ClinicalTrials.gov Search & Export
Pricing
Pay per event
Search ClinicalTrials.gov by condition, drug, sponsor, phase, status, and country, and export clinical trials to CSV, Excel, or JSON with sponsors, dates, enrollment, and trial sites.
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Pay per event
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Data Lantern
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You can access the ClinicalTrials.gov Search & Export programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
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Any words in the study record, for example: GLP-1, pediatric, quality of life." }, "intervention": { "title": "Drug or intervention", "type": "string", "description": "Optional. For example: semaglutide, pembrolizumab, cognitive behavioral therapy." }, "sponsor": { "title": "Sponsor or collaborator", "type": "string", "description": "Optional. Company or institution, for example: Pfizer, National Cancer Institute." }, "phase": { "title": "Phase", "type": "array", "description": "Optional. Leave empty for all phases.", "items": { "type": "string", "enum": [ "EARLY_PHASE1", "PHASE1", "PHASE2", "PHASE3", "PHASE4", "NA" ], "enumTitles": [ "Early Phase 1", "Phase 1", "Phase 2", "Phase 3", "Phase 4", "Not applicable" ] }, "default": [] }, "status": { "title": "Recruitment status", "type": "array", "description": "Optional. Leave empty for all statuses.", "items": { "type": "string", "enum": [ "RECRUITING", "NOT_YET_RECRUITING", "ENROLLING_BY_INVITATION", "ACTIVE_NOT_RECRUITING", "COMPLETED", "SUSPENDED", "TERMINATED", "WITHDRAWN", "UNKNOWN" ], "enumTitles": [ "Recruiting", "Not yet recruiting", "Enrolling by invitation", "Active, not recruiting", "Completed", "Suspended", "Terminated", "Withdrawn", "Unknown status" ] }, "default": [] }, "country": { "title": "Country", "type": "string", "description": "Optional. Studies with at least one site in this country, for example: United States, Germany, Japan." }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "newest", "lastUpdated", "startDate" ], "type": "string", "description": "Relevance works best with search words. Use 'Last updated' to monitor changes.", "default": "relevance" }, "maxResults": { "title": "Maximum results", "minimum": 0, "type": "integer", "description": "Stop after this many studies. 0 means no limit.", "default": 50 } } }, "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 }, "PROXY_UNBLOCKER_UNITS": { "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 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for ClinicalTrials.gov Search & Export from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: