FDA Exclusivity Dataset

FDA Exclusivity Data, Built for Analysts

Small-molecule drugs (NDA/ANDA) and biologics (BLA) in one queryable SQLite database. Enriched with USPTO patents, FDA drug labels, and normalized company data. Full monthly change history from both sources.

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Try the Interactive Dashboard

Explore drugs and biologics losing exclusivity over the next five years. The full export covers NDA and BLA applications, monthly change history (Orange Book from October 2023, Purple Book from May 2020), pre-computed LOE estimates across both sources, USPTO patent details, and FDA label data.

Explore a Sample of the Data

250 products from 147 companies

Representative sample. The full dataset covers all NDA, ANDA, and BLA applications. 50,397 products with monthly change history, USPTO patent detail, structured label data, and unified LOE estimates across small-molecule and biologic drugs.

Exclusivity Timeline (2026–2031)

Click any bar to filter the table by month. Click a company below to filter the chart.

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Use Cases

What You Can Do With It

Structured for direct analysis. No data cleaning, no manual joins required.

Economics and Strategy Consulting

  • ● Pulling all NDA and BLA drugs losing exclusivity in the next 5 years is one query against all_loe_estimates
  • ● Reconstruct a drug's patent position as of any month in the last 31 months for litigation or regulatory work
  • ● Support client due diligence with primary-source FDA records
  • ● Query biologic and small-molecule exclusivity from a single dataset, no separate sources to join

Investment Research

  • ● Rank a company's patent cliff by product using all_loe_estimates joined to the ticker field
  • ● Join RxCUI and NDC fields to claims or formulary data for utilization and revenue modeling
  • ● Map competitive generic entry using first_generic_entry dates and generic_count by formulation
  • ● Biologic LOE dates are in the same table as small-molecule NDAs, queryable by sponsor ticker

Pharmaceutical Business Development

  • ● Map the full exclusivity landscape of a therapeutic area to see what's expiring, when, and for whom
  • ● Compare exclusivity positions across M&A targets using a consistent, normalized dataset
  • ● Track month-over-month patent modifications using our change tracking to catch quiet extensions or changing strategies
  • ● Screen reference BLAs by exclusivity expiration date to evaluate biosimilar development timelines

Generic Drug Development

  • ● Find brand NDAs with patents expiring in 1–3 years, filtered by route, dosage form, and indication
  • ● Track competitor ANDA filings and approval dates by therapeutic area
  • ● Monitor exclusivity changes monthly to catch new grants or unexpected extensions

What's Included

One dataset, multiple primary sources

Integrated from FDA, USPTO, and openFDA. Normalized, documented, and ready for analysis.

RxDataLabNormalize · Enrich · Track Changes · Compute EstimatesRxDataLab.comFDA ElectronicOrange BookFDAPurple BookopenFDADrug Labels (SPL)USPTOPatentsViewNDA/ANDA + BLAApplications & ProductsUSPTO PatentsDrug LabelsRxCUI · UNII · NDC · EPC5+ YearsChange HistoryLOE EstimatesOB + PB Unified
27,962
FDA-approved applications (NDA/ANDA + BLA)
50,397
approved drug products
30
months of OB change history

Data Coverage

  • Current Dataset May 2026 snapshot with current patent and exclusivity data
  • Historical Data 30 months of Orange Book change history. Purple Book data from May 2020.
  • Integrated Data USPTO patent details, FDA drug labels (NDA + BLA), and normalized company names with tickers and SEC CIKs across Orange Book and Purple Book sponsors
  • Biologic Coverage 841 approved BLA applications with exclusivity and patent data

How to Access

  • SQLite Database
    Primary format. Open and query with Python (sqlite3), R (RSQLite), or any database tool. Includes AGENTS.md context for LLM-assisted analysis and ~25 ready-to-run example queries covering LOE timelines, patent cliff, company portfolios, and change history.
  • CSV Files
    One file per table including applications, products, patents, exclusivity, drug labels, LOE estimates, and monthly change logs. Import directly into Excel, Pandas, or any tabular tool.
  • Platform or API Access
    Search and explore the data directly on app.rxdatalab.com, or access programmatically via API for teams integrating exclusivity data into internal tools or recurring workflows.

Fields Include:

  • • Application number and type (NDA, ANDA, BLA)
  • • Trade name and active ingredient
  • • Sponsor name (raw FDA) + RxDataLab canonical company name
  • • Stock ticker and SEC CIK (where available)
  • • Approval date, dosage form, route, strength
  • • Patent number and expiration date
  • • Patent use codes + definition
  • • Pediatric exclusivity flag
  • • USPTO patent enrichment
  • • Therapeutic equivalence (TE) code
  • • Approved indication text (from FDA drug label)
  • • FDA pharmacological class (EPC)
  • • RxNorm CUI for links to claims and formulary data
  • • NDC code for links to dispensing databases
  • • UNII links to FDA FAERS adverse event data
  • • Boxed warning text (when present)
  • • BLA number and approval type (reference product, biosimilar, or interchangeable)
  • • Biologic proper name (INN generic name equivalent)
  • • 12-year biologic reference product exclusivity expiration date
  • • Orphan drug exclusivity dates for biologics
  • • First interchangeable biosimilar exclusivity window
  • • Unified LOE estimates covering both small-molecule and biologic drugs in one table
Cross-reference identifiersin the RxDataLab datasetRxDataLab datasetsLinkable external sourcesRxDataLab.comRxCUINDCUNIISEC CIKCompany IDCompany Intelligence& Pipeline DataClaims &Formulary DataPrescriptionDispensing DataSEC / EDGARFilingsFDA FAERSAdverse Events
Full documentation:
Dataset overview Schema reference Exclusivity types & LOE methodology Change history Patent analysis

Try the Data

Download a sample export

Enter your email and we'll give you access to a sample export with the same format as the full data.

