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Updated: Jul 13, 2026

Non-invasive Assessment of the Efficacy of New Therapeutics for Intestinal Pathologies Using Serial Endoscopic Imaging of Live Mice
Published on: March 10, 2015
A Longitudinal Disease Progression Model Characterizing Endoscopic Response and Remission in Crohn's Disease
Anita Moein1, Jurgen Langenhorst2, Nastya Kassir3
1Genentech, Inc, South San Francisco, CA, USA. moein.anita@gene.com.
Abstract:
Crohn's disease (CD) is a heterogeneous, progressive inflammatory bowel disease in which substantial placebo effects often confound assessment of therapeutic efficacy. A placebo-based disease model was developed using Simple Endoscopic Score for Crohn's Disease (SES-CD) within an item-level response theory-bounded integer (IRT-BI) and full random effects models (FREM) framework. Longitudinal SES-CD data from 155 placebo-treated patients in the Phase 3 BERGAMOT-trial were analyzed. Each SES-CD subscore, across five intestinal segments, was described by a bounded-integer model and linked through a latent disease variable capturing a mono-exponential placebo trajectory. Endoscopic response (≥50% reduction from baseline SES-CD) and remission (SES-CD 0-2) were defined according to the FDA guidance. IRT-BI model adequately characterized longitudinal trajectories of all SES-CD subscores and accurately predicted individual patient endoscopic response and remission, with predictive accuracy exceeding 89% for responders and 85% for non-responders. Visual predictive checks showed that observed mean trajectories for all 20 SES-CD subscores were within the 90% confidence intervals across the 66-week trial. Population maximum placebo response (RMaxPL) was estimated at -0.220 with a time to half-maximal effect of 13.8 weeks. Covariate analysis identified elevated baseline C-reactive protein and fecal calprotectin correlated to reduced RMaxPL, whereas TNF-naïve status was associated with increased RMaxPL. This is first application of an integrated item-level IRT-BI-FREM approach in CD, enabling robust characterization of placebo response and identification of clinically relevant covariates. By providing quantitative framework for isolating drug-effects from placebo-response, this model aligns with FDA model-informed drug development priorities and supports efficient, targeted, and informative clinical trials.Clinical Trial RegistrationNCT02394028 Registered March 20, 2015.
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