name: clinical-data-extractor
description: Extract clinical trial data from pharmaceutical conference websites or PDF documents. Use when user provides a URL or PDF file containing innovative drug clinical trial data and needs structured extraction of: drug name, manufacturer, indication, clinical phase, trial name, conference, efficacy and safety data (presented as tables), and markdown output to "药品名称@适应症.md" file.
Clinical Data Extractor
Overview
This skill enables extracting structured clinical trial data from pharmaceutical conference websites (ASCO, ESMO, EHA, etc.) and saving it as a markdown file with standardized format.
Configuration
输出路径: ~/.openclaw/workspace
命名格式: {药品名称}@{适应症}.md
文件名清理规则:
常见终点缩写列表 - 以下缩写在表格中无需写中文全称：
- ORR (客观缓解率)
- cORR (确认缓解率)
- DCR (疾病控制率)
- mPFS/rPFS (中位无进展生存期)
- mOS (中位总生存期)
- mDOR (中位缓解持续时间)
- PSA50/PSA90 (PSA缓解率)
- CR (完全缓解)
- PR (部分缓解)
- SD (疾病稳定)
- PD (疾病进展)
- AE (不良事件)
⚠️ 如需修改配置，请直接编辑本配置区域
⚠️ 注意：~ 需在执行时展开为实际用户 home directory
⚠️ 注意：不在列表中的终点数据应写中文全称以清晰说明
⚠️ 注意：本技能会尝试自动提取网页图片，但对于受限平台（微信公众号等）需要手动截图
Requirements
This skill requires the following tools to be available in the OpenClaw runtime environment:
Core Dependencies
- browser: Built-in OpenClaw tool for webpage automation and content extraction (no installation required)
- Requires: Chrome browser installed on the host system
- Usage:
browser action=start profile=openclaw target=host
- read/write: Built-in OpenClaw tools for file operations (no installation required)
Browser System Requirements
For browser automation to work correctly:
- Chrome browser: Must be installed on the host system (typically at
/usr/bin/google-chrome or similar path)
- Display server: Desktop environment with X11/Wayland (for non-headless mode) or headless mode support
- Network connectivity: Required for loading webpages
Optional Dependencies (For PDF Processing)
The following tools are used for PDF extraction. The skill will attempt each method in order:
-
nano-pdf CLI (recommended)
- Installation: Usually pre-installed with OpenClaw
- Alternative: If unavailable, file size reduction or OCR may be needed for scanned PDFs
-
pdftotext (poppler-utils)
- Installation (Debian/Ubuntu):
sudo apt-get install poppler-utils
- Installation (macOS):
brew install poppler
- Used as fallback if nano-pdf is not available
Filesystem Requirements
- Write access to user home directory: The skill creates markdown files and image files in the configured output path (default:
~/.openclaw/workspace)
Configuration Flexibility
All configuration options are defined in the Configuration section above and can be modified without reinstalling the skill:
- 输出路径 (Output path)
- 命名格式 (Filename format)
- 文件名清理规则 (Filename sanitization rules)
- 常见终点缩写列表 (Common endpoint abbreviations)
When to Use
Use this skill when:
- User provides a URL to a pharmaceutical conference website or clinical trial publication (ASCO, ESMO, EHA, WCLC, AACR, etc.) containing clinical trial data
- User provides a PDF file containing clinical trial data
- User requests to extract structured clinical trial data from webpages or PDFs
- User mentions keywords like "临床数据", "临床试验", "clinical data", "clinical trial", or similar requests
Examples of trigger phrases:
- "提取临床数据"
- "把这份PDF里的临床试验信息整理一下"
- "Extract clinical trial data from this URL/PDF"
Workflow
Step 1: Detect Input Type and Extract Content
Determine if user provided a URL or a PDF file.
Case A: User provides a URL
Use the built-in browser to open and extract page content:
-
Start browser (if not already running):
browser action=start profile=openclaw target=host
-
Navigate to URL:
browser action=open targetUrl=<provided-url>
-
Capture page snapshot to extract content:
browser action=snapshot format=markdown
-
Optional: Take screenshot for visual reference:
browser action=screenshot fullPage=true
Case B: User provides a PDF file
Extract text content from the PDF. Two approaches available:
Approach 1: Use nano-pdf CLI (read-only)
nano-pdf --file <path-to-pdf> --action read
Approach 2: Use nano-pdf with natural language instructions
nano-pdf --file <path-to-pdf> --action edit --instruction "Extract all text content from this PDF, focusing on clinical trial data including drug name, indication, phase, efficacy, and safety results"
Note: The extracted PDF content will be in raw text format. You may need to clean up formatting before proceeding to extraction.
