Orphanet Rare Diseases Scraper

Orphanet Rare Diseases Scraper

Scrape detailed rare-disease records from Orphanet by ORPHAcode or from the latest Orphadata list. Every disease comes with its preferred term, synonyms, definition, epidemiological data and classification in one flat row. Export to CSV, JSON, Excel, or XML.

The Orphanet knowledge base is the reference for rare-disease nomenclature and epidemiology, but collecting its structured data manually means clicking through hundreds of pages. This scraper reads the public Orphadata endpoints and Orphanet clinical overview pages directly, giving you clean disease records filtered by language, with optional ORPHAcode targeting. Biomedical researchers, clinical-trials coordinators, and pharma-analytics teams get the definitions and classification they need in a fixed schema.

Who uses it	What they scrape Orphanet for
Clinical researchers	Build a reference list of rare-disease definitions and epidemiological estimates for study protocols.
Pharma market analysts	Identify candidate rare diseases for drug repurposing or co-morbidity analysis.
Bioinformaticians	Feed clean Orphanet disease records and cross-references into knowledge graphs or data platforms.
Medical writers	Source up-to-date Orphanet definitions and synonyms for regulatory submissions or patient-facing content.

What it does

This Actor collects Orphanet rare-disease records by ORPHAcode or from the latest Orphadata list, and returns each disease as one flat row with its preferred term, synonyms, definition and epidemiological details.

• 🎯 Targeted pull: supply specific ORPHAcodes like 558 for Marfan syndrome or 93 for Huntington disease.
• 🔄 Latest-record sweep: leave ORPHAcodes empty and the scraper automatically pulls records from the Orphadata list endpoint.
• 🌐 Multi-language support: choose from English, French, German, Spanish, Italian, Dutch, Polish, Portuguese and Czech for preferred terms and definitions.
• 📦 Fixed flat schema: each disease returns as one row, ready for CSV, JSON, Excel or XML export.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Orphanet data

🧬 Populate a rare-disease knowledge graph.

A bioinformatics team runs the scraper weekly via the list endpoint, building a graph of disease nodes enriched with Orphanet definitions, synonyms and cross-references.

📋 Support clinical study design.

A CRO downloads epidemiological data and age-of-onset for a batch of ORPHAcodes to screen rare-disease populations for feasibility.

💊 Prioritize drug repurposing candidates.

A pharma analyst collects the full classification and prevalence data for hundreds of rare diseases, then joins it with internal drug-target mapping to rank opportunities.

📑 Source definitions for regulatory documents.

A medical writer pulls the official Orphanet definition and synonyms for a specific ORPHAcode in French and English for use in a European HTA submission.

Why choose this scraper

	What you get
Preferred term and synonyms	Obtain the standard Orphanet disease name and all linked synonyms in your chosen language.
Classification codes	Receive the ORPHAcode, ICD-10 mappings, OMIM links and UMLS CUI for each record.
Definition and epidemiology	Capture the clinical definition, age of onset, prevalence and inheritance data.
Flat, analysis-ready rows	No nested JSON traversal: one disease equals one row in your dataset.

How it compares

The Rare Disease Lookup actor queries several knowledge bases for cross-references. This actor focuses on the full Orphanet clinical-overview record, including epidemiological detail and multi-language support.

Feature	ParseForge	Rare Disease Lookup - OMIM + Orphanet + MedGen API
Native Orphanet clinical-overview page parsing	Yes	Not listed
Epidemiological data per disease	Yes, including prevalence class, age of onset and inheritance	Not listed
Multi-language disease terms and definitions	Yes, 9 European languages	Not listed
Automatic latest-record pull from Orphadata list	Yes, without entering codes	Not listed
Cross-references to OMIM, ICD-10 and UMLS	Yes	Yes
ORPHAcode-targeted scraping	Yes, per-code	Not listed

Configure the run

Drive the Actor with a list of ORPHAcodes or let it pull the latest records automatically. Filters run per-record so only the diseases you need reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
 "orphaCodes": [
 "558",
 "61",
 "141",
 "93",
 "118"
 ],
 "maxItems": 10
}

A larger pull:

{
 "orphaCodes": [
 "558",
 "61",
 "141",
 "93",
 "118"
 ],
 "maxItems": 200
}

Pricing

Pay-per-result: $0.006 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.60
1,000 results	$6.00
10,000 results	$60.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Orphanet Rare Diseases Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Orphanet through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/orphanet-rare-diseases-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

I entered my ORPHAcodes but got an empty dataset.

Double-check the codes on the Orphanet website. A missing digit or an invalid code will cause the page to return a 404, and the actor skips the record. Try running with the list-endpoint mode first to verify that real codes are returned.

My dataset has fewer rows than expected.

The Maximum diseases field limits the total collected per run. If you left ORPHAcodes empty and your limit was low, raise the max-items value and re-run.

I need the French definition but got English text.

Check that you set the Language input to French before starting the run. The default is English, and changing it after input does not affect a queued run.

Running the actor with an empty ORPHAcodes list takes a long time.

The list-endpoint returns many records. Set a realistic Maximum diseases number for your first test, such as 10, then scale up once you are confident in the output shape.

The prevalence field says 'Not yet documented' or is empty.

Orphanet does not have epidemiological data for every disease. The actor copies whatever text the clinical overview page provides, including notes like 'Not yet documented'.

FAQ

Question	Answer
What is an ORPHAcode?	ORPHAcodes are unique, stable identifiers that Orphanet assigns to each rare disease. You can use them as input to target a specific disease record, such as 558 for Marfan syndrome. When you leave ORPHAcodes empty, the scraper fetches records automatically from the Orphadata list endpoint.
Does this actor need an API key?	No. The scraper reads the public Orphanet clinical overview pages and the open Orphadata endpoints directly. No registration or token is required.
Can I choose the language for the disease data?	Yes. You can set the language to English, French, German, Spanish, Italian, Dutch, Polish, Portuguese or Czech. The preferred term, synonyms and definition fields are returned in the language you select.
How do I scrape all rare diseases on Orphanet?	Leave the ORPHAcodes field empty and the actor will pull the latest rare-disease records from the Orphadata list endpoint. Set a maximum-diseases number to control the volume per run.
What epidemiological data is included?	The row includes the disease definition, prevalence class, age of onset, inheritance pattern and cross-references like ICD-10 codes, OMIM identifiers and UMLS CUIs.
Can I run this on a schedule?	Yes. You can set the actor to run daily or weekly from the Apify platform. Orphanet updates its knowledge base regularly, and the list-endpoint mode will capture the latest records each time.
Does the scraper follow links to disability or functional data?	The actor is focused on the clinical overview page: the definition, synonyms, epidemiology and classification. Deeper pages like disability and functional consequences are not collected.
What format are the results in?	You can export your dataset to CSV, JSON, Excel or XML from the Apify console or through the API.
How many diseases can I scrape in one run?	You set the maximum with the Maximum diseases field, up to one million records. The list-endpoint mode respects this limit and stops when it is reached.
Does the actor handle 404 errors for invalid ORPHAcodes?	If you supply an ORPHAcode that Orphanet does not recognize, the actor logs the issue and continues with the next code. Your dataset contains only successfully fetched records.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by INSERM (Orphanet). It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.