We extract enforcement reports, drug approvals, device clearances, and adverse events from fda.gov databases. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Warning Letters objects from fda.gov. All fields typed and schema-versioned.
"letter_id": "WL-641928", "issue_date": "2026-03-14", "company_name": "PharmaCorp Synthetics Ltd", "issuing_office": "Center for Drug Evaluation and Research", "violative_products": "Unapproved New Drugs", "letter_url": "https://www.fda.gov/inspections/warning-letters/641928"
| # | letter_id | issue_date | company_name | subject | issuing_office | violative_products |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Enforcement Reports objects from fda.gov. All fields typed and schema-versioned.
"recall_number": "D-1425-2026", "product_description": "Aspirin 81mg Tablets, 100 count bottle", "recalling_firm": "HealthMeds LLC", "reason_for_recall": "Presence of foreign particulate matter", "recall_class": "Class II", "status": "Ongoing", "date_initiated": "2026-02-28"
| # | recall_number | product_description | code_info | recalling_firm | reason_for_recall | recall_class |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for 510(k) Clearances objects from fda.gov. All fields typed and schema-versioned.
"k_number": "K240182", "device_name": "Advanced Cardiac Monitor", "applicant": "CardioTech Devices Inc.", "classification_product_code": "MHX", "decision_date": "2026-01-15", "decision": "Substantially Equivalent (SESE)"
| # | k_number | device_name | applicant | contact | regulation_number | classification_product_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Orange Book objects from fda.gov. All fields typed and schema-versioned.
"appl_no": "NDA214589", "product_no": "001", "form": "TABLET;ORAL", "dosage": "50MG", "product_mkt_status": "Prescription", "te_code": "AB", "active_ingredient": "METOPROLOL SUCCINATE"
| # | appl_no | product_no | form | dosage | product_mkt_status | te_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inspections objects from fda.gov. All fields typed and schema-versioned.
"fei_number": "3014582910", "legal_name": "BioManufacturing Partners", "city": "Boston", "country": "United States", "inspection_end_date": "2026-04-02", "classification": "Voluntary Action Indicated (VAI)"
| # | fei_number | legal_name | city | state | country | inspection_end_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our fda.gov scraper navigates legacy government architectures, parses unstructured PDFs, and normalises company names across fragmented databases to deliver clean compliance signals.
Capture metadata and full text from FDA warning letters. We parse HTML pages and run OCR on legacy PDF documents.
Track Class I, II, and III recalls across drugs, devices, and food. Filter by recalling firm, product code, or distribution pattern.
Extract medical device clearance records, applicant details, product codes, and decision dates from the premarket notification database.
Monitor approved drug products, therapeutic equivalence codes, and patent expiration dates to anticipate generic market entry.
Extract adverse event reports for medical devices and drugs to monitor post-market safety signals.
Track facility inspections (OAI, VAI, NAI) globally to monitor supply chain compliance and manufacturing risks.
Navigate legacy FDA search forms automatically. We manage ViewState tokens and session cookies to extract deep paginated results.
Run daily pipelines that only push new or modified records, reducing database bloat and highlighting immediate compliance risks.
We map FEI numbers, applicant names, and product codes across disconnected FDA datasets to create unified entity profiles.
Combine direct web scraping of the latest portal updates with historical bulk data from the OpenFDA API for complete coverage.
Brief in. Clean data out.
Select the FDA databases, specific product codes, or company names you need to monitor.
We configure crawlers to handle FDA search forms, PDF parsing, and pagination limits.
Schema checks ensure entity names, dates, and classification codes meet your normalisation standards.
JSON, CSV, or Parquet files pushed to your S3 bucket or data warehouse on a daily or weekly cadence.
Government sites are notoriously difficult to scrape reliably. Here is how we bypass legacy architecture bottlenecks.
Many FDA databases rely on legacy ASP.NET web forms. Our crawlers capture and submit __VIEWSTATE and __EVENTVALIDATION tokens dynamically, ensuring search queries and deep pagination work flawlessly without session timeouts.
Older warning letters and inspection reports exist only as scanned PDFs. We route these documents through a PyPDF2 and Tesseract OCR pipeline to extract actionable text and metadata into structured JSON.
FDA servers frequently drop connections under load. We implement strict concurrency limits, exponential backoff, and automatic retry queues to ensure complete data extraction without triggering firewall blocks.
A company might be listed under different name variations in the Orange Book versus the Inspections database. We extract standard identifiers like FEI numbers to help you link records across disparate FDA systems.
FDA search interfaces often cap results at 10,000 records. We automatically partition search queries by date ranges or product codes to extract the complete historical dataset.
Track competitor drug approvals, clinical hold notices, and Orange Book patent expirations to inform market entry strategies.
Monitor contract manufacturing organisations (CMOs) for warning letters and OAI inspection classifications to prevent supply disruptions.
Analyse 510(k) clearances to identify trending device categories, predicate devices, and emerging competitors.
Quant funds ingest daily FDA enforcement actions and approval decisions to trade on regulatory events affecting public healthcare equities.
Law firms track warning letters and MAUDE adverse events to identify mass tort litigation opportunities.
Safety teams aggregate FAERS data to detect early signals of adverse drug reactions across patient populations.
"Regulatory intelligence requires absolute precision. Missing a Class I recall or a warning letter is a catastrophic failure for compliance teams."
Extracting data from fda.gov means navigating legacy ASP.NET architectures, unstructured PDF warning letters, and fragmented databases. DataFlirt handles the ViewState tokens, OCR pipelines, and daily diffs so your compliance system always has the latest regulatory signals.
Everything supported by our fda.gov scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Custom Scrapy middlewares maintain ASP.NET session state, handling complex multi-step search forms without timing out.
Documents are downloaded to ephemeral storage, processed via PyPDF2 and Tesseract OCR, and converted into structured JSON fields.
Pipelines run on AWS ECS with Airflow scheduling. Strict rate limiting prevents IP bans while ensuring complete daily data syncs.
Data delivered to where your team already works — no new tooling required.
About fda.gov scraping, legality, and pipeline operations.
Ask us directly →Yes. The data published on fda.gov is public domain government information. We only extract publicly available regulatory records and do not attempt to access gated or confidential submission systems.
While the OpenFDA API is useful, it often suffers from data lag and does not cover all datasets (such as recent warning letters or specific inspection details). Direct scraping ensures you have the absolute latest information as soon as it is published on the portal.
We extract the HTML text where available. For older letters provided only as scanned PDFs, we download the file and run it through an OCR pipeline to extract the text into a searchable JSON field.
Yes. Our pipelines use hash-based diffing. If an ongoing Class II recall is upgraded to Class I, or an inspection status changes, we capture the modification and deliver it in the daily update.
For most enforcement and clearance databases, daily extraction is standard. We can configure specific targeted queries to run hourly if you require immediate alerting for specific companies.
We extract all available identifiers, such as FEI numbers or applicant IDs. While we provide the raw extracted company name exactly as it appears on the FDA site, we can build custom mapping logic to help you link records across different databases.
Government sites change layouts occasionally. Our managed service includes 24/7 pipeline monitoring. If a DOM change breaks an extraction rule, our engineers update the selectors and backfill any missed data to meet our SLA.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually checking government portals. Tell us which FDA databases and entities you need to monitor, and we will build the pipeline.
