# Biotech Catalyst Monitor (`b3lch/biotech-catalyst-monitor`) Actor Clean, ticker-mapped feed of biotech catalysts — trial readouts, status changes, results, FDA approvals & recalls, and upcoming PDUFA / FDA decision dates — from ClinicalTrials.gov, the FDA, and SEC EDGAR. - **URL**: https://apify.com/b3lch/biotech-catalyst-monitor.md - **Developed by:** [alfred dias](https://apify.com/b3lch) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / actor start 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 ### What does the Biotech Catalyst Monitor do? The Biotech Catalyst Monitor turns three public data feeds — ClinicalTrials.gov, the FDA, and SEC EDGAR — into a single, clean, ticker-mapped feed of biotech catalysts: trial registrations, status changes (completed, terminated, suspended, withdrawn), results postings, upcoming readouts, drug approvals, enforcement recalls, and **upcoming PDUFA / FDA decision dates** as companies announce them in SEC filings. Every row is enriched with a best-effort public-company ticker so you can see, at a glance, which events are actually investable and which belong to private or foreign sponsors. Use it market-wide (leave the filters empty) or scope it down to specific tickers, companies, indications, or trial phases. Trials with a primary completion date inside a configurable "upcoming window" are flagged as `UpcomingReadout` so you can watch for readouts before they happen, not just after. Because it runs as an Apify Actor, you can schedule it (e.g. daily or weekly) and wire it into Apify's integrations — Slack, email, webhooks, Zapier, Make — to get notified the moment a new catalyst appears in the dataset, without writing any scraping code yourself. ### Why use it? - **Event-driven biotech investing** — catalysts (trial readouts, approvals, recalls) are the primary drivers of biotech stock moves; this feed surfaces them as they happen. - **Competitive intelligence** — track a competitor's trial pipeline, phase progress, and FDA interactions over time. - **Alerting** — schedule the Actor and pipe new dataset items into Slack/email so nothing slips by while you're not watching the terminal. ### How to use it 1. Click **Try for free**. 2. Leave all filters empty and click **Start** to pull a market-wide snapshot of last week's catalysts (default: 7 days ago through today). 3. Or narrow the run: set `tickers`, `companies`, or `indications` to follow specific names, and/or set `phases` to focus on later-stage trials. 4. Click **Start** and wait for the run to finish. 5. Open the **Dataset** tab and download the results as JSON, CSV, or Excel — or connect the dataset to your own pipeline via the API. ### Input | Field | Type | Description | | --- | --- | --- | | `dateFrom` | string | Earliest event date (YYYY-MM-DD). Default: 7 days ago. | | `dateTo` | string | Latest event date (YYYY-MM-DD). Default: today. | | `sources` | array | Which sources to include: `clinicaltrials`, `fda`, `sec` (SEC EDGAR PDUFA dates). Default: all three. | | `eventTypes` | array | Filter to specific catalyst types. Empty = all. | | `tickers` | array | Limit to these public-company tickers. Empty = market-wide. | | `companies` | array | Limit to sponsors/applicants whose name contains these terms. | | `indications` | array | Limit to trials whose conditions contain these keywords. | | `phases` | array | Limit trial rows to these phases (e.g. `PHASE2`, `PHASE3`). | | `upcomingWindowDays` | integer | Flag trials whose primary completion date is within this many days as `UpcomingReadout`. Default: 90. | | `industryOnly` | boolean | Restrict trials to industry sponsors (the investable subset). Default: true. | | `onlyWithTicker` | boolean | Emit only events mapped to a public-company ticker. Default: false. | | `maxResults` | integer | Maximum rows to return. Set 0 to return none. Default: 1000. | | `contactEmail` | string | Used in the API User-Agent header (courtesy identification to ClinicalTrials.gov/FDA). | ### Output Each dataset item is one catalyst event, enriched with ticker mapping. Example: ```json { "eventType": "UpcomingReadout", "eventDate": null, "targetDate": "2026-08-15", "isForwardLooking": true, "daysUntil": 42, "company": "Example Therapeutics Inc", "ticker": "EXTX", "tickerConfidence": 0.95, "tickerMatchMethod": "exact", "drug": "EXT-101", "indications": ["Non-small cell lung cancer"], "phase": "PHASE3", "status": "RECRUITING", "source": "ClinicalTrials.gov", "identifier": "NCT01234567", "title": "A Study of EXT-101 in Advanced NSCLC", "officialUrl": "https://clinicaltrials.gov/study/NCT01234567", "isApproval": false, "isTrialFailure": false, "isUpcomingReadout": true, "sourceSnippet": null, "isPdufaDate": false } ```` Results are available as JSON, CSV, or Excel from the Dataset tab, or programmatically via the Apify API. ### Data table | Field | Meaning | | --- | --- | | `eventType` | Catalyst type: `NewRegistration`, `TrialCompleted`, `TrialTerminated`, `TrialSuspended`, `TrialWithdrawn`, `ResultsPosted`, `UpcomingReadout`, `DrugApproval`, `Recall`, `PDUFADate`. | | `eventDate` | Date the event already