// Generate comprehensive drug development progress reports for disease therapeutic targets. Use when user asks about target drug pipeline, clinical trials, or research progress. Triggers on phrases like "target report", "drug development progress", "clinical trial summary", "靶点报告", "药物研发进展", "竞品分析", "专利分析".
Find the most suitable skill for a given biomedical task. Use this skill when: (1) You are unsure which skill to use for a specific biomedical task, (2) You want to discover available skills for a particular domain, (3) You need to compare multiple skills for a given use case.
Generate diverse druggable molecules for a given target or disease using OpenBioMed's AI-powered drug discovery tools. Use this skill when: (1) Generating drug candidates, molecules, or compounds for a target/disease, (2) Performing structure-based drug design or de novo drug design, (3) Finding or creating molecules that bind to a specific protein target, (4) Discovering potential drugs for a disease name, (5) Designing molecules with specific properties (LogP, QED, docking scores). The skill handles target identification, structure retrieval, molecule generation, and in silico evaluation.
Analyze potential drug-drug interactions (DDI) for up to 5 drugs using KEGG DDI database. Use this skill when: (1) Checking interactions between multiple medications, (2) Assessing DDI risk for drug combinations, (3) Understanding interaction mechanisms and severity, (4) Analyzing CYP enzyme involvement in DDIs.
Create new biomedical skills or improve existing ones for the OpenBioMed toolkit. Use this skill when: (1) Creating a new skill from scratch, (2) Capturing a workflow as a reusable skill, (3) Automating a biomedical task, (4) Improving an existing skill. This skill guides through an interactive process: define intent → design workflow → validate with real data → iterate → evaluate.
Query ChEMBL database for bioactivity data on drug-like compounds. Use this skill when: (1) Finding compounds active against a protein target (target-based search), (2) Getting bioactivity profile for a molecule (molecule-based search), (3) Finding drugs for a disease indication (indication-based search).
Identify the IUPAC name of a molecule using BioT5 question answering model. Use this skill when: (1) User wants to find the IUPAC name of a molecule, (2) User asks "What is the IUPAC name?" or "What's the systematic name?", (3) User provides a SMILES string and wants the IUPAC nomenclature.
| name | target-drug-report |
| description | Generate comprehensive drug development progress reports for disease therapeutic targets. Use when user asks about target drug pipeline, clinical trials, or research progress. Triggers on phrases like "target report", "drug development progress", "clinical trial summary", "靶点报告", "药物研发进展", "竞品分析", "专利分析". |
Generate beautiful, comprehensive reports on drug development progress for therapeutic targets.
Features:
from open_biomed.tools.tool_registry import TOOLS
target_name = "CGRP"
# Step 1: Multi-source search
web_search = TOOLS["web_search"]
# Search clinical trials
trial_results, _ = web_search.run(
query=f"{target_name} clinical trial 2024 2025"
)
# Search research papers
paper_results, _ = web_search.run(
query=f"{target_name} discovery mechanism site:pubmed.ncbi.nlm.nih.gov"
)
# Step 2: Generate report
report = generate_target_report(
target=target_name,
output_format="html" # or "markdown"
)
| Section | Description | Key Content |
|---|---|---|
| 🎯 靶点概况 | Target overview | Protein function, diseases |
| 💊 已上市药物 | Approved drugs | Name, company, indication |
| 🏥 临床管线 | Clinical pipeline | Phase distribution, drugs |
| 📚 研究热点 | Research trends | Publications, directions |
| 📜 专利布局 | Patent landscape | Trends, applicants |
| 📊 市场分析 | Market analysis | Size, competition |
| 🔮 投资展望 | Investment outlook | Opportunities, risks |
# Generate HTML report
report = generate_target_report("EGFR", output_format="html")
# Generate Markdown report
report = generate_target_report("KRAS", output_format="markdown")
# Save to file
report = generate_target_report(
target="BCL-2",
output_format="html",
output_path="report.html"
)
When web search is unavailable, uses built-in knowledge for common targets:
target-drug-report/
├── SKILL.md # This file
├── examples/
│ └── basic_example.py # Report generator script
└── references/
├── html_template.py # HTML template
└── data_sources.md # Data source reference