FDA De Novo Device Decisions Scraper

Turn the FDA De Novo database into structured regulatory intelligence.

Search recent decisions or look up known DEN###### records, enrich every match from its official detail page, and export the results as JSON, CSV, Excel, XML, or RSS through Apify.

This Actor is built for recurring monitoring as well as one-off device research.

What does FDA De Novo Device Decisions Scraper do?

The Actor reads the public FDA Device Classification Under Section 513(f)(2) database.

It can:

• 🔎 search decisions by requester, device, product code, panel, date, or PCCP status;
• 🎯 look up one or more known De Novo numbers;
• 🧾 enrich search rows with regulation and committee details;
• 🔗 retain official classification-order and decision-summary PDF links;
• 📤 deliver typed records in an Apify dataset;
• ⏰ run on a schedule for repeat monitoring.

Each dataset row represents one FDA De Novo classification decision.

Why use this FDA De Novo scraper?

FDA's search interface is useful for individual lookups, but recurring analysis requires repeatable structured output.

This Actor removes manual copying and joins list-page data with detail-page fields.

Use it to build a decision feed, compare pathways, watch competitors, identify newly created product codes, or populate a regulatory research warehouse.

The source remains the official FDA record, and every row includes its source URL.

Who is it for?

Regulatory affairs teams

Monitor grants, review committees, submission types, and document availability.

Medtech competitive-intelligence teams

Track competitor requesters, novel devices, linked 510(k)s, and emerging product codes.

Investors and strategy teams

Build a time series of novel-device decisions and examine category activity.

Consultants and researchers

Export consistent records across clients, panels, dates, and product areas.

Data engineers

Schedule the Actor and send results to a database, spreadsheet, webhook, or cloud workflow.

What FDA De Novo data can you extract?

Field	Meaning
deNovoNumber	FDA De Novo identifier
deviceName	Submitted device or trade name
deviceClassificationName	FDA classification name
requester	Requesting company or organization
requesterAddress	Address shown by FDA
contact	Public contact shown by FDA
linked510kNumber	Related 510(k), when listed
regulationNumber	Applicable regulation number
productCodes	FDA product classification codes
dateReceived	Date FDA received the request
decisionDate	Decision date
decision	FDA decision text and code
submissionType	Direct or other submission type
classificationAdvisoryCommittee	Classification committee
reviewAdvisoryCommittee	Review committee
pccpAuthorized	Predetermined Change Control Plan authorization
classificationOrderUrl	Official classification-order PDF
decisionSummaryUrl	Official FDA decision-summary PDF
sourceUrl	FDA detail page
scrapedAt	Extraction timestamp

Fields that FDA does not publish for a record are omitted rather than guessed.

How to scrape FDA De Novo decisions

1. Open the Actor in Apify Console.
2. Keep the prefilled DEN230041 for a quick lookup, or clear it to use search filters.
3. Set a low maxItems while testing a workflow.
4. Click Start.
5. Open the default dataset when the run succeeds.
6. Export the data or connect it to another service.

A one-record prefilled run is suitable for validating your setup.

Input options

De Novo numbers

Provide values such as:

["DEN230041", "DEN210003"]

Identifiers must start with DEN and contain six digits.

FDA detail URLs

You can provide official URLs ending in denovo.cfm?ID=DEN######.

URLs outside the FDA De Novo detail surface are rejected.

Search filters

Leave both direct-input fields empty to search.

Available filters include:

• requester name;
• device name;
• three-letter product code;
• advisory panel;
• decision date from and to;
• PCCP authorization.

Maximum decisions

maxItems controls how many detail records are enriched and saved.

The allowed range is 1–500.

Proxy configuration

The FDA blocks some data-center egress.

The Actor defaults to Apify's US SHADER proxy group and rotates sessions on FDA anti-bot responses.

You can select another available group in the standard proxy editor.

Input examples

Look up one known decision

{
  "deNovoNumbers": ["DEN230041"],
  "maxItems": 1
}

Search recent decisions

{
  "deNovoNumbers": [],
  "decisionDateFrom": "01/01/2026",
  "decisionDateTo": "07/21/2026",
  "maxItems": 25
}

Search one product code

{
  "deNovoNumbers": [],
  "productCode": "QZW",
  "maxItems": 10
}

Find PCCP-authorized decisions

{
  "deNovoNumbers": [],
  "pccpAuthorized": "yes",
  "maxItems": 50
}

Output example

{
  "deNovoNumber": "DEN230041",
  "deviceName": "Sleep Apnea Feature",
  "deviceClassificationName": "over-the-counter device to assess risk of sleep apnea",
  "requester": "samsung electronics co., ltd.",
  "contact": "hon pak",
  "regulationNumber": "868.2378",
  "productCodes": ["QZW"],
  "dateReceived": "05/31/2023",
  "decisionDate": "02/06/2024",
  "decision": "granted (DENG)",
  "submissionType": "Direct",
  "classificationAdvisoryCommittee": "Anesthesiology",
  "reviewAdvisoryCommittee": "Anesthesiology",
  "pccpAuthorized": false,
  "classificationOrderUrl": "https://www.accessdata.fda.gov/cdrh_docs/pdf23/DEN230041.pdf",
  "decisionSummaryUrl": "https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN230041.pdf"
}

Values reflect the FDA page at extraction time.

How much does it cost to scrape FDA De Novo decisions?

The Actor uses pay-per-event pricing.

A small start charge covers run initialization, and each successfully saved enriched decision creates one item charge.

Failed pages are not emitted as paid dataset items.

Your Apify pricing tier determines the item rate shown in Console.

