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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Pharmacol Ther. Jun 5, 2026; 17(2): 116608
Published online Jun 5, 2026. doi: 10.4292/wjgpt.v17.i2.116608
Current approaches to disease severity and therapy effectiveness assessment in patients with inflammatory bowel disease
Alexandre Loktionov
Alexandre Loktionov, DiagNodus Ltd, Cambridge CB4 0WS, United Kingdom
Author contributions: Loktionov A is responsible for all work related to the preparation of this review paper; Loktionov A has designed paper structure, performed literature search, contributed figures and tables, analysed literature data and wrote the paper.
Conflict-of-interest statement: Loktionov A reports personal fees from DiagNodus Ltd, outside the submitted work.
Corresponding author: Alexandre Loktionov, MD, PhD, Director, DiagNodus Ltd, St John’s Innovation Centre, Cowley Road, Cambridge CB4 0WS, United Kingdom. alex.loktionov@diagnodus.com
Received: November 17, 2025
Revised: December 4, 2025
Accepted: February 9, 2026
Published online: June 5, 2026
Processing time: 193 Days and 8.3 Hours
Core Tip

Core Tip: Inflammatory bowel disease patients need continuous lifetime monitoring of disease activity and effects of therapeutic interventions. This review considers a wide range of approaches currently applied for this purpose. The reviewed modalities comprise clinical criteria, endoscopy, cross-sectional imaging, detection of biomarkers in body fluids and feces, gut microbiome analysis, and application of modern technologies, such as multi-omics and artificial intelligence. Artificial intelligence-driven integration of abundant information provided by a range of diagnostic and analytical approaches outlined in this review may help in transforming the current ‘one-size-fits-all’ inflammatory bowel disease treatment concept into a truly personalized model of disease care.

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