// Global drug development pipeline tracking by disease, target, mechanism, or company. Use for competitive intelligence, opportunity identification, and trend analysis. Keywords: pipeline, drug development, clinical trials, R&D tracking, competitive landscape
| name | pipeline-tracker |
| description | Global drug development pipeline tracking by disease, target, mechanism, or company. Use for competitive intelligence, opportunity identification, and trend analysis. Keywords: pipeline, drug development, clinical trials, R&D tracking, competitive landscape |
| category | Competitive Intelligence |
| tags | ["pipeline","fda","clinical-trials","drug-development","tracking"] |
| version | 1.0.0 |
| author | Drug Discovery Team |
| dependencies | ["clinicaltrials-api","fda-api","pharma-projects","citeline"] |
Track global drug development pipeline across diseases, targets, and companies.
/pipeline --target "EGFR" --by-phase
/pipeline --disease "NSCLC" --phase 2,3
/pipeline --company "AstraZeneca" --oncology
/pipeline-trends --compare 2023 vs 2024
| 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% |
| 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% | → |
# 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)
# 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
pip install requests pandas numpy
# Optional for advanced features
pip install plotly seaborn
| 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 |
Structure-based similarity search and scaffold analysis for drug discovery. Use for lead hopping, scaffold morphing, and chemical space exploration. Keywords: similarity search, scaffold hopping, chemical space, fingerprint, Tanimoto
Analyze target competitive landscape including existing drugs, pipeline companies, differentiation opportunities, and market maturity assessment. Keywords: target competition, landscape, differentiation, pipeline analysis, market share
Target safety assessment including known toxicities, essentiality, and off-target concerns. Use for early safety risk evaluation and target selection. Keywords: target safety, toxicity, essential gene, knockout, safety risks
Comprehensive target validation assessing druggability, disease association strength, tractability, and competitive landscape. Use for go/no-go decisions on target selection. Keywords: target validation, druggability, tractability, disease association, genetic validation
ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) prediction for drug candidates. Use for assessing drug-likeness, PK properties, and safety risks early in drug discovery. Keywords: ADMET, PK, toxicity, drug-likeness, DILI, hERG, bioavailability
Automated alert system for key events in drug discovery. Use for tracking competitor milestones, clinical trial updates, regulatory decisions, and publications of interest. Keywords: alerts, monitoring, tracking, notifications, competitive intelligence