happened (ISO), or `null` for forward-looking events. | | `targetDate` | Expected/target date for a forward-looking event (ISO), or `null`. | | `isForwardLooking` | `true` if this event hasn't happened yet (e.g. an upcoming readout). | | `daysUntil` | Days between today and `targetDate`, or `null` if not applicable. | | `company` | Sponsor, applicant, or manufacturer name as reported by the source. | | `ticker` | Best-effort public-company ticker, or `null` if unmapped (private/foreign sponsor). | | `tickerConfidence` | 0–1 confidence score when a ticker was matched; `0.0` for a known-private company (match attempted, deliberately no ticker); `null` when no match was found. | | `tickerMatchMethod` | How the ticker was derived: `cik` (exact CIK match, PDUFA rows), `exact`, `alias`, `fuzzy`, `private`, `none`. | | `drug` | Drug/investigational product name, when available. | | `indications` | List of conditions/indications the event relates to. | | `phase` | The trial phase(s), e.g. `PHASE3` or `PHASE1/PHASE2`; `null` if not reported (FDA events, or trials with no listed phase). | | `status` | Current status string as reported by the source. | | `source` | `ClinicalTrials.gov`, `FDA`, or `SEC EDGAR`. | | `identifier` | Source identifier (NCT number or FDA application/enforcement number). | | `title` | Human-readable title of the trial or FDA record. | | `officialUrl` | Link to the source record. | | `isApproval` | `true` if `eventType` is `DrugApproval`. | | `isTrialFailure` | `true` if the event represents a negative trial outcome (terminated/suspended/withdrawn). | | `isUpcomingReadout` | `true` if `eventType` is `UpcomingReadout`. | | `sourceSnippet` | For PDUFA events: the ~200-char excerpt the date was parsed from, so you can audit it in one click; `null` otherwise. | | `isPdufaDate` | `true` if `eventType` is `PDUFADate`. | ### Known limitations - **PDUFA dates are announcement-based.** They are sourced from SEC EDGAR filings (8-K / 6-K) the moment a company discloses a target action date — not a curated calendar of every pending decision. A date announced before your `dateFrom` window won't reappear, so schedule recurring runs (daily/weekly) to accumulate a rolling calendar. - **PDUFA coverage is US-listed / ADR filers.** Wire-only press releases never filed with the SEC are not seen; the FDA itself does not publish a forward-looking PDUFA calendar. - **PDUFA date extraction is proximity-based and conservative.** A `Month DD, YYYY` date within ±150 characters of a trigger phrase ("PDUFA date", "target action date", …), strictly after the filing date and within 18 months, is attributed to that phrase. Each row carries a `sourceSnippet` audit excerpt; ambiguous multi-date filings are skipped rather than guessed. - **FDA coverage is approvals + recalls only.** FDA Warning Letters are not yet included. - **Phase is reported, not diffed.** The Actor reports each trial's current phase; it does not detect or flag phase-to-phase transitions (e.g. Phase 2 → Phase 3) as a distinct event. - **Ticker mapping is best-effort.** Matching is based on public SEC ticker/company-name data. Private companies, foreign private issuers, and name variants the mapper doesn't recognize will have `ticker: null` — this is expected, not a bug. ### Pricing This Actor uses Apify's **pay-per-result** pricing model with a free tier included, so you can try it at no cost before scaling up. See the Pricing tab on this page for current rates. ### FAQ, disclaimers, and support **Where does the data come from?** Exclusively public sources: ClinicalTrials.gov (the U.S. National Library of Medicine trial registry), openFDA (drug approvals and enforcement/recall data), and SEC EDGAR (company filings for PDUFA / FDA decision-date announcements). No private or paywalled data is used. **Is this investment advice?** No. This Actor is a data aggregation tool. Nothing it outputs is investment advice, a recommendation to buy or sell any security, or a substitute for your own due diligence. Always verify catalysts against the primary source (`officialUrl`) before acting on them. **How current is the data?** As current as ClinicalTrials.gov and openFDA themselves; the Actor does not cache or delay upstream updates beyond your chosen `dateFrom`/`dateTo` window. **Something looks wrong or missing.** Please open an issue on the Issues tab of this Actor with the run ID and a description of what you expected — we read every report. # Actor input Schema ## `dateFrom` (type: `string`): Earliest event date (YYYY-MM-DD). Default: 7 days ago. ## `dateTo` (type: `string`): Latest event date (YYYY-MM-DD). Default: today. ## `sources` (type: `array`): Which sources to include. ## `eventTypes` (type: `array`): Filter to specific catalyst types (e.g. DrugApproval, PDUFADate, UpcomingReadout, Recall). Empty = all. ## `tickers` (type: `array`): Limit to these public-company tickers. Empty = market-wide. ## `companies` (type: `array`): Limit to sponsors/applicants whose name contains these terms. ## `indications` (type: `array`): Limit to trials whose conditions contain these keywords. ## `phases` (type: `array`): Limit trial rows to these phases (e.g. PHASE2, PHASE3). ## `upcomingWindowDays` (type: `integer`): Flag trials whose primary completion date is within this many days as UpcomingReadout. ## `industryOnly` (type: `boolean`): Restrict trials to industry sponsors (the investable subset). ## `onlyWithTicker` (type: `boolean`): Emit only events mapped to a public-company ticker. ## `maxResults` (type: `integer`): Maximum rows to return. Set 0 to return none. ## `contactEmail` (type: `string`): Used in the User-Agent header sent to ClinicalTrials.gov, the FDA, and SEC EDGAR. Each requires a descriptive UA with a real contact; use a mailbox you monitor. ## Actor input object example ```json { "sources": [ "clinicaltrials", "fda", "sec" ], "eventTypes": [], "tickers": [], "companies": [], "indications": [], "phases": [], "upcomingWindowDays": 90, "industryOnly": true, "onlyWithTicker": false, "maxResults": 1000 } ``` # Actor output Schema ## `dataset` (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 = { "sources": [ "clinicaltrials", "fda", "sec" ], "eventTypes": [], "tickers": [], "companies": [], "indications": [], "phases": [] }; // Run the Actor and wait for it to finish const run = await client.actor("b3lch/biotech-catalyst-monitor").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 = { "sources": [ "clinicaltrials", "fda", "sec", ], "eventTypes": [], "tickers": [], "companies": [], "indications": [], "phases": [], } # Run the Actor and wait for it to finish run = client.actor("b3lch/biotech-catalyst-monitor").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 '{ "sources": [ "clinicaltrials", "fda", "sec" ], "eventTypes": [], "tickers": [], "companies": [], "indications": [], "phases": [] }' | apify call b3lch/biotech-catalyst-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=b3lch/biotech-catalyst-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Biotech Catalyst Monitor", "description": "Clean, ticker-mapped feed of biotech catalysts — trial readouts, status changes, results, FDA approvals & recalls, and upcoming PDUFA / FDA decision dates — from ClinicalTrials.gov, the FDA, and SEC EDGAR.", "version": "1.1", "x-build-id": "Rq3tSDDIQWZAKGL1m" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/b3lch~biotech-catalyst-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-b3lch-biotech-catalyst-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/b3lch~biotech-catalyst-monitor/runs": { "post": { "operationId": "runs-sync-b3lch-biotech-catalyst-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/b3lch~biotech-catalyst-monitor/run-sync": { "post": { "operationId": "run-sync-b3lch-biotech-catalyst-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "contactEmail" ], "properties": { "dateFrom": { "title": "Date from", "type": "string", "description": "Earliest event date (YYYY-MM-DD). Default: 7 days ago." }, "dateTo": { "title": "Date to", "type": "string", "description": "Latest event date (YYYY-MM-DD). Default: today." }, "sources": { "title": "Sources", "type": "array", "description": "Which sources to include.", "items": { "type": "string", "enum": [ "clinicaltrials", "fda", "sec" ], "enumTitles": [ "ClinicalTrials.gov", "FDA", "SEC EDGAR (PDUFA)" ] } }, "eventTypes": { "title": "Event types", "type": "array", "description": "Filter to specific catalyst types (e.g. DrugApproval, PDUFADate, UpcomingReadout, Recall). Empty = all.", "items": { "type": "string" } }, "tickers": { "title": "Tickers", "type": "array", "description": "Limit to these public-company tickers. Empty = market-wide.", "items": { "type": "string" } }, "companies": { "title": "Companies", "type": "array", "description": "Limit to sponsors/applicants whose name contains these terms.", "items": { "type": "string" } }, "indications": { "title": "Indications", "type": "array", "description": "Limit to trials whose conditions contain these keywords.", "items": { "type": "string" } }, "phases": { "title": "Phases", "type": "array", "description": "Limit trial rows to these phases (e.g. PHASE2, PHASE3).", "items": { "type": "string" } }, "upcomingWindowDays": { "title": "Upcoming window (days)", "minimum": 0, "type": "integer", "description": "Flag trials whose primary completion date is within this many days as UpcomingReadout.", "default": 90 }, "industryOnly": { "title": "Industry-sponsored only", "type": "boolean", "description": "Restrict trials to industry sponsors (the investable subset).", "default": true }, "onlyWithTicker": { "title": "Only rows with a ticker", "type": "boolean", "description": "Emit only events mapped to a public-company ticker.", "default": false }, "maxResults": { "title": "Max results", "minimum": 0, "type": "integer", "description": "Maximum rows to return. Set 0 to return none.", "default": 1000 }, "contactEmail": { "title": "Contact email", "type": "string", "description": "Used in the User-Agent header sent to ClinicalTrials.gov, the FDA, and SEC EDGAR. Each requires a descriptive UA with a real contact; use a mailbox you monitor." } } }, "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 } } } } } } } } } } ```