clinical-intelligence

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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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When & Why to Use This Skill

The Clinical Intelligence skill is a specialized analytical tool designed for pharmaceutical professionals, researchers, and competitive intelligence analysts to perform deep-dive evaluations of clinical trials. By aggregating real-time data from ClinicalTrials.gov, FDA, and EMA, it provides comprehensive insights into study designs, enrollment metrics, and clinical outcomes. This skill streamlines the process of monitoring the drug development landscape, allowing users to track NCT IDs, compare competitive positioning, and forecast trial milestones with high precision.

Use Cases

  • Competitive Intelligence: Compare efficacy data (such as PFS or ORR) and safety profiles between your drug candidate and competitors to identify market advantages.
  • Landscape Analysis: Map all active Phase 2 and Phase 3 trials for specific molecular targets (e.g., EGFR, KRAS) to understand research density and identify therapeutic gaps.
  • Trial Monitoring & Feasibility: Analyze enrollment rates, site distributions, and recruitment statuses to evaluate the progress and potential delays of specific clinical studies.
  • Protocol Optimization: Extract and review inclusion/exclusion criteria and primary endpoints from successful trials to inform the design of new clinical protocols.
nameclinical-intelligence
description|
Keywordsclinical, trials, NCT, enrollment, phase, outcomes, study design
categoryClinical Intelligence
tags[clinical, trials, intelligence, fda, nmpa]
version1.0.0
authorDrug Discovery Team

Clinical Intelligence Skill

Comprehensive clinical trial analysis for drug development and competitive intelligence.

Quick Start

/clinical NCT03704547
/clinical-intelligence EGFR inhibitors --phase 3
Analyze all trials for KRAS G12C inhibitors
Compare NSCLC trial designs across companies

What's Included

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

Output Structure

# 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 |

Examples

Trial Lookup

/clinical NCT03704547
/clinical-intelligence NCT01234567

By Target/Drug

/clinical EGFR trials --phase 3
/clinical "sotorasib" studies
Analyze all KRAS G12C clinical trials

Competitive Analysis

Compare osimertinib trials vs competitors
/clinical NSCLC --company AstraZeneca
Map phase III trials in EGFR-mutated NSCLC

Enrollment Analysis

/clinical NCT03704547 --focus enrollment
Compare enrollment rates across similar trials
Analyze site distribution for KRAS trials

Running Scripts

# 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

Requirements

pip install requests pandas

Additional Resources

Best Practices

  1. Use NCT ID: Most precise way to look up trials
  2. Specify phase: Narrow down to relevant trials
  3. Check status: Trials may be terminated/suspended
  4. Verify enrollment: Actual vs target enrollment matters
  5. Cross-reference: Check publications for results

Common Pitfalls

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
clinical-intelligence – AI Agent Skills | Claude Skills