Step 2: Extract Key Information
Analyze the fetched content and extract the following fields. Leave blank if information is not available:
- 药品名称 (Drug Name)
- 生产厂家 (Manufacturer)
- 适应症 (Indication)
- 临床阶段 (Clinical Phase)
- 临床名称 (Trial Name)
- 学术会议 (Academic Conference)
- 药品有效性和安全性 (Efficacy and Safety)
Handling Clinical Data Images
网页图片：
- 公开网站（ASCO、ESMO、EHA 等）：识别网页中直接显示的临床数据图片（如疗效曲线、安全性图表），尝试提取图片 URL 并引用
- 受限平台（微信公众号等）：这些平台通常会禁止图片链接的外部访问，无法直接提取图片 URL。在此情况下：
- 在文档中添加图片说明，提示用户手动截图
- 提供参考图片的描述（如"疗效数据图"、"安全性汇总表"等）
- 如果需要获取原图，建议用户手动截图保存
图片处理的两种方式：
方式一：自动提取（适用于公开网站）
方式二：手动截图（适用于受限平台或提取失败时）
## 临床数据图片
⚠️ 无法自动提取图片（受限平台或提取失败），建议手动截图保存。
参考图片描述：
1. 疗效数据图（如 rPFS 曲线、OS 曲线）
2. 安全性汇总表（AE 发生率、严重 AE）
截图保存路径示例：
```markdown
PDF 图片：
- 识别 PDF 中直接显示临床数据的图片页面
- 重要：PDF 中的图片无法自动提取，需要手动截图保存
- 使用截图工具保存图片到输出目录（与 markdown 文件同目录）
- 在 markdown 中用本地路径引用：
For effectiveness and safety data, present findings in markdown table format:
## 药品有效性和安全性
| 指标 | ABC001 | 对照组 | HR | p-value |
|------|----------------|--------|------|------|
| N | 100 | 50 | - | - |
| ORR | 41.4% | 25.3% | - | <0.0001 |
| cORR | 34.5% | - | - | <0.0001 |
| DCR | 87.9% | - | - | <0.0001 |
| mPFS | 11.3 | 6.8 | 0.62 | <0.0001 |
| mOS | 22.1 | 14.2 | 0.73 | <0.0001 |
| 最常见AE | 恶心、血液事件（1-2级） | - | - | - |
多剂量组示例：
| 指标 | AAB001 2mg | AAB001 4mg | AAB001 6mg | Placebo |
|------|----------|--------------|--------------|--------------|
| N | 50 | 50 | 50 | 50 |
| OS | 12.1 | 14.2 | 17.3 | 0.2 |
| OS p-value | <0.0001 | <0.0001 | <0.0001 | - |
| PFS | 12.1 | 14.2 | 17.3 | 0.2 |
| PFS p-value | <0.0001 | <0.0001 | <0.0001 | - |
表格格式规范：
- 表格内容第一行必须列出各组入组人数，指标列写"N"
- 关键原则：确保同一列的数据与该列标题对应的cohort一致
- 重要规则：必须明确标注cohort的具体信息（如剂量组、治疗方案等），避免使用"最大剂量组"、"高剂量组"等笼统表述
- ❌ 错误：
AAB001 (最大效果) 或 高剂量组
- ✅ 正确：
AAB001 6mg 或 对照组
- 不同终点可能基于不同分析人群（如总人群 vs 可评估人群），需分别分列
- 缺乏的数据标注 "N/A"，不要将不同人群的数据混用
- 合并主要终点、次要终点、安全性到一个表格
- 列名：
["指标", "实验组1", "实验组2", ...] 或 ["指标", "实验组", "对照组"]（如有对照）
- 常见终点使用英文缩写（见 Configuration 中的"常见终点缩写列表"）
- 不常见的终点写中文全称
- 不要写95% CI置信区间
- 时间指标（PFS/OS/DOR等）只写数字，不写单位（如
11.3 而非 11.3个月）
- 百分比保留一位小数（如
41.4%）
- 数值不存在的用
N/A 或 NE（未成熟/未评估）表示
- 可在数值后用括号标注实际样本量（如
11.3 (N=82)）
Step 3: Save as Markdown File
Generate output file using the configuration from Configuration section:
- Filename format: Follow the 命名格式 from Configuration section
- Sanitize filename:
- Replace spaces with underscores
- Remove special characters
- Final save path: Use the 输出路径 from Configuration section, followed by the generated
{filename}, then expand ~ to actual home directory.
