# FDA FAERS Adverse Event Signal Report (`pj_pai/faers-signal-report`) Actor Per-drug pharmacovigilance summary from FDA FAERS: report volume, seriousness, outcomes, top reactions and yearly trend. - **URL**: https://apify.com/pj_pai/faers-signal-report.md - **Developed by:** [Rakesh Pai](https://apify.com/pj_pai) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $50.00 / 1,000 drug signal reports 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/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## FDA FAERS Adverse Event Signal Report Per-drug pharmacovigilance summary from FDA FAERS: report volume, seriousness, outcomes, top reactions and yearly trend. **Data source:** openFDA FAERS adverse event API. Official public data, no API key, no login and no scraping of protected pages. Results are returned as clean, flat JSON that is ready for spreadsheets, databases, BI tools and AI agents. ### What can you use it for? - Pharmacovigilance signal screening - Medical affairs and safety reviews - Competitive safety comparisons between drugs - AI agent tool for adverse event questions - Use it as a tool from AI agents through the Apify MCP server, or schedule it and send new results to Slack, Google Sheets or a webhook ### Input | Field | Name | Description | |---|---|---| | `drugs` | Drug names | Drug names as reported in FAERS | | `topReactions` | Top reactions | How many reactions to return | #### Example input ```json { "drugs": [ "metformin", "semaglutide" ], "topReactions": 10 } ``` ### Output Each result is one dataset item with these fields: `drug`, `totalReports`, `seriousReports`, `deathReports`, `seriousPct`, `topReactions`, `reportsByYear`, `disclaimer`, `generatedAt`. #### Example output (real result, long fields shortened) ```json { "drug": "metformin", "totalReports": 439104, "seriousReports": 293750, "deathReports": 36189, "seriousPct": 66.9, "topReactions": [ { "reaction": "NAUSEA", "reports": 30159, "pctOfReports": 6.87 }, { "reaction": "DIARRHOEA", "reports": 28197, "pctOfReports": 6.42 }, { "reaction": "BLOOD GLUCOSE INCREASED", "reports": 27577, "pctOfReports": 6.28 }, { "reaction": "DRUG INEFFECTIVE", "reports": 22744, "pctOfReports": 5.18 } ], "reportsByYear": { "2001": 1, "2003": 2, "2004": 1935, "2005": 2955, "2006": 6365, "2007": 7464, "2008": 7508, "2009": 7809, "2010": 9426, "2011": 11861, "2012": 14156, "2013": 14855, "2014": 18847, "2015": 29843, "2016": 30651, "2017": 29447, "2018": 34565, "2019": 34692, "2020": 32300, "2021": 27594, "2022": 26840, "2023": 26629, "2024": 25369, "2025": 25549, "2026": 12441 }, "disclaimer": "FAERS reports are unverified and do not establish causation.", "generatedAt": "2026-10-28T05:28:26.000Z" } ``` Download the results as JSON, CSV, Excel or XML, or read them through the Apify API. ### Pricing This Actor uses **pay-per-event** pricing. You pay **$0.05 per drug report** returned, plus standard Apify platform usage, which is small because the Actor only calls lightweight APIs. You are never charged for results that are not returned. To cap spending, set a maximum cost per run in the run options. ### Tips - Start with a small max-results value to check your filters, then scale up. - Schedule the Actor (for example daily) with a "since" date filter where available to get change alerts. - The data comes straight from the official source, so its freshness and completeness depend on that publisher. ### Disclaimer This Actor is not affiliated with or endorsed by the data publisher. Verify critical decisions against the official source. # Actor input Schema ## `drugs` (type: `array`): Drug names as reported in FAERS ## `topReactions` (type: `integer`): How many reactions to return ## Actor input object example ```json { "drugs": [ "metformin", "semaglutide" ], "topReactions": 15 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "drugs": [ "metformin", "semaglutide" ] }; // Run the Actor and wait for it to finish const run = await client.actor("pj_pai/faers-signal-report").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "drugs": [ "metformin", "semaglutide", ] } # Run the Actor and wait for it to finish run = client.actor("pj_pai/faers-signal-report").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "drugs": [ "metformin", "semaglutide" ] }' | apify call pj_pai/faers-signal-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,pj_pai/faers-signal-report" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/5RiKNvTk0IvHqluRJ/builds/A0yVQgGboW7tBzLsS/openapi.json