菜单
Deep analysis of clinical trials including design, enrollment, outcomes, and competitive positioning. Use for trial monitoring, landscape analysis, and competitive intelligence. Keywords: clinical, trials, NCT, enrollment, phase, outcomes, study design
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基于 SOC 职业分类
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
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
| name | clinical-intelligence |
| description | Deep analysis of clinical trials including design, enrollment, outcomes, and competitive positioning. Use for trial monitoring, landscape analysis, and competitive intelligence. Keywords: clinical, trials, NCT, enrollment, phase, outcomes, study design |
| category | Clinical Intelligence |
| tags | ["clinical","trials","intelligence","fda","nmpa"] |
| version | 1.0.0 |
| author | Drug Discovery Team |
| dependencies | ["clinicaltrials-database","fda-database","ema-database"] |
Comprehensive clinical trial analysis for drug development and competitive intelligence.
/clinical NCT03704547
/clinical-intelligence EGFR inhibitors --phase 3
Analyze all trials for KRAS G12C inhibitors
Compare NSCLC trial designs across companies
| Section | Description | Data Source |
|---|---|---|
| Trial Overview | NCT ID, title, status, dates | ClinicalTrials.gov |
| Study Design | Phase, type, arms, endpoints | ClinicalTrials.gov |
| Enrollment | Target, actual, rate, sites | ClinicalTrials.gov |
| Eligibility | Inclusion/exclusion criteria | ClinicalTrials.gov |
| Outcomes | Primary/secondary endpoints | ClinicalTrials.gov, publications |
| Competitive Map | Similar trials comparison | Aggregated |
| Timeline | Milestones and readouts | Estimated |
# Clinical Trial Analysis: NCT03704547
## Executive Summary
FLAURA2 study evaluating osimertinib ± chemotherapy in first-line
EGFR-mutated NSCLC. **Status**: Active, not recruiting. **Results**: Positive PFS benefit.
## Trial Overview
| Field | Value |
|-------|-------|
| NCT ID | NCT03704547 |
| Title | Osimertinib With or Without Chemotherapy in EGFR-Mutated NSCLC |
| Status | Active, not recruiting |
| Phase | Phase 3 |
| Start Date | November 2018 |
| Primary Completion | October 2022 |
| Sponsor | AstraZeneca |
## Study Design
**Type**: Randomized, double-blind, placebo-controlled
**Arms:**
| Arm | Intervention | N |
|-----|--------------|---|
| Arm A | Osimertinib + chemotherapy | 279 |
| Arm B | Osimertinib + placebo chemo | 278 |
**Primary Endpoint:** Progression-free survival (PFS)
**Key Secondary:** Overall survival (OS), ORR, DoR
## Enrollment
| Metric | Value |
|--------|-------|
| Target Enrollment | 557 |
| Actual Enrollment | 557 |
| Enrollment Rate | On target |
| Sites | 150+ centers |
| Countries | 25+ countries |
## Key Results
- **PFS HR**: 0.62 (95% CI: 0.44-0.89)
- **Median PFS**: 25.5 vs 16.7 months
- **ORR**: 82% vs 74%
- **OS**: Mature (68% events)
## Competitive Landscape
| Trial | Drug | Phase | Status | Readout |
|-------|------|-------|--------|--------|
| NCT03704547 | Osimertinib + chemo | III | Positive | 2023 ESMO |
| NCT04035486 | Lazertinib + amivantamab | III | Recruiting | 2025 |
| NCT04887080 | Furmonertinib + chemo | III | Recruiting | 2025 |
## Site Distribution
| Region | Sites | Patients |
|--------|-------|----------|
| North America | 45 | 180 |
| Europe | 60 | 210 |
| Asia Pacific | 45 | 167 |
/clinical NCT03704547
/clinical-intelligence NCT01234567
/clinical EGFR trials --phase 3
/clinical "sotorasib" studies
Analyze all KRAS G12C clinical trials
Compare osimertinib trials vs competitors
/clinical NSCLC --company AstraZeneca
Map phase III trials in EGFR-mutated NSCLC
/clinical NCT03704547 --focus enrollment
Compare enrollment rates across similar trials
Analyze site distribution for KRAS trials
# Fetch trial data
python scripts/fetch_trial_data.py NCT03704547 --output trial.json
# Search for trials by condition
python scripts/fetch_trial_data.py --condition "NSCLC" --phase 3 -o results.json
# Search by drug/intervention
python scripts/fetch_trial_data.py --intervention osimertinib -o osimertinib.json
# Competitive trial mapping
python scripts/fetch_trial_data.py --target EGFR --phase 2-3 --map-competition
pip install requests pandas
| Pitfall | Solution |
|---|---|
| Too many results | Add phase, status, or date filters |
| Outdated status | Trial status changes, verify current |
| Missing results | Results may be in publications only |
| Duplicate trials | Same study may have multiple NCTs |
| Terminated trials | Check why before analysis |