Clinical Trials Monitor | Condition & Recruitment Watch

Monitor ClinicalTrials.gov for new and updated studies matching condition keywords and recruitment status — one digest row per configured watchlist query without brittle broad crawling.

Store Quickstart

Run this actor with your target input. Results appear in the Apify Dataset and can be piped to webhooks for real-time delivery. Use dryRun to validate before committing to a schedule.

Key Features

• 📈 Competitive intelligence — Aggregates cross-platform signals (reviews, listings, catalogs)
• 🌐 Multi-source aggregation — Unifies iOS/Android/Shopify/market data in one run
• 📊 Trend detection — Rolling averages, sentiment scoring, and share-of-voice metrics
• 🎯 Targeted queries — Focused brand/product/keyword watchlists
• 📡 Webhook intel push — Deliver insights to marketing/product teams in real-time

Use Cases

Who	Why
Developers	Automate recurring data fetches without building custom scrapers
Data teams	Pipe structured output into analytics warehouses
Ops teams	Monitor changes via webhook alerts
Product managers	Track competitor/market signals without engineering time

Input

Field	Type	Default	Description
watchlist	array	required	One entry per monitored query. Each produces one digest row in the output. At minimum set id, name, and condition. Add r
watchTerms	string	—	Sponsor names, principal investigators, or institution names to flag in study digests. Any study matching a watch term r
maxStudiesPerQuery	integer	50	Upper bound on studies fetched per query per run. Increase for discovery; keep lower for recurring digest runs.
delivery	string	"dataset"	dataset stores results in the Apify dataset. webhook posts the digest JSON to webhookUrl.
webhookUrl	string	—	POST target for trial digest payload. Leave empty for dataset delivery.
datasetMode	string	"all"	all emits every query digest row. action_needed emits only queries with watch-term hits or new recruiting studies. new_o
snapshotKey	string	"clinical-trials-monitor-state"	Stable key used to persist seen study NCT IDs across recurring runs so new_only and action_needed modes stay comparable.
clinicalTrialsApiUrl	string	"https://clinicaltrials.gov/api/v2/studies"	ClinicalTrials.gov API v2 studies endpoint. No API key required.

Input Example

{
  "maxStudiesPerQuery": 50,
  "delivery": "dataset",
  "datasetMode": "all",
  "snapshotKey": "clinical-trials-monitor-state",
  "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies",
  "requestTimeoutSeconds": 30,
  "notifyOnNoNew": true,
  "dryRun": false
}

Output

Field	Type	Description
meta	object
errors	array
digests	array
digests[].queryId	string
digests[].queryName	string
digests[].condition	string
digests[].recruitmentStatusFilter	array
digests[].checkedAt	timestamp
digests[].status	string
digests[].newStudyCount	number
digests[].totalStudyCount	number
digests[].recruitingCount	number
digests[].changedSinceLastRun	boolean
digests[].actionNeeded	boolean
digests[].recommendedAction	string
digests[].topSponsors	array
digests[].watchTermHits	array
digests[].signalTags	array
digests[].studies	array
digests[].error	null

Output Example

{
  "meta": {
    "generatedAt": "2026-04-15T09:00:00.000Z",
    "now": "2026-04-15T09:00:00.000Z",
    "queryCount": 2,
    "totalStudies": 7,
    "newStudies": 4,
    "watchTermHitCount": 2,
    "actionNeededCount": 1,
    "snapshot": {
      "key": "clinical-trials-monitor-sample",
      "loadedFrom": "local",
      "savedTo": "local"
    },
    "warnings": [],
    "executiveSummary": {
      "overallStatus": "action_needed",
      "brief": "1 query(s) have sponsor watch-term hits requiring review.",
      "topSponsors": [
        {
          "name": "Pfizer Inc",
          "studyCount": 2,
          "isWatchTermHit": true
        },
        {
          "name": "Novo Nordisk A/S",
          "studyCount": 1,
          "isWatchTermHit": true
        },
        {
          "name": "AstraZeneca",
          "studyCount": 2,
          "isWatchTermHit": false
        }
      ],
      "watchTermHits": [
        {
          "term": "Pfizer",
          "studyId": "NCT05001234",
          "sponsor": "Pfizer Inc",

API Usage

Run this actor programmatically using the Apify API. Replace YOUR_API_TOKEN with your token from Apify Console → Settings → Integrations.

cURL

curl -X POST "https://api.apify.com/v2/acts/taroyamada~clinical-trials-pipeline-monitor/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "maxStudiesPerQuery": 50, "delivery": "dataset", "datasetMode": "all", "snapshotKey": "clinical-trials-monitor-state", "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies", "requestTimeoutSeconds": 30, "notifyOnNoNew": true, "dryRun": false }'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("taroyamada/clinical-trials-pipeline-monitor").call(run_input={
  "maxStudiesPerQuery": 50,
  "delivery": "dataset",
  "datasetMode": "all",
  "snapshotKey": "clinical-trials-monitor-state",
  "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies",
  "requestTimeoutSeconds": 30,
  "notifyOnNoNew": true,
  "dryRun": false
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('taroyamada/clinical-trials-pipeline-monitor').call({
  "maxStudiesPerQuery": 50,
  "delivery": "dataset",
  "datasetMode": "all",
  "snapshotKey": "clinical-trials-monitor-state",
  "clinicalTrialsApiUrl": "https://clinicaltrials.gov/api/v2/studies",
  "requestTimeoutSeconds": 30,
  "notifyOnNoNew": true,
  "dryRun": false
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Tips & Limitations

• Run weekly for trend tracking; daily for competitive launch monitoring.
• Use webhook delivery to push insights into your BI tools or marketing Slack.
• Archive results in Apify Dataset for your own historical trend analysis.
• Combine with ai-visibility-monitor-actor for AI-era brand surface coverage.
• Start with a small watchlist, iterate on keyword precision before scaling.

FAQ

What platforms are covered?

Varies by actor — see each actor's input schema for the full source list. Most cover 3–8 major platforms per vertical.

How is data deduplicated across sources?

The actor normalizes entity identifiers (brand name, SKU) before aggregation — cross-source duplicates are merged.

Can I whitelabel the output?

Dataset rows are raw data — build your own presentation layer to whitelabel.

Is the sentiment scoring accurate?

Sentiment uses rule-based + keyword scoring tuned for English. For non-English content, treat scores as directional rather than absolute.

Can I share the dashboard output?

Export from Dataset API into your BI tool (Looker, Metabase, Tableau) for stakeholder-facing dashboards.

Related Actors

Market Intelligence cluster — explore related Apify tools:

• AI Brand Visibility Monitor API | Google + Reddit Tracker — See whether your AI brand is appearing, climbing, or disappearing in Google and Reddit prompts, then get rank deltas, competitor overlap, and weekly action items.
• Shopify Store Intelligence API | Catalog + Merch Signals — Analyze public Shopify storefront endpoints for store metadata, collections, product samples, and vendor/tag rollups.
• App Review Intelligence API | App Store + Google Play Summary — Monitor one app across the App Store and Google Play, cluster review themes, flag rating drift, and return recommended actions in a single summary row.
• TED, SAM.gov & Grants Monitor | Bid Alerts & Award Watch — Public-sector tender monitoring for teams that need TED, SAM.

Cost

Pay Per Event:

• actor-start: $0.01 (flat fee per run)
• dataset-item: $0.003 per output item

Example: 1,000 items = $0.01 + (1,000 × $0.003) = $3.01

No subscription required — you only pay for what you use.