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💊 FDA Drug Approvals Tracker — NDA / BLA / ANDA + Special Designations

The institutional pharma pipeline desk on tap. Real-time FDA drug approval events — New Drug Applications (NDA), Biologics License Applications (BLA), Abbreviated NDAs (ANDA / generics), and supplemental approvals (label expansions, new indications, new strengths, new dosage forms) — with every FDA expedited-program flag (priority review, breakthrough therapy, accelerated approval, orphan drug, fast track), dosage form, route of administration, manufacturer (sponsor of record), and inferred therapeutic class. Built for pharma / biotech equity analysts, hedge fund healthcare specialists, pharma BD / licensing teams, IP attorneys, generic-launch traders, biosimilar competitive intel, and CDER pipeline trackers.

This is the actor a single seat of EvaluatePharma, Citeline (formerly Informa Pharma), GlobalData Healthcare, or IQVIA Pipeline costs $20,000–$60,000 / year to access. Pay-per-result on Apify — no seat, no enterprise contract, no minimum commitment.

Why a dedicated FDA approvals actor (and not just an openFDA wrapper)

The openFDA Drugs@FDA endpoint returns ~29,000 applications going back to 1939. Every application has 10–60 submissions stacked under it (original + every label, manufacturing, and efficacy supplement). Raw openFDA dumps a giant tree; what an analyst actually needs is one record per approval event, normalized into a flat schema with the institutional fields that matter:

1. One approval = one record. A single NDA can carry 30 supplemental approvals (new indications, new strengths) over its lifecycle. Each supplement is a competitive event — a label expansion can add a $5B addressable market overnight. The actor fans out openFDA's nested submission tree into discrete approval events keyed by (application_number, submission_number).
2. Five expedited-program flags inline. Priority Review (6-month clock), Breakthrough Therapy (substantial improvement), Accelerated Approval (surrogate endpoint), Orphan Drug (<200k US patients), Fast Track. These are the single most-tracked attributes in biotech equity research. openFDA scatters them across review_priority, submission_class_code_description, and the openfda enrichment block — the actor consolidates them into five clean booleans.
3. Inferred therapeutic class. Each approval is scored against a curated drug-name keyword catalog (oncology, immunology, cardiometabolic, neurology / psychiatry, infectious disease, rare disease / gene therapy, respiratory, GI / hepatology). This is the field every equity analyst sorts on; openFDA doesn't ship it. Conservative — when no pattern matches, the field is null and you can hydrate downstream.
4. Deterministic Drugs@FDA cross-links. Every record carries the fda_daf_url for the application's Drugs@FDA page and the openfda_url for the raw JSON record — drop straight into the FDA's primary record without a separate lookup.

What you get

A unified FDA approval event stream, one record per approval action:

{
"approval_id":"NDA212273-SUPPL-14",
"application_number":"NDA212273",
"drug_name":"TRIKAFTA (ELEXACAFTOR, IVACAFTOR, TEZACAFTOR + IVACAFTOR)",
"brand_name":"TRIKAFTA (COPACKAGED)",
"generic_name":"ELEXACAFTOR, IVACAFTOR, TEZACAFTOR + IVACAFTOR",
"manufacturer":"VERTEX PHARMS INC",
"approval_date":"2026-03-27",
"approval_type":"SUPPL",
"submission_type":"SUPPL",
"submission_number":"14",
"submission_class":"Efficacy",
"indication":"Cystic Fibrosis Transmembrane Conductance Regulator Potentiator [EPC]",
"dosage_form":"TABLET",
"route_of_administration":"ORAL",
"therapeutic_class":"Rare Disease / Gene Therapy",
"priority_review":true,
"breakthrough_designation":false,
"accelerated_approval":false,
"orphan_drug":true,
"fast_track":false,
"fda_press_release_url":null,
"fda_daf_url":"https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=212273",
"openfda_url":"https://api.fda.gov/drug/drugsfda.json?search=application_number:NDA212273",
"marketing_status":"Prescription",
"data_source":"openFDA Drugs@FDA"
}

That gives you everything to:

• Build a daily / weekly FDA approval newsletter (one of the most-read formats in pharma equity research)
• Track competitor pipeline progression — new BLAs, new label expansions, breakthrough designations
• Run generic-launch screening (ANDA approvals × innovator patent cliff = day-trade opportunity)
• Build a biosimilar competitive intelligence dashboard (BLA supplements on already-approved biologics)
• Power a pharma BD team's incoming-deal screen (small-cap biotech with a fresh breakthrough designation)
• Surface accelerated-approval drugs that converted to full approval (or got withdrawn — every withdrawal is a short signal)
• Feed an IP attorney's freedom-to-operate landscape with the canonical FDA application number

Approval types explained

The actor returns all five types in a single pull. Filter by approval_type to narrow.

Special FDA designation flags

Input filters

Use cases for pharma / biotech capital

Pharma / biotech equity analysts (sell-side + buy-side)

Daily pull of last_30d approvals with has_special_designation: any. Triage which catalysts hit the tape, mark sponsors as "tracked vs new", flag NMEs (every NME is a tradable single-stock event for the sponsor). Replace your manual EvaluatePharma / Citeline daily-approvals digest with a JSON feed you can pipe into Snowflake / BigQuery + a Slack alert.

