--- name: cancer-therapy-design description: "Cancer Therapy Design - Design cancer therapy: identify targets, find drugs, check safety, and analyze differential expression. Use this skill for oncology tasks involving get associated targets by disease efoId get associated drugs by target name get adverse reactions by drug name tcga differential expression analysis. Combines 4 tools from 3 SCP server(s)." --- # Cancer Therapy Design **Discipline**: Oncology | **Tools Used**: 4 | **Servers**: 3 ## Description Design cancer therapy: identify targets, find drugs, check safety, and analyze differential expression. ## Tools Used - **`get_associated_targets_by_disease_efoId`** from `opentargets-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets` - **`get_associated_drugs_by_target_name`** from `opentargets-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets` - **`get_adverse_reactions_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug` - **`tcga_differential_expression_analysis`** from `tcga-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA` ## Workflow 1. Find cancer targets 2. Get associated drugs 3. Check drug safety 4. Analyze differential expression ## Test Case ### Input ```json { "disease_efo": "EFO_0000311", "query": "lung adenocarcinoma drug targets" } ``` ### Expected Steps 1. Find cancer targets 2. Get associated drugs 3. Check drug safety 4. Analyze differential expression ## Usage Example > **Note:** Replace `` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn). ```python import asyncio import json from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client from mcp.client.sse import sse_client SERVERS = { "opentargets-server": "https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets", "fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", "tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA" } async def connect(url, transport_type): transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": ""}) read, write, _ = await transport.__aenter__() ctx = ClientSession(read, write) session = await ctx.__aenter__() await session.initialize() return session, ctx, transport def parse(result): try: if hasattr(result, 'content') and result.content: c = result.content[0] if hasattr(c, 'text'): try: return json.loads(c.text) except: return c.text return str(result) except: return str(result) async def main(): # Connect to required servers sessions = {} sessions["opentargets-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets", "streamable-http") sessions["fda-drug-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", "streamable-http") sessions["tcga-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", "streamable-http") # Execute workflow steps # Step 1: Find cancer targets result_1 = await sessions["opentargets-server"].call_tool("get_associated_targets_by_disease_efoId", arguments={}) data_1 = parse(result_1) print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}") # Step 2: Get associated drugs result_2 = await sessions["opentargets-server"].call_tool("get_associated_drugs_by_target_name", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Check drug safety result_3 = await sessions["fda-drug-server"].call_tool("get_adverse_reactions_by_drug_name", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Analyze differential expression result_4 = await sessions["tcga-server"].call_tool("tcga_differential_expression_analysis", arguments={}) data_4 = parse(result_4) print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}") # Cleanup print("Workflow complete!") if __name__ == "__main__": asyncio.run(main()) ``` --- Source attribution: InternScience Original project: https://github.com/InternScience/scp/blob/cea5398564032aea65a78e246d06c30ae945e03f/skills/cancer_therapy_design/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Copyright (c) 2024 Anthropic, PBC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: InternScience Original project: https://github.com/InternScience/scp/blob/cea5398564032aea65a78e246d06c30ae945e03f/skills/cancer_therapy_design/SKILL.md Attribution basis: Source repository record Fields of work: Education & Research, Healthcare & Life Sciences, Product Management Roles: Clinical Research, Health Informatics, Medical Writer, Product Manager, Researcher Specialties: API Tools: Fda Drug Server, Opentargets Server, Tcga Server Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: cbbca189c311e7a99c6e19c61c130c7e6072ebf55e065f6cc81203d3aca009df