Ex-vivo Confocal Imaging and Proteomic Profiling to Determine Treatment Response in Children With IBD

Part of paid clinical trials in Arlington, Texas.

Sponsor
Cook Children's Health Care System
Study ID
NCT07121920
Status
Not Yet Recruiting

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Conditions

  • IBD
  • IBD (Inflammatory Bowel Disease)
  • IBD - Inflammatory Bowel Disease

Eligibility Criteria

Sex
ALL
Age
2 Years - 21 Years
Healthy Volunteers
Not accepted

Interventions

  • Confocal Laser Endomicroscopy — DEVICE
    Patients will undergo Esophagogastroduodenoscopy (EGD) and/or Ileocolonoscopy (IC) EGD with CLE as per standard of care. Each participant will have 3-4 mucosal biopsies taken from the terminal ileum, rectosigmoid and cecum, ideally from the most affected areas of accessible segment. Ex vivo staining of biopsied tissue will be expanded to include FITC-labeled antibodies to cytokines IL12 and IL12/IL23 and to cytokine receptors IL12R and IL23R and possibly other cytokines, receptors and adhesion molecules. All biopsies tested for membrane bound antibodies will be done using CLE technology with artificial intelligence (AI). The cellular landscape will be characterized by surveying surface markers using bar-coded antibodies and performing gene expression profiling on every cell within inflamed tissue of patients with IBD. We will develop algorithm using AI to predict responders versus non-responders and to further subclassify IBD patients using phenotype data.

Study Details

This study aims to test the overall hypothesis that the membrane tissue binding capacity of cytokines in the biopsied tissue of patients with Inflammatory Bowel Disease (IBD) is predictive of/strongly correlated to clinical response/outcomes observed. The key questions under investigation are: Aim 1: To assess the fluorescent signal intensity at baseline (control antibody with control biopsy and control antibody with IBD biopsy). Aim 2: To characterize the cellular landscape by surveying surface markers using bar-coded antibodies and performing gene expression profiling on every cell within inflamed tissue of patients with IBD. Aim 3: Develop algorithm using artificial intelligence to predict responders versus non-responders and to further subclassify IBD patients using phenotype data.

Key Dates

Start date
Sep 1, 2025
Status verified
Aug 2025
Primary completion
Jul 1, 2027
Completion
Jul 1, 2028

Study Design

Enrollment
40 participants (estimated)
Allocation
NON_RANDOMIZED
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC

Arms

  • Experimental: Intervention
    Pediatric patients with clinical signs and symptoms suggestive of IBD or with established diagnosis of IBD (newly diagnosed or on therapeutic management) who are scheduled to undergo Esophagogastroduodenoscopy (EGD) and/or Ileocolonoscopy (IC) with CLE as part of their clinical management

Primary Outcome Measure

Number of FITC tagged antibodies [ Time Frame: Baseline ]

Central Contacts

Locations (2)

FacilityCityStateZIPSite coordinators
University of Texas at ArlingtonArlingtonTexas76010
Jon Weidanz, PhD
[email protected]
817-272-6831
Cook Children's Health Care SystemFort WorthTexas76104
Sumith Roy, MBBS, MPH
[email protected]
682-885-1790

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By research site
University of Texas at Arlington· Arlington, TXCook Children's Health Care System· Fort Worth, TX

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