# Clinical Trial & FDA Signal Alerts (`taroyamada/clinical-trials-fda-watch-monitor`) Actor Watch drugs, sponsors, and conditions across ClinicalTrials.gov and openFDA: new-trial alerts, trial status changes, and FDA drug recall signals as source-linked rows. No-change runs are free. - **URL**: https://apify.com/taroyamada/clinical-trials-fda-watch-monitor.md - **Developed by:** [naoki anzai](https://apify.com/taroyamada) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $100.00 / 1,000 new trial alerts 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 ## Clinical Trial & FDA Signal Alerts — Drug, Sponsor & Condition Watch Get alerted when a **new clinical trial** appears for your drug, condition, or competitor, when a tracked trial **changes status** (for example RECRUITING → TERMINATED) or slips its **primary completion date**, and when an **FDA drug recall / enforcement signal** hits your watched products or firms — without re-reading ClinicalTrials.gov and openFDA every morning. Built for pharma/biotech competitive intelligence, medical affairs, investor research, and market analysts. Official public APIs only — **no API keys, no login, no proxies**. ### What you get | Row | Event | Price | When | |---|---|---|---| | New trial alert | `new-trial-alert` | $0.10 | A trial matching your watch appears that was not tracked before | | Trial status change alert | `trial-status-change-alert` | $0.08 | A tracked trial's overall status or primary completion date changed | | FDA signal alert | `fda-signal-alert` | $0.10 | A new or status-changed FDA drug enforcement (recall) report matches your watch | | Pipeline watch report | `pipeline-watch-report` | $5 | Opt-in (`generateReport: true`): one source-linked summary row per run with alerts | | Watch export | `watch-export-generated` | $7 | Opt-in (`emitExport: true`): one export bundle row per run with alerts | | Raw record row | `raw-record-row` | $0.006 | Opt-in (`emitRawRows: true`): every normalized source record | **No-change runs are free.** The first run saves a baseline and charges nothing (default `initialRunMode: "baseline_only"`). After that, you are only charged when something actually changed. ### Quickstart 1. Define a watch: ```json { "watches": [ { "id": "glp1-obesity-watch", "drugs": ["semaglutide", "tirzepatide"], "conditions": ["obesity"], "sponsors": ["Novo Nordisk", "Eli Lilly"] } ] } ```` 2. Run once — the baseline is saved, nothing is charged. 3. Add a daily/weekly Schedule. Each run emits only what changed since the last run: new trials, status flips, completion-date slips, and new FDA recall signals. Want the current matches immediately (instead of a silent baseline)? Set `initialRunMode: "emit_backfill"` on the first run. ### How watches match - **Within a field, terms are OR** — `"drugs": ["semaglutide", "tirzepatide"]` matches trials with either drug. - **Across fields, conditions are AND** (ClinicalTrials.gov) — drugs + conditions + sponsors narrows the trial set. Want "any trial of drug X **or** any trial by sponsor Y"? Use two watches. - On openFDA, `drugs`/`keywords` match `product_description` and `sponsors` match `recalling_firm` (merged, deduplicated). - Optional `phases` (e.g. `["PHASE3"]`) and `statuses` filters apply to trials. Note: a `statuses` filter can hide status-change alerts for trials that leave the filtered set — leave it empty for termination monitoring. ### Inputs | Field | Default | Notes | |---|---|---| | `watches` | — (required) | Each needs at least one of `drugs`, `conditions`, `sponsors`, `keywords` | | `sources` | `["trials", "fda"]` | ClinicalTrials.gov API v2 + openFDA drug enforcement | | `monitorKey` | `my-clinical-trials-fda-watch` | Stable key for the persistent monitoring state | | `initialRunMode` | `baseline_only` | `emit_backfill` to emit current matches on the first run | | `generateReport` | `false` | Opt-in $5 report row | | `emitExport` | `false` | Opt-in $7 export row | | `emitRawRows` | `false` | Opt-in $0.006 raw rows | | `maxRecordsPerWatch` | `50` | Per watch and source, max 100 | | `maxChargeUsd` | `25` | Hard budget: the run fails closed before delivering rows that would exceed it | ### Why not just the free APIs? ClinicalTrials.gov and openFDA are free — but they answer "what exists right now", not "**what changed since I last looked**". This actor adds the monitoring layer: normalized records across both sources, persistent per-watch state, new/changed diffing (including RECRUITING → TERMINATED flips and completion-date slips), deduplication, zero-noise scheduled runs that stay free when nothing changed, and a hard `maxChargeUsd` budget. It also runs on a schedule with webhooks/dataset integrations and works as an AI-agent/MCP tool — no code to host. ### Data sources, limits, compliance - Sources: [ClinicalTrials.gov API v2](https://clinicaltrials.gov/data-api/api) and [openFDA drug enforcement](https://open.fda.gov/apis/drug/enforcement/) — official public US government APIs, queried directly with no keys. - Rows summarize public registry/enforcement data for human review; sources can revise or remove records after capture. openFDA data is not a complete list of FDA actions and **does not establish causation**. - Not medical, clinical, regulatory, legal, or investment advice. No patient-level data or PHI. See `docs/source-compliance.md`. ### Related actors - [Government Tender & Grants Alert Report](https://apify.com/taroyamada/government-tender-grants-monitor) — the same free-when-unchanged watch model for public tenders and grants. - [OpenAlex Research Intelligence](https://apify.com/taroyamada/openalex-research-intelligence) — new-paper alerts for authors, institutions, and concepts. # Actor input Schema ## `dryRun` (type: `boolean`): Return sample value-event rows without fetching live sources. ## `watches` (type: `array`): Drug, condition, sponsor, and keyword watches. Each watch needs at least one of drugs, conditions, sponsors, or keywords. Optional phases/statuses filters apply to ClinicalTrials.gov only; note a statuses filter can hide status-change alerts for trials that leave the filtered set. ## `sources` (type: `array`): Public sources to query. No API keys required. ## `monitorKey` (type: `string`): Stable key for stateful no-change monitoring. ## `initialRunMode` (type: `string`): baseline\_only saves state and emits no billable rows. emit\_backfill emits current matches for charged proof or first reports. ## `generateReport` (type: `boolean`): Opt-in: generate a source-linked pipeline watch report row when alerts are found. ## `emitExport` (type: `boolean`): Opt-in: generate an export bundle row when alerts are found. ## `emitRawRows` (type: `boolean`): Optional low-priced raw rows. Main value is alert rows. ## `maxRecordsPerWatch` (type: `integer`): Maximum source records to normalize per watch and source before dedupe and alert generation. ## `maxChargeUsd` (type: `number`): Fail closed before delivery if the estimated PPE charge would exceed this amount. ## Actor input object example ```json { "dryRun": false, "watches": [ { "id": "glp1-obesity-watch", "drugs": [ "semaglutide", "tirzepatide" ], "conditions": [ "obesity" ], "sponsors": [ "Novo Nordisk", "Eli Lilly" ] } ], "sources": [ "trials", "fda" ], "monitorKey": "my-clinical-trials-fda-watch", "initialRunMode": "baseline_only", "generateReport": false, "emitExport": false, "emitRawRows": false, "maxRecordsPerWatch": 50, "maxChargeUsd": 25 } ``` # 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 = { "watches": [ { "id": "glp1-obesity-watch", "drugs": [ "semaglutide", "tirzepatide" ], "conditions": [ "obesity" ], "sponsors": [ "Novo Nordisk", "Eli Lilly" ] } ] }; // Run the Actor and wait for it to finish const run = await client.actor("taroyamada/clinical-trials-fda-watch-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 = { "watches": [{ "id": "glp1-obesity-watch", "drugs": [ "semaglutide", "tirzepatide", ], "conditions": ["obesity"], "sponsors": [ "Novo Nordisk", "Eli Lilly", ], }] } # Run the Actor and wait for it to finish run = client.actor("taroyamada/clinical-trials-fda-watch-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 '{ "watches": [ { "id": "glp1-obesity-watch", "drugs": [ "semaglutide", "tirzepatide" ], "conditions": [ "obesity" ], "sponsors": [ "Novo Nordisk", "Eli Lilly" ] } ] }' | apify call taroyamada/clinical-trials-fda-watch-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/clinical-trials-fda-watch-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Clinical Trial & FDA Signal Alerts", "description": "Watch drugs, sponsors, and conditions across ClinicalTrials.gov and openFDA: new-trial alerts, trial status changes, and FDA drug recall signals as source-linked rows. No-change runs are free.", "version": "0.1", "x-build-id": "Bv0MNjXYR6BsKWaZy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~clinical-trials-fda-watch-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-clinical-trials-fda-watch-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taroyamada~clinical-trials-fda-watch-monitor/runs": { "post": { "operationId": "runs-sync-taroyamada-clinical-trials-fda-watch-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taroyamada~clinical-trials-fda-watch-monitor/run-sync": { "post": { "operationId": "run-sync-taroyamada-clinical-trials-fda-watch-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "watches" ], "properties": { "dryRun": { "title": "Dry run", "type": "boolean", "description": "Return sample value-event rows without fetching live sources.", "default": false }, "watches": { "title": "Watches", "type": "array", "description": "Drug, condition, sponsor, and keyword watches. Each watch needs at least one of drugs, conditions, sponsors, or keywords. Optional phases/statuses filters apply to ClinicalTrials.gov only; note a statuses filter can hide status-change alerts for trials that leave the filtered set." }, "sources": { "title": "Sources", "type": "array", "description": "Public sources to query. No API keys required.", "items": { "type": "string", "enum": [ "trials", "fda" ], "enumTitles": [ "ClinicalTrials.gov", "openFDA drug enforcement" ] }, "default": [ "trials", "fda" ] }, "monitorKey": { "title": "Monitor key", "type": "string", "description": "Stable key for stateful no-change monitoring.", "default": "my-clinical-trials-fda-watch" }, "initialRunMode": { "title": "Initial run mode", "enum": [ "baseline_only", "emit_backfill" ], "type": "string", "description": "baseline_only saves state and emits no billable rows. emit_backfill emits current matches for charged proof or first reports.", "default": "baseline_only" }, "generateReport": { "title": "Generate watch report ($5)", "type": "boolean", "description": "Opt-in: generate a source-linked pipeline watch report row when alerts are found.", "default": false }, "emitExport": { "title": "Generate export row ($7)", "type": "boolean", "description": "Opt-in: generate an export bundle row when alerts are found.", "default": false }, "emitRawRows": { "title": "Emit raw record rows", "type": "boolean", "description": "Optional low-priced raw rows. Main value is alert rows.", "default": false }, "maxRecordsPerWatch": { "title": "Max records per watch", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum source records to normalize per watch and source before dedupe and alert generation.", "default": 50 }, "maxChargeUsd": { "title": "Max charge USD", "minimum": 0.1, "maximum": 250, "type": "number", "description": "Fail closed before delivery if the estimated PPE charge would exceed this amount.", "default": 25 } } }, "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 } } } } } } } } } } ```