ClinicalTrials.gov NCT Status Monitor

Re-check the NCT IDs on your clinops or competitive-intelligence list. Get overall status, enrollment, sponsor and last-update changes — and skip the trials that did not move.

This Actor takes a caller-owned list of NCT identifiers, reads the public ClinicalTrials.gov API v2, and writes one structured row per study. Pass the previous run's snapshot back in and you get INITIAL, UNCHANGED or CHANGED. This is not a trial dump or a site-scrape of investigator contact details.

---

What this Actor does

You already have NCT IDs (your own studies, a competitor set, or a therapeutic-area watchlist). You want a scheduled check for RECRUITING → COMPLETED, enrollment count moves, sponsor changes and new last-update dates — without a $0.12 start fee on every small run.

That is the job: an NCT status watchlist, not a ClinicalTrials.gov catalogue.

---

What you get

{
  "schemaVersion": 1,
  "id": "NCT00001372",
  "status": "ok",
  "nctId": "NCT00001372",
  "briefTitle": "Example brief title from ClinicalTrials.gov",
  "overallStatus": "COMPLETED",
  "enrollmentCount": 20,
  "lastUpdatePostDate": "2024-01-15",
  "startDate": "1993-09-01",
  "leadSponsor": "National Institute of Example",
  "statusVerifiedDate": "2023-12-01",
  "changeType": "INITIAL",
  "changedFields": [],
  "checkedAt": "2026-09-06T12:00:00.000Z",
  "sourceUrl": "https://clinicaltrials.gov/api/v2/studies/NCT00001372",
  "error": null
}

NCT00001372 is a public example identifier, not a customer or endorsement. Field values above are illustrative of shape. Missing source strings are null.

---

Main use cases

• Portfolio status. Daily or weekly re-check of studies you already manage.
• Competitive clinops. Watch a fixed competitor NCT list for status and enrollment moves.
• Sponsor changes. leadSponsor is a compared field.
• Publication pairing. Combine with the PubMed watchlist Actor for papers you already linked.
• n8n / MCP / EDC-adjacent jobs. Start from a server that holds APIFY_TOKEN.

---

Quick start

{
  "nctIds": ["NCT00001372"],
  "maxItems": 1
}

Run it, open the dataset, and save NEXT_SNAPSHOT from the default key-value store.

---

Repeat workflow

1. Keep one NCT watchlist per program or customer (1–50 IDs).
2. Start a bounded run. Schedule it yourself if you need a cadence.
3. Save NEXT_SNAPSHOT in your private workflow state.
4. On the next run pass it as previousSnapshot and set onlyChanges: true.
5. Route changeType: CHANGED rows (overallStatus, enrollmentCount, leadSponsor, lastUpdatePostDate) for review.

---

Input

Field	Type	Default	What it does
nctIds	array	—	1–50 IDs (NCT + 8 digits). Duplicates checked once.
maxItems	integer	50	1–50. Must cover all unique IDs.
onlyChanges	boolean	false	Suppress unchanged successful records without charging them.
previousSnapshot	object	—	Prior NEXT_SNAPSHOT with kind: "nct".

---

Pricing

Event	Price	When it happens
Successful watchlist result	$0.004	One successful NCT check written to the dataset
Actor start	none	No custom start fee

You are not charged for: failed requests, parse failures, retries, duplicate IDs, invalid input, or unchanged records suppressed by onlyChanges.

Worked example. 30 NCT IDs every weekday, 2 status changes/day after the first run → about $0.008 per run in Actor event charges.

How this compares

Actor	Price per result	Per-run start	Job
This Actor	$0.004	none	Caller-owned NCT watchlist
parseforge/clinicaltrials-gov-scraper (Store card, 2026-09-06)	$0.01067	$0.12	Dump-oriented listing

A 25-ID refresh costs $0.10 here and about $0.39 on a $0.01067 + $0.12 start card. Competitor prices change.

---

Using the API

curl --fail -X POST "https://api.apify.com/v2/acts/technicaldost~clinicaltrials-nct-status-monitor/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"nctIds":["NCT00001372"],"maxItems":1}'

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('technicaldost/clinicaltrials-nct-status-monitor').call({
    nctIds: ['NCT00001372'],
    maxItems: 1,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("technicaldost/clinicaltrials-nct-status-monitor").call(run_input={
    "nctIds": ["NCT00001372"],
    "maxItems": 1,
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["nctId"], row["overallStatus"], row["changeType"])

n8n / MCP. Same pattern as the other watchlist Actors: start from a server, poll, read the dataset and NEXT_SNAPSHOT. Keep the token off the public internet.

