FDA 510(k) Clearances API: Medical Device Intelligence by Company, Device, or Product Code

Every medical device cleared for US sale through the 510(k) pathway is recorded in the FDA’s public database. Our FDA 510(k) Scraper searches that database by company, device name, or product code and returns structured clearance records for competitive intelligence, regulatory tracking, and due diligence.

What is a 510(k) clearance

The 510(k) premarket notification is the FDA pathway for devices that are substantially equivalent to a legally marketed predicate device. It covers a wide range of products from diagnostic imaging equipment to surgical instruments to in vitro diagnostics. The FDA has processed over 500,000 510(k) submissions since the program began.

What you get per clearance

• k_number — the 510(k) decision number (e.g. K242345)
• applicant — company that submitted the clearance
• device_name — device name as submitted
• decision — SESE (Substantially Equivalent) or NSE (Not Substantially Equivalent)
• decision_date — date of FDA decision
• product_code — FDA product classification code
• regulation_number — CFR regulation number
• submission_type — Traditional, Abbreviated, or Special 510(k)
• scraped_at — ISO timestamp

Python example

import requests, time

run = requests.post(
    "https://api.apify.com/v2/acts/themineworks~fda-510k-device-clearances/runs",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"},
    json={
        "company": "Medtronic",
        "maxResults": 100
    }
)

run_id = run.json()["data"]["id"]

while True:
    r = requests.get(
        f"https://api.apify.com/v2/actor-runs/{run_id}",
        headers={"Authorization": f"Bearer {APIFY_TOKEN}"}
    ).json()
    if r["data"]["status"] in ("SUCCEEDED", "FAILED"):
        break
    time.sleep(5)

clearances = requests.get(
    f"https://api.apify.com/v2/actor-runs/{run_id}/dataset/items",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"}
).json()

for c in clearances:
    print(c["k_number"], c["device_name"], c["decision_date"])

Track clearances by product code

import pandas as pd

df = pd.DataFrame(clearances)
df["decision_date"] = pd.to_datetime(df["decision_date"], errors="coerce")

# Clearances per year for this company
by_year = df.groupby(df["decision_date"].dt.year).size()
print(by_year)

# Most common product codes
print(df["product_code"].value_counts().head(10))

Monitor a product category

# Pull all recent clearances in a product category
run = requests.post(
    "https://api.apify.com/v2/acts/themineworks~fda-510k-device-clearances/runs",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"},
    json={
        "productCode": "QFN",   # e.g. continuous glucose monitors
        "dateFrom": "2024-01-01",
        "maxResults": 200
    }
)

Parameters

Parameter	Default	Notes
company	—	Applicant company name (partial match)
deviceName	—	Device name keyword
productCode	—	FDA 3-letter product code
dateFrom	—	Filter decisions after this date (YYYY-MM-DD)
maxResults	100	Maximum clearances to return

Use cases

Competitive intelligence. Map every 510(k) clearance filed by a competitor in the past 5 years. Identify which product categories they are entering and how quickly they move from submission to clearance.

Market entry analysis. Before entering a device category, pull all cleared devices with the same product code to understand the competitive landscape and which predicates are most commonly cited.

M&A due diligence. During acquisition of a medtech company, verify their 510(k) portfolio against the FDA database. Cross-reference claimed clearances against actual k_numbers.

Regulatory strategy. Identify the predicate devices most frequently cited in successful clearances within your product category to inform your own 510(k) submission strategy.

Sales intelligence. Target medtech startups that just received their first clearance — they’re about to commercialize and may need distribution, manufacturing, or services partners.

Pricing

$0.003 per clearance record. Empty searches are not charged.

Available on Apify.