{
  "api_version": "1",
  "request": {
    "url": "https://clinicaltrialsfind.com/api/v1/search.json?condition=Large+Language+Model",
    "query": {
      "condition": "Large Language Model"
    },
    "page_size": 10
  },
  "pagination": {
    "page": 1,
    "page_size": 10,
    "total_count": 27,
    "total_pages": 3,
    "next_page_url": "https://clinicaltrialsfind.com/api/v1/search.json?condition=Large+Language+Model&page=2&page_size=10",
    "previous_page_url": null
  },
  "source": "remote",
  "last_synced_at": "2026-06-10T13:51:27.819Z",
  "attribution": "Data derived from public ClinicalTrials.gov records. The official record at https://clinicaltrials.gov/ remains the source of truth for current availability, contacts, and full study details.",
  "notes": [
    "This endpoint exposes only public summary fields — no participant contact emails, phone numbers, or scraped investigator contact details.",
    "For contact information and full protocol detail, follow each trial's `official_url` to the ClinicalTrials.gov record.",
    "This API is a navigational aid. It does not provide medical advice, eligibility determinations, or compensation guarantees."
  ],
  "trials": [
    {
      "nct_id": "NCT07107152",
      "title": "Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Colorectal Cancer Control and Prevention"
      ],
      "interventions": [
        {
          "name": "single GPT generated message",
          "type": "BEHAVIORAL"
        },
        {
          "name": "AI Chatbot",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Expert-Written Patient Materials",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "University of Pennsylvania",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "45 Years",
        "maximum_age": "75 Years",
        "sex": "ALL",
        "summary": "45 Years to 75 Years"
      },
      "enrollment_count": 915,
      "start_date": "2025-06-11",
      "completion_date": "2025-06-21",
      "has_results": false,
      "last_update_posted_date": "2025-08-07",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Philadelphia, Pennsylvania",
      "locations": [
        {
          "city": "Philadelphia",
          "state": "Pennsylvania"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07107152"
    },
    {
      "nct_id": "NCT07337577",
      "title": "Large Language Model-Generated Messages to Improve Guideline-Directed Medical Therapy in Heart Failure",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Heart Failure"
      ],
      "interventions": [
        {
          "name": "LLM-GDMT Clinical Decision Support Tool",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Brigham and Women's Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "85 Years",
        "sex": "ALL",
        "summary": "18 Years to 85 Years"
      },
      "enrollment_count": 500,
      "start_date": "2026-06-01",
      "completion_date": "2027-12-01",
      "has_results": false,
      "last_update_posted_date": "2026-04-21",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Boston, Massachusetts",
      "locations": [
        {
          "city": "Boston",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07337577"
    },
    {
      "nct_id": "NCT06911645",
      "title": "Diagnostic Reasoning With Customized GPT-4 Model",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Pathologic Processes",
        "Disease"
      ],
      "interventions": [
        {
          "name": "Immediate access to customized version of GPT-4",
          "type": "OTHER"
        },
        {
          "name": "Access to customized version of GPT-4 following use of conventional resources",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Stanford University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": null,
        "maximum_age": null,
        "sex": "ALL",
        "summary": "Not listed"
      },
      "enrollment_count": 70,
      "start_date": "2024-12-16",
      "completion_date": "2025-01-24",
      "has_results": false,
      "last_update_posted_date": "2025-04-04",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Palo Alto, California",
      "locations": [
        {
          "city": "Palo Alto",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06911645"
    },
    {
      "nct_id": "NCT06002425",
      "title": "Treatment Recommendations for Gastrointestinal Cancers Via Large Language Models",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Gastrointestinal Neoplasm Malignant"
      ],
      "interventions": [
        {
          "name": "Clinician-Directed Treatment Plan",
          "type": "OTHER"
        },
        {
          "name": "ChatGPT-Assisted Treatment Plan",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Chinese Academy of Sciences",
      "sponsor_class": "OTHER_GOV",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 400,
      "start_date": "2023-08-29",
      "completion_date": "2028-12-31",
      "has_results": false,
      "last_update_posted_date": "2023-09-08",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Duarte, California",
      "locations": [
        {
          "city": "Duarte",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06002425"
    },
    {
      "nct_id": "NCT07416734",
      "title": "RCT of HeartBot in Women",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Participants Must be Women Aged 25 Years or Older",
        "Participants Should Have no Self-reported History of Heart Disease or Stroke",
        "Participants Should Have no Terminal Illness or Diagnosed Cognitive Impairment, Including Alzheimer's Disease",
        "Participants Should Not be a Healthcare Professionals or Healthcare Trainees",
        "Participants Should Not be Employed in the Healthcare Field",
        "Participants Should Reside in the United States and be a University of California, San Francisco Health Patient",
