# 💊 FDA Intelligence — Recalls, Approvals & Adverse Events (`inexhaustible_glass/fda-intelligence-scraper`) Actor Scrape ALL FDA open data (openFDA): drug & device recalls, adverse events (FAERS/MAUDE), labels, device clearances (510k) & approvals (PMA), food recalls. 40M+ records, filter by date & field. For pharma, devices, product-liability lawyers, insurers, investors. Free, no key, no proxy. - **URL**: https://apify.com/inexhaustible\_glass/fda-intelligence-scraper.md - **Developed by:** [Hitman studio](https://apify.com/inexhaustible_glass) (community) - **Categories:** Lead generation, News, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results 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 Intelligence Scraper — Recalls, Approvals & Adverse Events > **One actor for the entire FDA open-data universe.** Drug & device recalls, adverse events, > approvals, labels and food recalls — clean CSV / JSON, no key, no proxy. Pulls directly from the official **openFDA** API (`api.fda.gov`) — 40M+ records — and returns the **complete record** for every result plus a clean normalized summary. --- ### 👥 Who needs this | You are a… | You get… | |---|---| | ⚖️ **Product-liability / malpractice lawyer** | Recalls + adverse events = **litigation leads & evidence** | | 💊 **Pharma / biotech** | Competitor approvals, recalls, safety signals | | 🩺 **Medical-device company** | 510k/PMA clearances, device recalls & MAUDE events | | 🛡️ **Insurer / risk analyst** | Safety & recall signals for underwriting | | 📈 **Investor** | Approvals & recalls = market-moving events | | 🍎 **Food importer / retailer** | Food recall alerts | ### 🗂️ 8 datasets in one actor | Dataset | Source | Contents | |---|---|---| | 💊 Drug recalls | drug/enforcement | recalling firm, product, reason, class, status | | ⚠️ Drug adverse events | drug/event (FAERS) | reactions, drugs, seriousness | | 🏷️ Drug labels & safety | drug/label | brand, manufacturer, indications, warnings | | 🩺 Device recalls | device/recall | firm, product, reason, class | | ⚠️ Device adverse events | device/event (MAUDE) | device, event type, manufacturer | | ✅ Device clearances | device/510k | applicant, device, K-number, decision date | | ✅ Device approvals | device/pma | applicant, product, PMA number, decision date | | 🍎 Food recalls | food/enforcement | firm, product, reason, class | > **Most other actors do ONE of these. This does all eight** — and returns the full underlying > record so nothing is ever missed. --- ### 🚀 How to use 1. Pick a **Dataset**. 2. *(optional)* Add a **Search** (openFDA syntax) and/or a **date range**. 3. Press **Start** → download CSV / Excel / JSON. #### Example input ```json { "dataset": "drug-recalls", "searchQuery": "classification:\"Class I\"", "dateFrom": "2026-01-01", "dateTo": "2026-06-30", "maxResults": 500 } ```` 👉 *"All Class I (most serious) drug recalls in the first half of 2026."* #### Useful search examples - `recalling_firm:Pfizer` — everything from one firm - `reason_for_recall:contamination` - `applicant:Medtronic` (device clearances/approvals) - `patient.reaction.reactionmeddrapt:headache` (adverse events) *** ### 📦 Output Each row contains a **normalized summary** (`date`, `firm`, `title`, `reason`, `classification`, `status`, `recall_number`…) **plus** `full_record` — the complete original openFDA object, so you have every field for deeper analysis. *** ### ℹ️ Notes - **Source:** official `api.fda.gov` (openFDA) — public, free, no key needed. - Add a free **openFDA API key** (open.fda.gov) to raise limits (1,000 → 120,000 req/day) and page beyond 25,000 results. - US-only data (FDA). A UK equivalent is a separate actor. *** *Keywords: FDA, openFDA, drug recall, device recall, FAERS, MAUDE, adverse events, 510k, PMA, drug approvals, food recall, pharmacovigilance, product liability, medical device intelligence, pharma competitive intelligence, recall monitoring, FDA enforcement.