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

NCT07121920 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 40

Last updated 2025-08-14

No results posted yet for this study

Summary

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.

Conditions

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

Interventions

DEVICE

Confocal Laser Endomicroscopy

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.

Sponsors & Collaborators

  • Cook Children's Health Care System

    lead OTHER

Principal Investigators

  • Clifton Huang, MD · Cook Children's Health Care System

Study Design

Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
2 Years
Max Age
21 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-01
Primary Completion
2027-07-01
Completion
2028-07-01
FDA Device
Yes

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07121920 on ClinicalTrials.gov