orphan-drug-analysis

name	orphan_drug_analysis
description	Orphan Drug & Rare Disease Analysis - Analyze orphan drugs: Monarch disease phenotypes, OpenTargets targets, FDA drug data, and clinical studies. Use this skill for orphan drug development tasks involving get joint associated diseases by HPO ID list get associated targets by disease efoId get clinical studies info by drug name pubmed search. Combines 4 tools from 4 SCP server(s).
i18n	{"zh":{"description":"孤儿药与罕见病分析。"}}

Orphan Drug & Rare Disease Analysis

Discipline: Orphan Drug Development | Tools Used: 4 | Servers: 4

Description

Analyze orphan drugs: Monarch disease phenotypes, OpenTargets targets, FDA drug data, and clinical studies.

Tools Used

• get_joint_associated_diseases_by_HPO_ID_list from monarch-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch
• get_associated_targets_by_disease_efoId from opentargets-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets
• get_clinical_studies_info_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
• pubmed_search from search-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search

Workflow

1. Map phenotypes to diseases
2. Find drug targets
3. Get clinical studies
4. Search literature

Test Case

Input

{
    "hpo_ids": [
        "HP:0001250"
    ],
    "disease_efo": "MONDO_0010075",
    "query": "orphan drug seizure disorder"
}

Expected Steps

1. Map phenotypes to diseases
2. Find drug targets
3. Get clinical studies
4. Search literature

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.

import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "monarch-server": "https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch",
    "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",
    "search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_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 (result)
    :  (result)

  ():
    
    sessions = {}
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )

    
    
    result_1 =  sessions[].call_tool(, arguments={})
    data_1 = parse(result_1)
    ()

    
    result_2 =  sessions[].call_tool(, arguments={})
    data_2 = parse(result_2)
    ()

    
    result_3 =  sessions[].call_tool(, arguments={})
    data_3 = parse(result_3)
    ()

    
    result_4 =  sessions[].call_tool(, arguments={})
    data_4 = parse(result_4)
    ()

    
    ()

 __name__ == :
    asyncio.run(main())