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Multimodal profiling of inflammatory bowel disease (IBD) patient tissue and blood samples has revealed the disease spectrum in unprecedented detail, and cellular and molecular correlates of disease severity and outcome in IBD have been elaborated. Incorporating these in the clinical setting would offer a unique opportunity to increase the granularity of current clinical measures and to better assess treatment response. Remission and healing at a cellular/molecular level are also likely to have predictive value for long-term outcomes. Here, we outline a path forward to implementing the most promising molecular disease descriptors as future clinical treatment targets in IBD. We focus on the concept of cellular/molecular measures of inflammation, remission, healing, response to therapy, and target pathway engagement. Monitoring mode-of-action-specific pharmacodynamic modules in the context of disease-related resolution pathways will guide assessment of novel and existing therapies. Artificial intelligence-assisted tools will be key to enabling this development, improving reproducibility, limiting costs, and delivering fast detection.

More information Original publication

DOI

10.1053/j.gastro.2025.12.002

Type

Journal article

Publication Date

2026-02-10T00:00:00+00:00

Keywords

AI, Artificial, Biomarker, Bowel, Diverse/Diversity, End Point, Endoscopy, Histology, IBD, Inflammatory, Machine, Molecular, Outcome, Predictor, Trial