---

Limitations

• Public study metadata only. No investigator emails, phone numbers, or documents behind login.
• This is not a regulatory submission, safety signal, or medical-advice product.
• ClinicalTrials.gov availability governs results. One request at a time, no automatic retries.
• At most 1,000 snapshot records are retained.

Source: public ClinicalTrials.gov API v2. Not affiliated with NIH, NLM or ClinicalTrials.gov.

---

Related Actors

• PubMed Watchlist Monitor — metadata changes on PMIDs you already track.
• OFAC SDN Watchlist Monitor — exact uid/name re-screen of known SDN entries.

---

Changelog

See CHANGELOG.md. Release 1.0.0 (2026-09-06): caller-owned NCT watchlists, status/enrollment deltas, $0.004 per successful result, no start fee.

Output example

Each result is one dataset item. A real item from a test run (long fields shortened):

{
  "schemaVersion": 1,
  "id": "NCT00001372",
  "status": "ok",
  "nctId": "NCT00001372",
  "briefTitle": "Study of Systemic Lupus Erythematosus",
  "overallStatus": "RECRUITING",
  "enrollmentCount": 2000,
  "lastUpdatePostDate": "2026-10-09",
  "startDate": "1994-02-10",
  "leadSponsor": "National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)",
  "statusVerifiedDate": "2026-10-07",
  "changeType": "INITIAL"
}

Use ClinicalTrials.gov NCT Status Monitor with AI agents (MCP)

Give Claude, ChatGPT, Cursor, VS Code or any MCP client this Actor as a tool through the hosted Apify MCP server. The agent sees the input fields with descriptions and example values, runs the Actor, and reads the results.

MCP server URL (this Actor only):

https://mcp.apify.com/?tools=technicaldost/clinicaltrials-nct-status-monitor

Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/clinicaltrials-nct-status-monitor" --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Cursor, VS Code, Claude Desktop and other clients (mcp.json or the client's MCP settings):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/clinicaltrials-nct-status-monitor",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Clients that support sign-in (such as Claude.ai connectors) can use the URL without a token and log in to Apify instead. Get your token in Apify Console → Settings → API & Integrations, or generate a ready config for your client at mcp.apify.com. In the agent the tool is named technicaldost--clinicaltrials-nct-status-monitor; ask it, for example, to "run ClinicalTrials.gov NCT Status Monitor with {"nctIds": ["NCT00001372"]}".

AI agents without an Apify account can also run and pay for this Actor per request with x402 agentic payments.

Run ClinicalTrials.gov NCT Status Monitor via API

Run the Actor and get its results in one call (replace YOUR_APIFY_TOKEN):

curl -X POST "https://api.apify.com/v2/acts/technicaldost~clinicaltrials-nct-status-monitor/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"nctIds": ["NCT00001372"]}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/clinicaltrials-nct-status-monitor").call(run_input={"nctIds": ["NCT00001372"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/clinicaltrials-nct-status-monitor').call({"nctIds": ["NCT00001372"]});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Long runs: start them with POST /v2/acts/technicaldost~clinicaltrials-nct-status-monitor/runs and fetch the dataset when the run finishes, or receive a webhook.

FAQ

Can I use ClinicalTrials.gov NCT Status Monitor with AI agents like Claude or ChatGPT?

Yes. Connect the Apify MCP server with ?tools=technicaldost/clinicaltrials-nct-status-monitor (see above) and the agent can run the Actor and read its results on its own.

Can I call ClinicalTrials.gov NCT Status Monitor from my own code?

Yes. Use the REST API, or the official Python and JavaScript clients shown above. Results are available as JSON, CSV, Excel, XML or HTML.

How do I run it on a schedule?

Save your input as a task in Apify Console and add a schedule (for example, daily). Use webhooks or integrations to send each run's results onward.

Is it legal to use this Actor?

It works with publicly available data. Make sure your use complies with the source website's terms and with data protection laws such as GDPR, especially for personal data.

Something doesn't work or I need a feature. What should I do?

Open an issue in the Issues tab on this Actor's page with an example input, and we'll look into it.