Start with one to ten records to estimate workflow cost before scheduling a larger monitor.

Accuracy and data quality

The parser uses FDA's visible field labels rather than relying on column positions in the detail table.

Required identity and decision fields must exist before a record is saved.

The Actor deduplicates De Novo numbers returned by search.

It preserves the official record URL and extraction timestamp for auditing.

It does not infer clinical claims, approval status, or market authorization beyond FDA's published decision text.

Monitoring new FDA decisions

Create a scheduled Apify task with:

• direct identifiers cleared;
• a rolling or recent decision-date range;
• a practical maxItems cap;
• dataset or webhook integration enabled.

For durable incremental monitoring, send completed datasets to your own store and deduplicate on deNovoNumber.

Weekly monitoring is often sufficient for regulatory intelligence workflows.

Tips for reliable runs

• Keep the default proxy enabled.
• Use exact DEN###### lookups when you already know identifiers.
• Use MM/DD/YYYY for date filters.
• Keep initial result limits low.
• Treat PDF links as source documents, not extracted PDF text.
• Retry later if FDA is undergoing maintenance.
• Schedule at conservative frequency to respect the public source.

Integrations

Google Sheets

Use the Google Sheets integration to append newly observed decisions to a tracker.

Slack or Microsoft Teams

Send a webhook when a scheduled run contains a new De Novo number.

Airtable or a CRM

Map requester and device fields into an account or market-intelligence table.

Data warehouses

Load JSON or CSV into BigQuery, Snowflake, Redshift, or PostgreSQL.

Make and Zapier

Trigger downstream workflows after a run succeeds.

Webhooks

Attach a run-succeeded webhook and fetch the default dataset through the API.

Use with the Apify API in Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/fda-de-novo-device-decisions-scraper').call({
  deNovoNumbers: ['DEN230041'],
  maxItems: 1,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Use with the Apify API in Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("automation-lab/fda-de-novo-device-decisions-scraper").call(
    run_input={"deNovoNumbers": ["DEN230041"], "maxItems": 1}
)
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

Use with cURL

curl -X POST \
  "https://api.apify.com/v2/acts/automation-lab~fda-de-novo-device-decisions-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"deNovoNumbers":["DEN230041"],"maxItems":1}'

Read the resulting default dataset after the run completes.

Use through Apify MCP

Connect the Actor to an AI assistant through:

https://mcp.apify.com/?tools=automation-lab/fda-de-novo-device-decisions-scraper

Claude Code

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=automation-lab/fda-de-novo-device-decisions-scraper"

Claude Desktop

Add this server under mcpServers in Claude Desktop's configuration:

{
  "mcpServers": {
    "apify-fda-denovo": {
      "url": "https://mcp.apify.com/?tools=automation-lab/fda-de-novo-device-decisions-scraper"
    }
  }
}

Cursor

Add the same mcpServers JSON in Cursor Settings → MCP, then authenticate with Apify when prompted.

VS Code

Open MCP: Add Server from the command palette, choose HTTP, and paste the MCP URL above.

Example prompts:

• “Look up FDA De Novo record DEN230041 and summarize the regulatory pathway.”
• “Find 2026 De Novo decisions for neurology devices and return official document links.”
• “Compare requester and product-code activity in the latest FDA De Novo records.”

Always verify consequential conclusions against the linked FDA documents.

Error handling

Invalid identifiers and unsupported URLs fail before scraping.

The Actor rotates proxy sessions when FDA returns a 403 or apology page.

A search with no matches fails with a clear message instead of silently returning misleading success.

If every detail extraction fails, the run exits non-zero.

Partial data is saved only when required fields are present.

Legal and ethical use

This Actor accesses publicly available U.S. Food and Drug Administration records.

Use it responsibly, at conservative frequency, and in accordance with Apify's terms and applicable law.

FDA records may be corrected after publication.

Do not treat Actor output as medical, clinical, investment, or legal advice.

Review original FDA pages and documents before making decisions.

This Actor is independent and is not affiliated with or endorsed by the FDA.

Frequently asked questions

Is a De Novo grant the same as a 510(k) clearance?

No. They are different FDA pathways. This Actor reports the source decision text and linked 510(k) number when FDA provides one.

Does the Actor download or parse PDFs?

No. It preserves classification-order and decision-summary URLs. Use a separate PDF extraction workflow if document text is required.

Why did my filtered search return no records?

Check spelling, use MM/DD/YYYY, clear direct De Novo numbers, and broaden one filter at a time. No-match searches fail clearly.

Why was an FDA request blocked?

FDA uses egress-sensitive anti-bot controls. Keep Apify proxy enabled; the Actor rotates sessions automatically on recognized blocks.

Can I monitor only new records?

Schedule a date-filtered task and deduplicate completed datasets by deNovoNumber in your downstream store.

Are all output fields always present?

No. Older or unusual FDA records may omit linked 510(k)s, contacts, PCCP status, or documents.

Can I search more than 500 records?

A run is capped at 500 enriched records. Split large historical work into bounded date ranges.

Related scrapers

• OpenFDA 510(k) Device Clearances Scraper for the distinct 510(k) clearance pathway.
• OpenFDA Drug NDC Directory Scraper for drug product directory data.
• OpenFDA Scraper for supported openFDA datasets.

Choose this Actor when the entity of interest is specifically an FDA De Novo classification decision.

Support

If a valid FDA De Novo record is missing a published field, open an issue from the Actor page.

Include the De Novo number, input, run ID, and expected FDA field.

Do not include confidential medical or business information.

Source-page changes can then be reproduced and addressed precisely.