Protocol for the Therapy Personalisation Using Multiomic Analyses in Inflammatory Bowel Disease (THAMES‐IBD) Study

ABSTRACT Background Despite an expanding repertoire of advanced therapies for inflammatory bowel disease (IBD), treatment outcomes remain suboptimal, with only 30%–40% of patients achieving sustained remission. Emerging evidence indicates that therapeutic outcomes are shaped by complex interactions between host immune pathways, the gut microbiome and psychosocial factors. However, robust biomarkers to predict individual treatment response are currently lacking. Aims The Therapy Personalisation using Multiomic Analyses in Inflammatory Bowel Disease (THAMES‐IBD) study aims to address this critical unmet need by identifying predictors that differentiate responders from non‐responders to advanced therapies in ulcerative colitis (UC) using an integrated multiomics approach. Methods The THAMES‐IBD study is a multicentre, prospective observational cohort study recruiting adults with active UC initiating or switching advanced therapies, alongside patients with inactive UC and non‐IBD controls. Multimodal samples will be collected from recruited participants prior to treatment initiation, including stool (metagenomics and metabolomics), blood (transcriptomics, proteomics and metabolomics) and mucosal biopsies (transcriptomics). Longitudinal blood and stool samples, as well as clinical, demographic, dietary and comprehensive psychosocial data, will be collected at baseline and at 8–14 weeks and 28–32 weeks after commencing a new advanced therapy. Treatment outcomes will be pragmatically defined based on validated patient‐reported outcome (PRO‐2) scores and biochemical measures. Multiomics integration will be performed using complementary unsupervised and supervised approaches. Predictive models will undergo internal cross‐validation and, where feasible, external validation in independent cohorts. Conclusion Through deep multimodal phenotyping of patients with UC, the THAMES‐IBD study seeks to identify biological mechanisms associated with therapeutic response and resistance. These insights have the potential to inform the development of novel predictive biomarkers to guide precision medicine strategies, minimise ineffective treatment cycling and ultimately improve outcomes for patients with IBD.