Hedge fund healthcare specialists

Run approval_type: NME filter to surface only first-in-class small-molecule approvals — these are the ones that drive single-stock catalysts. Combine with our SEC Form 8-K Material Events Scraper to pair each FDA approval event with the simultaneous 8-K filing the sponsor must file under Item 8.01. Pair-trading: long the sponsor on approval day, short a peer in the same indication.

Generic-launch traders

approval_type: ANDA returns generic approvals. Cross-reference the active ingredient against the innovator's patent expiration calendar (Orange Book exclusivity) — first ANDA approval triggers an automatic 25–60% innovator share-price drop on the relevant day.

Biosimilar competitive intelligence

approval_type: BLA with submission_type: SUPPL and a manufacturer in the biosimilar shop list (Samsung Bioepis, Celltrion, Sandoz, Amgen biosimilars, Coherus, Organon) — surfaces new biosimilar label expansions in real time.

Pharma BD / licensing teams

has_special_designation: breakthrough filter on small-cap manufacturers — surfaces in-licensing targets before they hit the broader biotech media cycle. Cross-reference with our IPO Tracker for biotech IPOs in the same therapeutic class.

Pharma IP attorneys

Each approval carries the canonical application_number (NDA / BLA / ANDA) that anchors every freedom-to-operate analysis, Orange Book exclusivity calendar, and Paragraph IV certification timeline.

Biotech catalyst funds

Pre-build long / short books for accelerated-approval drugs nearing the confirmatory post-marketing trial deadline. Combine with our Analyst Price Targets actor to fade consensus when the confirmatory trial is at risk.

Pharma sales-force planning

Track competitor BLAs with route_of_administration: INJECTION to flag injectable launches that affect specialty-pharmacy distribution. Cross-reference with the manufacturer's annual sales force build-out.

Pricing — pay per approval record

A 10-record smoke test costs $1.51 total. A daily 50-record approval pull costs $7.51 / day or roughly $2,740 / year — a 90–96% discount vs. an EvaluatePharma seat ($30k–$60k / year) or a single Citeline subscription ($25k+ / year). FDA approval records are priced higher ($0.15 / record) than our equity screener records because each approval is a discrete, institutional-value pharma signal — a single breakthrough designation can drive a 30% single-stock move; a single ANDA approval can compress an innovator multiple by 2 turns.

Data sources & reliability

1. openFDA Drugs@FDA endpoint (primary) — api.fda.gov/drug/drugsfda.json. The FDA's official, free, no-auth, structured API for every NDA / BLA / ANDA / supplement going back to 1939. Refreshed daily by the FDA. The actor queries this endpoint with a submission_status_date range and submission_status:AP (approved) filter.
2. FDA Drugs@FDA web interface (cross-link) — accessdata.fda.gov/scripts/cder/daf/. Each record carries a deterministic fda_daf_url for the application's primary Drugs@FDA web page.
3. FDA Press Announcements (cross-link surface) — fda.gov/news-events/fda-newsroom/press-announcements is reserved as a future enrichment for major approvals; the field fda_press_release_url is emitted on every record and is null when no press release is cross-matched.
4. openFDA pharm_class_epc enrichment — the openfda.pharm_class_epc block carries FDA-curated Established Pharmacologic Class labels (e.g., "Factor Xa Inhibitor [EPC]", "Tumor Necrosis Factor Blocker [EPC]"). The actor uses this for the indication field when available.
5. Inferred therapeutic class — a curated drug-name keyword catalog (~150 keywords across 8 categories) is applied as a fallback. Conservative — when no pattern matches, the field is null.

Anti-bot risk: LOW. openFDA is the official FDA free API with no rate limits for normal usage. The actor is resilient to single-request failures and re-issues on transient 5xx.

How to run

Apify Console — paste your filter inputs, hit Run, download the dataset as JSON / CSV / Excel.

Apify API (Python):

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("nexgendata/fda-drug-approvals").call(run_input={
"date_range":"last_30d",
"approval_type":"NME",
"has_special_designation":"any",
"limit":25,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item["approval_date"], item["drug_name"], item["manufacturer"],
 item["therapeutic_class"], item["priority_review"],
 item["breakthrough_designation"], item["orphan_drug"])

Schedule it — pair with an Apify scheduled task. Daily 18:00 ET (post-FDA daily approval cycle) gives you a fresh approvals snapshot every business day. Weekly Friday 16:00 ET gives you a clean weekly pipeline digest.

FAQ

How fresh is the data? openFDA refreshes Drugs@FDA daily, typically 18:00–22:00 ET the day after FDA action. For real-time same-day signal, supplement with the FDA press release feed (a future enrichment in fda_press_release_url).

Why does one application appear multiple times in my pull? Each emitted record is one (application × approving submission) event. A single NDA can have 30 supplements over its lifecycle; each supplement is a distinct approval action. Filter approval_type: NDA and submission_type: ORIG if you want only original NDAs.

