# FDA Drug Approvals Tracker — NDA/BLA/ANDA API (`nexgendata/fda-drug-approvals`) Actor Track FDA drug approvals via openFDA — NDA / BLA / ANDA / supplements with priority review, breakthrough, accelerated approval, orphan drug, fast track flags. Indication, dosage form, route, manufacturer. EvaluatePharma / Citeline / GlobalData alternative for pharma analysts. - **URL**: https://apify.com/nexgendata/fda-drug-approvals.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $150.00 / 1,000 fda approval records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## FDA Drug Approvals Tracker Track FDA drug approvals — NDA, BLA and ANDA application records with dates and manufacturers. > Public regulatory/health data — not medical advice. ### ⏰ Run this as a monitoring subscription (recommended) Regulatory data is monitoring data. Schedule a weekly sweep (`0 8 * * 1`) and catch new approvals as they post — an always-on official-records feed. ### 📊 What you get Clean JSON, one record per approval (full output has 25 fields): - `approval_id` — Approval id - `application_number` — Application number - `drug_name` — Drug name - `brand_name` — Brand name - `generic_name` — Generic name - `manufacturer` — Manufacturer - `approval_date` — Approval date - `approval_type` — Approval type - `submission_type` — Submission type - `submission_number` — Submission number **Pricing:** $0.150 per approval (Pay-Per-Event) — about **7 approvals per $1**. ### 🤖 Use with AI agents Point Claude, the OpenAI Agents SDK, an n8n flow or any MCP-aware client at it and pull official records on demand. **Agentic payments (x402):** Supports agentic payment via x402 — agents can call this actor with USDC, no API key required. ### 🔗 Related regulatory actors **FDA & public-health records family:** [OpenFDA Drug](https://apify.com/nexgendata/openfda-drug-search) · [Drug Shortages](https://apify.com/nexgendata/fda-drug-shortages-monitor) · [Purple Book](https://apify.com/nexgendata/fda-purple-book-biologics-biosimilars) · [Warning Letters/483](https://apify.com/nexgendata/fda-warning-letters-483-inspections) · [Pharma Pipeline](https://apify.com/nexgendata/fda-pharma-catalyst-pipeline) · [Adverse Events](https://apify.com/nexgendata/fda-adverse-events-faers-maude) · [Medical Devices](https://apify.com/nexgendata/medical-device-fda-intelligence) **Product-safety recalls:** [NHTSA Recalls](https://apify.com/nexgendata/nhtsa-us-vehicle-recalls) · [NHTSA Defects](https://apify.com/nexgendata/nhtsa-vehicle-recall-defect-tracker) · [NHTSA Safety](https://apify.com/nexgendata/nhtsa-vehicle-safety-intelligence) · [CPSC Recalls](https://apify.com/nexgendata/cpsc-product-recalls) **Agent front door — Healthcare & FDA MCP:** [Healthcare & FDA MCP](https://apify.com/nexgendata/healthcare-fda-intelligence-mcp) --- *Public official records and enforcement data, assembled for research and monitoring.* # Actor input Schema ## `date_range` (type: `string`): Filter by FDA approval date window. 'last_30d' = approvals in the last 30 calendar days (typical weekly desk pull); 'last_90d' = last 90 days (quarterly pipeline review window); 'last_180d' = last 180 days (half-year cohort); 'last_365d' = trailing 12 months (annual approval count vs CDER stats); 'ytd' = year-to-date approvals; 'all' = full history (~29,000 applications, use with care + a tight limit). ## `approval_type` (type: `string`): Filter by FDA application type. NDA = New Drug Application (small-molecule, CDER review); BLA = Biologics License Application (biologics, CBER/CDER); ANDA = Abbreviated NDA (generics, equivalence pathway); NME = New Molecular Entity (first-in-class small-molecule, subset of NDA originals); SUPPL = supplemental approval (label expansion, new indication, new strength, new dosage form). 'all' returns every type. ## `manufacturer` (type: `string`): Filter by FDA sponsor (applicant company) name. Case-insensitive substring match against the openFDA sponsor_name field. Examples: 'pfizer', 'merck', 'vertex', 'novartis', 'eli lilly', 'regeneron', 'amgen', 'gilead'. Leave empty to return all sponsors. NB: openFDA records the FDA applicant of record, which can be a subsidiary or co-development partner — search broadly. ## `therapeutic_class` (type: `string`): Filter by therapeutic area or indication keyword. Case-insensitive match against drug name + active ingredient + dosage form. Examples: 'oncology', 'cancer', 'diabetes', 'cardiovascular', 'neurology', 'immunology', 'rare disease', 'infectious'. The actor enriches each record with a best-effort therapeutic_class derived from the active ingredient class. Leave empty to skip. ## `has_special_designation` (type: `string`): Filter approvals by FDA expedited program flag. 'priority_review' = 6-month FDA review clock (vs 10-month standard); 'breakthrough' = breakthrough therapy designation (substantial improvement over existing therapy); 'accelerated' = accelerated approval (surrogate endpoint, e.g., tumor response); 'orphan' = orphan drug status (rare disease, <200k US patients); 'fast_track' = fast track designation; 'any' = at least one of the above; 'none' = no special designation (standard review). ## `limit` (type: `integer`): Maximum number of FDA approval records to emit. Set to 10 for a smoke test, 50 for a weekly desk pull, 200 for a full quarterly cohort. The openFDA index contains ~29,000 applications all-time and ~700-900 approval events in any rolling 90-day window. Set to 0 to disable the cap (will fetch up to 1000 from the API per pull). ## Actor input object example ```json { "date_range": "last_90d", "approval_type": "all", "manufacturer": "", "therapeutic_class": "", "has_special_designation": "all", "limit": 50 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "date_range": "last_90d", "approval_type": "all", "manufacturer": "", "therapeutic_class": "", "has_special_designation": "all", "limit": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/fda-drug-approvals").