Inclusion Criteria Generator

Generate and optimize clinical trial subject inclusion/exclusion criteria to balance scientific rigor with recruitment feasibility.

Use Cases

• - Protocol Design: Create initial eligibility criteria for new clinical trials
• Criteria Optimization: Refine existing criteria to improve enrollment without compromising safety/efficacy
• Competitive Analysis: Analyze eligibility patterns across similar trials
• Recruitment Strategy: Identify and mitigate barriers to enrollment
• Feasibility Assessment: Evaluate if proposed criteria are realistic for target population

Usage

CLI Usage

CODEBLOCK0

Python API

CODEBLOCK1

Input Format

Study Design Parameters

CODEBLOCK2

Existing Criteria Format

CODEBLOCK3

Output Format

Generated/Optimized Criteria

CODEBLOCK4

Criteria Categories

Category	Description	Examples
demographics	Age, sex, race, ethnicity	Age 18-75, women of childbearing potential
disease_severity

Disease stage, severity markers | HbA1c range, tumor stage, NYHA class | | medical_history | Prior conditions, comorbidities | No cardiovascular events within 6 months | | concomitant_meds | Allowed/prohibited medications | Stable metformin dose allowed | | laboratory | Lab value requirements | eGFR > 30 mL/min, normal liver function | | lifestyle | Diet, exercise, habits | Non-smoker, willing to maintain diet | | compliance | Ability to participate | Able to provide informed consent | | safety | Risk minimization criteria | No history of severe hypoglycemia |

Optimization Strategies

Common Modifications

Issue	Strategy	Example
Narrow age range	Widen limits	18-70 → 18-75 years
Restrictive lab values

Adjust thresholds | eGFR > 60 → eGFR > 30 mL/min | | Comorbidity exclusions | Add time limits | Exclude "current" vs "history of" | | Medication washouts | Shorten periods | 4 weeks → 2 weeks | | Geographic barriers | Add telemedicine | Include remote visits option |

Retention Considerations

• - Minimize visit frequency when possible
• Allow window periods for visit timing
• Provide transportation assistance language
• Consider patient-reported outcome burden

Technical Details

• - Difficulty: Medium
• Standards: ICH E6(R2) GCP, CDISC Protocol Representation Model
• Data Sources: ClinicalTrials.gov eligibility patterns, literature feasibility data
• Dependencies: None (pure Python)

References

• - references/criteria_templates.json - Templates by therapeutic area
• INLINECODE1 - Best practices for criteria optimization
• INLINECODE2 - Frequent eligibility design mistakes
• INLINECODE3 - FDA/EMA guidance on eligibility criteria
• INLINECODE4 - Screen failure rates by criterion type

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python scripts with tools	High
Network Access

External API calls | High | | File System Access | Read/write data | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Data handled securely | Medium |

Security Checklist

• - [ ] No hardcoded credentials or API keys
• [ ] No unauthorized file system access (../)
• [ ] Output does not expose sensitive information
• [ ] Prompt injection protections in place
• [ ] API requests use HTTPS only
• [ ] Input validated against allowed patterns
• [ ] API timeout and retry mechanisms implemented
• [ ] Output directory restricted to workspace
• [ ] Script execution in sandboxed environment
• [ ] Error messages sanitized (no internal paths exposed)
• [ ] Dependencies audited
• [ ] No exposure of internal service architecture

Prerequisites

CODEBLOCK5

Evaluation Criteria

Success Metrics

• - [ ] Successfully executes main functionality
• [ ] Output meets quality standards
• [ ] Handles edge cases gracefully
• [ ] Performance is acceptable

Test Cases

1. 1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• - Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:

- Performance optimization - Additional feature support

Parameters

Parameter	Type	Default	Description
INLINECODE5	str	Required	Therapeutic indication
INLINECODE6

str | Required | | | --population | str | "adults" | Target population | | --duration | str | "" | Study duration | | --output | str | Required | Output file path | | --age-min | int | 18 | Minimum age | | --age-max | int | 75 | Maximum age | | --input | str | Required | Input criteria JSON file | | --enrollment-target | int | Required | Target enrollment | | --current-enrollment | int | Required | Current enrollment | | --output | str | Required | Output file path | | --input | str | Required | Input criteria JSON file | | --output | str | Required | Output file path | | --input | str | Required | Input criteria JSON file | | --condition | str | Required | Medical condition | | --output | str | Required | Output file path |