* # Actor input Schema ## `dataset` (type: `string`): Which FDA dataset to pull. ## `searchQuery` (type: `string`): openFDA query. Examples: 'recalling\_firm:Pfizer', 'classification:"Class I"', 'reason\_for\_recall:contamination', 'applicant:Medtronic'. Leave empty for all. ## `dateFrom` (type: `string`): Only records on/after this date (YYYY-MM-DD). Uses each dataset's main date field (report/decision/received date). ## `dateTo` (type: `string`): Only records on/before this date (YYYY-MM-DD). ## `maxResults` (type: `integer`): Cap total records (millions are available). ## `apiKey` (type: `string`): Free key from open.fda.gov/apis/authentication → raises limits from 1,000 to 120,000 requests/day and lets you page past 25k results. Without it, the actor still works for normal sizes. ## Actor input object example ```json { "dataset": "drug-recalls", "searchQuery": "classification:\"Class I\"", "dateFrom": "2026-01-01", "dateTo": "2026-06-30", "maxResults": 100 } ``` # 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 = { "dataset": "drug-recalls", "dateFrom": "2026-01-01" }; // Run the Actor and wait for it to finish const run = await client.actor("inexhaustible_glass/fda-intelligence-scraper").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 = { "dataset": "drug-recalls", "dateFrom": "2026-01-01", } # Run the Actor and wait for it to finish run = client.actor("inexhaustible_glass/fda-intelligence-scraper").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 '{ "dataset": "drug-recalls", "dateFrom": "2026-01-01" }' | apify call inexhaustible_glass/fda-intelligence-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=inexhaustible_glass/fda-intelligence-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "💊 FDA Intelligence — Recalls, Approvals & Adverse Events", "description": "Scrape ALL FDA open data (openFDA): drug & device recalls, adverse events (FAERS/MAUDE), labels, device clearances (510k) & approvals (PMA), food recalls. 40M+ records, filter by date & field. For pharma, devices, product-liability lawyers, insurers, investors. Free, no key, no proxy.", "version": "1.0", "x-build-id": "ZJIAZudNRgtiRd8LH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/inexhaustible_glass~fda-intelligence-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-inexhaustible_glass-fda-intelligence-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/inexhaustible_glass~fda-intelligence-scraper/runs": { "post": { "operationId": "runs-sync-inexhaustible_glass-fda-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/inexhaustible_glass~fda-intelligence-scraper/run-sync": { "post": { "operationId": "run-sync-inexhaustible_glass-fda-intelligence-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "dataset": { "title": "📂 Dataset", "enum": [ "drug-recalls", "drug-adverse-events", "drug-labels", "device-recalls", "device-adverse-events", "device-clearances", "device-approvals", "food-recalls" ], "type": "string", "description": "Which FDA dataset to pull.", "default": "drug-recalls" }, "searchQuery": { "title": "🔍 Search (openFDA syntax, optional)", "type": "string", "description": "openFDA query. Examples: 'recalling_firm:Pfizer', 'classification:\"Class I\"', 'reason_for_recall:contamination', 'applicant:Medtronic'. Leave empty for all." }, "dateFrom": { "title": "📅 Date From", "type": "string", "description": "Only records on/after this date (YYYY-MM-DD). Uses each dataset's main date field (report/decision/received date)." }, "dateTo": { "title": "📅 Date To", "type": "string", "description": "Only records on/before this date (YYYY-MM-DD)." }, "maxResults": { "title": "🔢 Max Results", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Cap total records (millions are available).", "default": 100 }, "apiKey": { "title": "🔑 openFDA API key (optional, free)", "type": "string", "description": "Free key from open.fda.gov/apis/authentication → raises limits from 1,000 to 120,000 requests/day and lets you page past 25k results. Without it, the actor still works for normal sizes." } } }, "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 } } } } } } } } } } ```