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "date_range": "last_90d", "approval_type": "all", "manufacturer": "", "therapeutic_class": "", "has_special_designation": "all", "limit": 50, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/fda-drug-approvals").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "date_range": "last_90d", "approval_type": "all", "manufacturer": "", "therapeutic_class": "", "has_special_designation": "all", "limit": 50 }' | apify call nexgendata/fda-drug-approvals --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/fda-drug-approvals", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FDA Drug Approvals Tracker — NDA/BLA/ANDA API", "description": "Track FDA drug approvals via openFDA — NDA / BLA / ANDA / supplements with priority review, breakthrough, accelerated approval, orphan drug, fast track flags. Indication, dosage form, route, manufacturer. EvaluatePharma / Citeline / GlobalData alternative for pharma analysts.", "version": "0.0", "x-build-id": "SUkveb3XpWPQCdrbD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~fda-drug-approvals/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-fda-drug-approvals", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~fda-drug-approvals/runs": { "post": { "operationId": "runs-sync-nexgendata-fda-drug-approvals", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~fda-drug-approvals/run-sync": { "post": { "operationId": "run-sync-nexgendata-fda-drug-approvals", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "date_range": { "title": "Approval date range", "enum": [ "last_30d", "last_90d", "last_180d", "last_365d", "ytd", "all" ], "type": "string", "description": "Filter by FDA approval date window. 'last_30d' = approvals in the last 30 calendar days (typical weekly desk pull); 'last_90d' = last 90 days (quarterly pipeline review window); 'last_180d' = last 180 days (half-year cohort); 'last_365d' = trailing 12 months (annual approval count vs CDER stats); 'ytd' = year-to-date approvals; 'all' = full history (~29,000 applications, use with care + a tight limit).", "default": "last_90d" }, "approval_type": { "title": "Approval / application type", "enum": [ "all", "NDA", "BLA", "ANDA", "NME", "SUPPL" ], "type": "string", "description": "Filter by FDA application type. NDA = New Drug Application (small-molecule, CDER review); BLA = Biologics License Application (biologics, CBER/CDER); ANDA = Abbreviated NDA (generics, equivalence pathway); NME = New Molecular Entity (first-in-class small-molecule, subset of NDA originals); SUPPL = supplemental approval (label expansion, new indication, new strength, new dosage form). 'all' returns every type.", "default": "all" }, "manufacturer": { "title": "Manufacturer / sponsor filter", "type": "string", "description": "Filter by FDA sponsor (applicant company) name. Case-insensitive substring match against the openFDA sponsor_name field. Examples: 'pfizer', 'merck', 'vertex', 'novartis', 'eli lilly', 'regeneron', 'amgen', 'gilead'. Leave empty to return all sponsors. NB: openFDA records the FDA applicant of record, which can be a subsidiary or co-development partner — search broadly.", "default": "" }, "therapeutic_class": { "title": "Therapeutic class / indication keyword", "type": "string", "description": "Filter by therapeutic area or indication keyword. Case-insensitive match against drug name + active ingredient + dosage form. Examples: 'oncology', 'cancer', 'diabetes', 'cardiovascular', 'neurology', 'immunology', 'rare disease', 'infectious'. The actor enriches each record with a best-effort therapeutic_class derived from the active ingredient class. Leave empty to skip.", "default": "" }, "has_special_designation": { "title": "Special FDA designation filter", "enum": [ "all", "any", "priority_review", "breakthrough", "accelerated", "orphan", "fast_track", "none" ], "type": "string", "description": "Filter approvals by FDA expedited program flag. 'priority_review' = 6-month FDA review clock (vs 10-month standard); 'breakthrough' = breakthrough therapy designation (substantial improvement over existing therapy); 'accelerated' = accelerated approval (surrogate endpoint, e.g., tumor response); 'orphan' = orphan drug status (rare disease, <200k US patients); 'fast_track' = fast track designation; 'any' = at least one of the above; 'none' = no special designation (standard review).", "default": "all" }, "limit": { "title": "Number of approval records to return", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Maximum number of FDA approval records to emit. Set to 10 for a smoke test, 50 for a weekly desk pull, 200 for a full quarterly cohort. The openFDA index contains ~29,000 applications all-time and ~700-900 approval events in any rolling 90-day window. Set to 0 to disable the cap (will fetch up to 1000 from the API per pull).", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```