← 返回
未分类

Ib Summarizer

Summarize core safety information from Investigator's Brochures for clinical researchers
为临床研究人员总结研究者手册中的核心安全信息
aipoch-ai aipoch-ai 来源
未分类 clawhub v0.1.0 1 版本 99761.3 Key: 无需
★ 0
Stars
📥 418
下载
💾 4
安装
1
版本
#latest

概述

IB Summarizer

Description

Summarize core safety information from Investigator's Brochures (IB), helping clinical researchers quickly obtain key drug safety data.

Functions

  • Extract Core Safety Information (CSI) from IB documents
  • Identify and summarize:
  • Known Adverse Drug Reactions (ADRs) and their incidence rates
  • Contraindications
  • Warnings and Precautions
  • Drug Interactions
  • Special population precautions
  • Overdose Management
  • Important safety updates

Usage

python scripts/main.py <input_file> [options]

Parameters

ParameterTypeDefaultRequiredDescription
-------------------------------------------------
input_filestring-YesIB document path (PDF/Word/TXT)
-o, --outputstringstdoutNoOutput file path
-f, --formatstringmarkdownNoOutput format (json, markdown, text)
-l, --languagestringzhNoOutput language (zh, en)

Examples

# Basic usage
python scripts/main.py /path/to/IB.pdf

# Output to JSON file
python scripts/main.py /path/to/IB.pdf -o summary.json -f json

# English output
python scripts/main.py /path/to/IB.docx -l en -o summary.md

Output Structure

Markdown Format

# IB Safety Information Summary

## Basic Drug Information
- **Drug Name**: XXX
- **Version**: X.X
- **Date**: YYYY-MM-DD

## Core Safety Information

### Known Adverse Reactions
| System Organ Class | Adverse Reaction | Incidence | Severity |
|-------------|---------|--------|---------|
| ... | ... | ... | ... |

### Contraindications
- ...

### Warnings and Precautions
- ...

### Drug Interactions
- ...

### Special Populations
| Population | Precautions |
|-----|---------|
| Pregnant women | ... |
| Lactating women | ... |
| Children | ... |
| Elderly | ... |
| Hepatic/renal impairment | ... |

### Overdose
- Symptoms: ...
- Management: ...

### Safety Update History
| Version | Date | Update Content |
|-----|------|---------|
| ... | ... | ... |

JSON Format

{
  "drug_info": {
    "name": "Drug Name",
    "version": "Version Number",
    "date": "Date"
  },
  "core_safety_info": {
    "adverse_reactions": [...],
    "contraindications": [...],
    "warnings": [...],
    "drug_interactions": [...],
    "special_populations": {...},
    "overdose": {...},
    "safety_updates": [...]
  }
}

Dependencies

  • Python 3.8+
  • PyPDF2 / pdfplumber (PDF parsing)
  • python-docx (Word parsing)
  • Optional: openai / anthropic (for AI-enhanced extraction)

Installation

pip install -r requirements.txt

Notes

  1. Input documents should be readable PDF or Word format
  2. Scanned PDFs require OCR processing first
  3. For complex table structures, manual verification may be needed
  4. Information extracted by this tool is for reference only and does not constitute medical advice

Risk Assessment

Risk IndicatorAssessmentLevel
-----------------------------------
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • [ ] No hardcoded credentials or API keys
  • [ ] No unauthorized file system access (../)
  • [ ] Output does not expose sensitive information
  • [ ] Prompt injection protections in place
  • [ ] Input file paths validated (no ../ traversal)
  • [ ] Output directory restricted to workspace
  • [ ] Script execution in sandboxed environment
  • [ ] Error messages sanitized (no stack traces exposed)
  • [ ] Dependencies audited
  • Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

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

Test Cases

  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

版本历史

共 1 个版本

  • v0.1.0 当前
    2026-03-31 06:46 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

data-analysis

Survival Analysis (KM)

aipoch-ai
生成Kaplan‑Meier生存曲线,计算生存统计量(log‑rank检验、中位生存时间),并估算临床及生物...的 hazard ratios。
★ 2 📥 973
professional

Stock Analysis

udiedrichsen
{"answer":"基于雅虎财经数据,分析股票与加密货币。支持投资组合管理、自选股预警、股息分析、8维评分、热门趋势扫描及传闻/早期信号探测。适用于股票分析、持仓追踪、财报异动、加密监控、热门股追踪或提前发掘非主流传闻。"}
★ 277 📥 57,428
professional

A股量化 AkShare

mbpz
A股量化数据分析工具,基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
★ 185 📥 61,944