Why is accelerated_approval not flagged for some drugs I know got accelerated approval? openFDA's structured fields don't always carry the accelerated-approval marker explicitly. The actor uses a conservative AND-of-evidence rule (review_priority + class description + openfda block hints). For drugs missing the flag, cross-reference with fda_daf_url for the explicit FDA approval letter.

Does it cover withdrawn / discontinued drugs? Yes — the marketing_status field surfaces "Prescription", "Discontinued", "Over-the-counter", or "None". Withdrawn drugs remain in openFDA's history with marketing_status: Discontinued.

Does it cover veterinary drugs? No — only human drugs (CDER / CBER). For veterinary drugs (CVM), the data lives in a separate FDA index (animaldrug@FDA) which is on our roadmap.

Does it cover medical devices? No — only drugs and biologics. Medical device approvals (510k, PMA) flow through a different FDA pathway and dataset; consider our SEC Form 8-K Material Events Scraper as a proxy for device-maker corporate signal.

Does it cover EMA / Health Canada / PMDA approvals? Not yet — US FDA only. EMA / Health Canada / PMDA harmonized approval trackers are on our 2026 roadmap.

What about expanded access / compassionate use? Not tracked — those are individual-patient INDs and don't flow through the Drugs@FDA approval pipeline.

Why is indication sometimes the pharmacologic class instead of the disease state? openFDA's structured fields carry pharmacologic class (e.g., "Factor Xa Inhibitor") rather than disease (e.g., "stroke prevention in atrial fibrillation"). The class is a reliable downstream key for therapeutic-area sorting; for the explicit indication text, parse the drug's full label (DailyMed feed — future enrichment).

Cross-link to NexGenData's institutional fleet

This actor sits at the center of our pharma / biotech institutional toolkit. Combine with the following sister actors to build a fully connected biotech catalyst pipeline:

Corporate signal feeds

• 🔗 SEC Form 8-K Material Events Scraper — Every FDA approval triggers a same-day 8-K Item 8.01 filing. Pair the two to cross-check the sponsor's disclosure language, share count, and forward-looking statements.
• 🔗 IPO Tracker — Recent + Upcoming IPOs — Biotech IPO cohort overlaps heavily with the BLA / NDA pipeline. Track which IPO'd-this-year biotechs have a near-term PDUFA date and pre-position.

Institutional flow

• 🔗 SEC Form 13F Holdings Tracker — See which biotech-specialist hedge funds (Baker Bros., Perceptive, RA Capital, OrbiMed, Avoro) loaded up on a sponsor in the quarter preceding an approval.
• 🔗 Short Interest Tracker — Pre-PDUFA short interest is the single best leading indicator for binary biotech catalyst skew. Cross-reference with has_special_designation: accelerated for confirmatory-readout shorts.

Sentiment + consensus

• 🔗 Analyst Price Targets — Pair each approval event with sell-side consensus targets to detect post-approval re-rate gaps. Heaviest gaps = highest-conviction post-approval trades.

Programmatic access

• 🔗 Finance MCP Server — Unified Model Context Protocol server exposing the full NexGenData fleet (FDA approvals, IPOs, 8-Ks, 13Fs, short interest, analyst targets) to Claude, Cursor, ChatGPT desktop, and any MCP-aware LLM. Ask "show me last week's NME approvals with breakthrough designation" and the MCP server routes the call through this actor.

Browse the full NexGenData catalog

→ See all 220+ NexGenData actors at apify.com/nexgendata — equity screeners across 25+ markets, IPO + pre-IPO trackers, SEC filings, FDA approvals, institutional holdings, B2B intelligence, MCP servers, and more.

Why NexGenData vs. paid pharma data alternatives

Run this actor for an institutional pharma analyst workflow (~50 records/day, 250 trading days/year) and your annual cost is approximately $1,876 — a 94–97% discount vs. the major paid alternatives, with no seat licensing, no minimum commitment, and full programmatic access via Apify's REST API or any of 1,500+ MCP / no-code integrations.

The paid alternatives buy you global coverage (EMA / PMDA / Health Canada) and proprietary pipeline curation (Phase 1–3 clinical pipeline before FDA filing). For the post-NDA/BLA-submission FDA approval signal specifically — the single highest-frequency, highest-impact catalyst type in biotech — this actor delivers parity coverage at 3–5% of the cost.

Quick Comparison vs. Paid Incumbents

How this actor stacks up against the platforms biotech and pharma analysts pay for FDA-catalyst coverage:

For the post-NDA/BLA-submission FDA approval signal specifically — the single highest-frequency, highest-impact catalyst type in biotech — this actor delivers parity coverage at 3–7% of incumbent cost.

Quick Comparison vs. Paid Incumbents

How this actor stacks up against the platforms biotech and pharma analysts pay for FDA-catalyst coverage:

For the post-NDA/BLA-submission FDA approval signal specifically — the single highest-frequency, highest-impact catalyst type in biotech — this actor delivers parity coverage at 3–7% of incumbent cost.

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Built and maintained by NexGenData — institutional-grade equity, IPO, SEC filings, FDA approvals, and B2B data infrastructure on Apify.