KRAS"
# Export
python scripts/pipeline_tracker.py --export --format csv --output pipeline.csv
Requirements
pip install requests pandas numpy
# Optional for advanced features
pip install plotly seaborn
Reference
Best Practices
- Update regularly: Pipeline changes weekly
- Verify status: Check ClinicalTrials.gov
- **Track discontinuations: Learn from failures
- **Monitor conferences: ASCO, ESMO for pipeline updates
- **Include China: Major contributor to pipeline
Common Pitfalls
| Pitfall |
Solution |
| Stale data |
Regular refresh from source APIs |
| Missing inactive trials |
Include suspended/terminated |
| Geographic bias |
Include global programs |
| Company name variants |
Standardize company names |
| Duplicate counting |
Use unique trial IDs |