Data Quality

Primary Sources. Documented Methodology. No Black Boxes.

We pull directly from FDA, USPTO, and openFDA. No third-party vendor feeds, no repackaged commercial data.

Why Our Data are Different

  • • AI-Ready: Each export includes an AGENTS.md context file, a normalized schema, and ~25 example SQL queries. This allows LLMs to quickly get oriented and assist analysts in advanced domain-specific analysis.
  • • Trusted by consulting and research firms: Licensed by economics consulting and investment research teams for client engagements.
  • • Transparent LOE methodology: All methods and calculations are transparent and documented. No black boxes, no proprietary adjustments.
  • • Company intelligence built in: 300+ sponsor names across both Orange Book and Purple Book are normalized to canonical company identifiers with stock tickers and SEC CIK numbers, enabling M&A and portfolio analysis without manual cleanup.
  • • Primary sources only: We pull directly from FDA (Orange Book and Purple Book), USPTO, and openFDA. No third-party vendor resale, no repackaged commercial feeds. Data lineage traces to the original government source.

Data Sources

  • • FDA Electronic Orange Book monthly releases, ingested within 24 hours of publication
  • • FDA Purple Book monthly CSV releases covering all approved BLA applications with exclusivity grants and patent listings
  • • FDA exclusivity and patent use code definitions Over 4,000 use codes and 2,000 exclusivity codes
  • • USPTO Patents Via PatentsView, includes patent titles, grant dates, application numbers, and filing dates
  • • FDA Structured Product Labels via openFDA SPL includes approved indication text, pharmacological class
  • • RxDataLab company enrichment with canonical names, tickers, SEC CIK across raw FDA sponsor strings

Frequently Asked Questions

Does this include biologics and biosimilars?

Yes. The dataset includes the FDA Purple Book — all approved BLA applications including reference products, biosimilars, and interchangeable biosimilars. Exclusivity data covers the 12-year reference product protection period, orphan drug exclusivity for biologics, and the first interchangeable window. The all_loe_estimates view brings NDA and BLA loss-of-exclusivity dates together in one table.

What is the difference between the Orange Book and Purple Book data?

The Orange Book covers small-molecule drugs approved under NDA (brand) and ANDA (generic) pathways. The Purple Book covers biological products — large molecules, gene therapies, vaccines — approved under BLA. They use different exclusivity frameworks: Hatch-Waxman for small molecules, BPCIA for biologics. Our unified export combines both; you can query them separately by source or together using the all_loe_estimates and all_applications views.

Can I use this data for a client project?

Yes. Economic consulting and investment research teams use this data for client engagements. We can package the data in whatever format your team needs. Contact [email protected] to discuss scope and pricing.

How often is the data updated?

We create a new release of the data every month in-line with FDA data publishing timelines. You can subscribe for monthly updates or single-use downloads.

How can I access the data?

As a one-time export (SQLite database + CSV files + documentation) or as an annual data license with monthly updates. Data is delivered in the same format as the sample data. Contact us to discuss what you need, including formats or delivery mechanism. We can also provide access via our platform or custom programmatic access via API.

What other data can I join this to?

The dataset includes RxCUI, NDC, UNII, and SEC CIK identifiers (where available). RxCUI and NDC enable joins to claims, formulary, and prescription data sources. SEC CIK connects to EDGAR filings and SEC disclosures. Coverage of these fields is highest for NDA applications from public companies with active commercial products - most ANDA filers are private generic manufacturers and will be unmatched.

Why not just use FDA's free data?

FDA and other open regulatory agency data provide the foundation for this dataset. We then add USPTO patent details, structured label and indication data, normalize company names to CIK’s and stock tickers (where available), and maintain a clean schema designed for analysis. The Purple Book in particular comes in three different historical CSV formats with inconsistent date representations; unifying it with Orange Book data adds significant complexity we handle on our end.

What does 'AI-ready' mean for this dataset?

Each export includes an AGENTS.md file that describes the schema, data sources, and common query patterns in plain text. When loaded into an LLM context, it gives the model enough grounding to write accurate SQL against the database without you having to explain the schema yourself. The roughly 25 included example queries cover the most common analytical tasks and serve as starting points for more complex requests. The underlying data uses consistent, self-explanatory column names and a normalized structure, which reduces the kind of ambiguity that causes LLMs to make mistakes on less structured datasets.

Do you offer discounts for academics/nonprofits/journalists?

Yes. Contact [email protected] and we’ll work something out.

Get the Data

Get the Data, Fast

One-time exports for a specific project, or annual licenses with monthly updates or API access. We'll package the data in whatever format your team needs and get it to you quickly.

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