        "Participants Should Possess a Smartphone With an Active Data Plan or Access to Wi-Fi"
      ],
      "interventions": [
        {
          "name": "HeartBot II Program",
          "type": "OTHER"
        },
        {
          "name": "Waitlist Control",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "University of California, San Francisco",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "25 Years",
        "maximum_age": null,
        "sex": "FEMALE",
        "summary": "25 Years and older · Female only"
      },
      "enrollment_count": 200,
      "start_date": "2026-03-01",
      "completion_date": "2027-06-30",
      "has_results": false,
      "last_update_posted_date": "2026-02-18",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "San Francisco, California",
      "locations": [
        {
          "city": "San Francisco",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07416734"
    },
    {
      "nct_id": "NCT07105397",
      "title": "Evaluating Conversational Artificial Intelligence for Depression Management",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Major Depressive Disorder (MDD)"
      ],
      "interventions": [
        {
          "name": "Conversational AI system vs Usual Care",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "George Mason University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "85 Years",
        "sex": "ALL",
        "summary": "18 Years to 85 Years"
      },
      "enrollment_count": 130,
      "start_date": "2026-04-15",
      "completion_date": "2028-06-30",
      "has_results": false,
      "last_update_posted_date": "2026-04-09",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Fairfax, Virginia",
      "locations": [
        {
          "city": "Fairfax",
          "state": "Virginia"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07105397"
    },
    {
      "nct_id": "NCT07199231",
      "title": "OpenEvidence Safety and Comparative Efficacy of Four LLM's in Clinical Practice",
      "overall_status": "ENROLLING_BY_INVITATION",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "AI (Artificial Intelligence)",
        "Large Language Model",
        "Generative Artificial Intelligence"
      ],
      "interventions": [
        {
          "name": "AI clinical reference tool",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Cambridge Health Alliance",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": null,
        "maximum_age": null,
        "sex": "ALL",
        "summary": "Not listed"
      },
      "enrollment_count": 20,
      "start_date": "2025-10-01",
      "completion_date": "2026-09-30",
      "has_results": false,
      "last_update_posted_date": "2026-05-22",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Cambridge, Massachusetts",
      "locations": [
        {
          "city": "Cambridge",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07199231"
    },
    {
      "nct_id": "NCT07214831",
      "title": "A Feasibility and Acceptability Study of a Large Language Model-based Chatbot for Brief Alcohol Intervention Among Emerging Adults",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Alcohol Use Disorder"
      ],
      "interventions": [
        {
          "name": "Large language model-based chatbot brief alcohol intervention session",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "Massachusetts General Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "29 Years",
        "sex": "ALL",
        "summary": "18 Years to 29 Years"
      },
      "enrollment_count": 20,
      "start_date": "2027-06-01",
      "completion_date": "2028-08-31",
      "has_results": false,
      "last_update_posted_date": "2025-10-22",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Boston, Massachusetts",
      "locations": [
        {
          "city": "Boston",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07214831"
    },
    {
      "nct_id": "NCT06624605",
      "title": "Enhancing Interdisciplinary Understanding of Ophthalmology Notes Through a Local Large Language Model",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Communication",
        "Artificial Intelligence (AI)",
        "Artificial Intelligence Technology",
        "Interdisciplinary Communication"
      ],
      "interventions": [
        {
          "name": "Large Language Model-generated Plain Language Summary of Ophthalmology notes",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "John J Chen",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 851,
      "start_date": "2024-02-01",
      "completion_date": "2024-05-31",
      "has_results": false,
      "last_update_posted_date": "2024-10-03",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Rochester, Minnesota",
      "locations": [
        {
          "city": "Rochester",
          "state": "Minnesota"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06624605"
    },
    {
      "nct_id": "NCT06935253",
      "title": "Large Language Models To Improve the Quality of Care of Cardiology Patients",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Hypertrophic Cardiomyopathy (HCM)",
        "Cardiomyopathy",
        "Genetic Disease",
        "Cardiology"
      ],
      "interventions": [
        {
          "name": "Large Language Model",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Stanford University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 12,
      "start_date": "2025-01-10",
      "completion_date": "2025-12",
      "has_results": false,
      "last_update_posted_date": "2025-05-15",
      "last_synced_at": "2026-06-10T13:51:27.819Z",
      "location_count": 1,
      "location_summary": "Palo Alto, California",
      "locations": [
        {
          "city": "Palo Alto",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06935253"
    }
  ]
}