# Scrape Biotech Sponsor Pipeline by Ticker

**Use case:** 

Roll up trials, FDA approvals, device clearances, recalls, and shortages into one ticker-tagged row per sponsor, with the next catalyst date.

## Input

```json
{
  "mode": "pipeline",
  "sponsorIdentifiers": [
    "MRNA",
    "PFE",
    "LLY"
  ],
  "nctIds": [],
  "conditions": [],
  "interventions": [],
  "phases": [],
  "statuses": [],
  "countries": [],
  "applicantName": "Medtronic",
  "productCode": "",
  "devicePathways": [
    "510k",
    "pma"
  ],
  "drugName": "Ozempic",
  "seriousOnly": false,
  "recallClassifications": [],
  "recallDomains": [
    "drug",
    "device"
  ],
  "shortageStatus": "any",
  "dateFrom": "",
  "dateTo": "",
  "maxItems": 25,
  "maxItemsPerSource": 1000,
  "incrementalMode": false,
  "monitorTargets": [],
  "enableAiSummary": false,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

## Output

```json
{
  "sponsorName": {
    "label": "Sponsor",
    "format": "text"
  },
  "ticker": {
    "label": "Ticker",
    "format": "text"
  },
  "trialCountTotal": {
    "label": "Trials",
    "format": "number"
  },
  "trialCountActiveRecruiting": {
    "label": "Recruiting",
    "format": "number"
  },
  "drugApprovalCount": {
    "label": "Approvals",
    "format": "number"
  },
  "deviceClearanceCount": {
    "label": "Clearances",
    "format": "number"
  },
  "nextCatalystDate": {
    "label": "Next catalyst",
    "format": "date"
  },
  "nextCatalystType": {
    "label": "Catalyst type",
    "format": "text"
  },
  "regulatorySignal": {
    "label": "Reg signal",
    "format": "number"
  }
}
```

## About this Actor

This example demonstrates how to use [Clinical Trials & FDA Pipeline Intelligence Scraper](https://apify.com/constructive_calm/clinical-trials-fda-scraper) with a specific input configuration. Visit the [Actor detail page](https://apify.com/constructive_calm/clinical-trials-fda-scraper) to learn more, explore other use cases, and run it yourself.