AI-Enabled Clinical Trials in IBD: Automating and Enhancing Disease Assessment and Study Management

Abstract

Artificial intelligence (AI) will fundamentally improve how we perform clinical trials by addressing issues of standardizing disease scoring, improving the sensitivity and precision of activity and phenotype assessments, and automating laborious and time-consuming study functions. Progress in AI image analysis is quickly proving to replicate expert judgement in endoscopy, histology, and cross-sectional imaging with speed, reproducibility, and reduced bias. However, AI analytics offer the ability to quantify disease characteristics with more detail and precision than human experts. Large language models and generative AI are automating the collection of high-quality data from electronic records and improving our ability to predict patient outcomes. This narrative review will focus on AI tools available today, their expected implementation, and future-facing opportunities for AI to reimagine IBD clinical trials.