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orphan_drug_analysis

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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).

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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 sk-b04409a1-b32b-4511-9aeb-22980abdc05c with your own SCP Hub API Key. You can obtain one from the SCP Platform.

import asyncio
import json
from contextlib import AsyncExitStack
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, stack):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
    read, write, _ = await stack.enter_async_context(transport)
    ctx = ClientSession(read, write)
    session = await stack.enter_async_context(ctx)
    await session.initialize()
    return session

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():
    async with AsyncExitStack() as stack:
        # Connect to required servers
        sessions = {}
        sessions["monarch-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/16/Origene-Monarch", stack)
        sessions["opentargets-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets", stack)
        sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)
        sessions["search-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search", stack)

        # Execute workflow steps
        # Step 1: Map phenotypes to diseases
        result_1 = await sessions["monarch-server"].call_tool("get_joint_associated_diseases_by_HPO_ID_list", arguments={})
        data_1 = parse(result_1)
        print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

        # Step 2: Find drug targets
        result_2 = await sessions["opentargets-server"].call_tool("get_associated_targets_by_disease_efoId", arguments={})
        data_2 = parse(result_2)
        print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

        # Step 3: Get clinical studies
        result_3 = await sessions["fda-drug-server"].call_tool("get_clinical_studies_info_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: Search literature
        result_4 = await sessions["search-server"].call_tool("pubmed_search", 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())