Results of the 9th Scientific Workshop of the European Crohn’s and Colitis Organisation (ECCO): Artificial Intelligence in medical management and precision medicine

Background and Aims Artificial intelligence (AI) is increasingly being applied in various fields of medicine, including Inflammatory Bowel Diseases (IBD). This systematic review, conducted as part of the ECCO 9th Scientific Workshop on AI in IBD, explores AI applications in multiomic precision medicine, large language models (LLMs) for textual tasks and utilisation of wearable and remote care technologies. Methods A comprehensive systematic analysis of the literature was undertaken, emphasising three topics: multiomic predictive models in IBD; natural language processing (NLP) and LLMs for clinical practice, research and patient communication; and the role of remote monitoring and wearable devices. Results Key areas of promise include the implementation of NLP and LLMs for case identification and differentiation, tracking disease activity, pharmacovigilance, quality assurance and patient support. Multiomic approaches, integrating genomics, transcriptomics, proteomics, metabolomics and metagenomics, show potential for developing more accurate diagnostic and risk prediction models and improving treatment response prediction and detection of actionable drug targets for future therapeutics. Wearables and remote monitoring technologies can transform IBD management from episodic assessments to continuous less biased tracking of patient-reported outcomes and physiological biomarkers. Conclusions While AI and multiomic approaches hold substantial promise for advancing IBD management and research, further refinement is necessary to ensure content validity and address safety concerns, thereby allowing integration of AI into clinical workflows and safeguarding of data privacy. Future research should prioritise the integration of diverse omic data, conduct of longitudinal studies and validation in large and diverse cohorts.