Step 4: Generate Expert Commentary (Optional but Recommended)
From a medical/pharmaceutical expert perspective, provide a concise analysis of the clinical trial data. This section should be clearly marked as "（仅供参考）" (For reference only).
Key aspects to analyze:
-
Efficacy Evaluation
- Did primary endpoints reach statistical significance?
- Are the effect sizes clinically meaningful?
- How does it compare to existing therapies in the same indication?
-
Safety Considerations
- Is the safety profile acceptable?
- Any concerning AEs?
- How does it compare to the drug class safety profile?
-
Study Design Assessment
- Is the trial design appropriate?
- Is sample size adequate?
- Are control groups appropriate?
- Any limitations?
-
Clinical Prospects
- What's the potential for FDA/NMPA approval?
- Commercial potential?
- What clinical development pathway comes next?
-
Cautions & Limitations
- Data limitations
- What still needs to be validated
Provide concise, objective analysis (3-6 bullet points). Avoid over-optimistic language.
Step 5: File Content Structure
The generated markdown file should follow this template:
# {药品名称} - {适应症} 临床数据
## 基本信息
| 字段 | 内容 |
|------|------|
| 药品名称 | {药品名称} |
| 生产厂家 | {生产厂家} |
| 适应症 | {适应症} |
| 临床阶段 | {临床阶段} |
| 临床名称 | {临床名称} |
| 学术会议 | {学术会议} |
## 药品有效性和安全性
| 指标 | {实验组名称} |
|------|--------------|
| 主要终点数据... | 值 |
| 次要终点数据... | 值 |
| 安全性数据... | 值 |
## 试验设计
| 设计要素 | 内容 |
|----------|------|
| 研究类型 | ... |
| 入组人数 | ... |
## 临床数据图片
{网页图片链接或PDF截图引用}
## 专家点评
（仅供参考）
从药学/医学专家角度分析该临床数据的意义：
- **疗效评价**：[分析主要终点结果是否达到临床意义，对比同类药物]
- **安全性考量**：[分析安全性概况，关注关键AE]
- **研究设计评价**：[研究设计是否合理、样本量是否充足、对照组选择等]
- **临床前景**：[基于当前数据评估药物商业化潜力及后续研究方向]
- **注意事项**：[数据的局限性、需要进一步验证的点等]
## 数据来源
{URL或PDF路径}
提取时间: {当前日期}
Tips
- 配置修改: 输出路径、命名格式、常见缩写列表在 Configuration 区域定义，直接编辑即可修改
- 输出文件位置: 查看 Configuration 区域的
输出路径 设置
- 终点缩写规则: 只对 Configuration 中"常见终点缩写列表"内的缩写使用英文，其他终点写中文全称
- 浏览器使用: 网页提取使用内置浏览器，启动时指定
target=host 参数。如果浏览器未运行，skill 会自动启动
- Use memory_search to check if similar drugs have been processed before extracting
- If the content (webpage or PDF) contains multiple drugs or trials, clarify with user which one to extract
- For complex clinical endpoints, preserve original terminology and units
- 图片处理注意事项:
- 网页图片：提取原始 URL，在 markdown 中直接引用
 或 <URL>（避免大图预览）
- PDF 图片：截图保存到与 markdown 同目录，使用相对路径引用
- 图片命名：使用药品名称+序号，如
PD-1抑制剂_图表1.png
- 只有临床数据相关的图片需要保存，装饰性图片可以忽略
- PDF 处理注意事项:
- PDF 提取的文本格式可能比较混乱，需要适当清理换行和空格
- 表格数据在 PDF 中可能无法完整保留，需要根据上下文推断
- 如果 PDF 是扫描图片，nano-pdf 可能无法提取文本，需要先 OCR 处理
- 对于大型 PDF 文件，可以先使用
--action read 快速提取全文内容
Not every skill requires all three types of resources.
