How to apply artificial intelligence (AI) to facilitate and enhance MASH trials

Introduction Metabolic dysfunction-associated steatohepatitis (MASH) is one of the most common liver diseases, but thus far only two drugs (resmetirom and semaglutide) have received conditional approval for use. Successful MASH trials are thus highly desired to fill the therapeutic and evidence gap. Concurrently, AI has powered advances in multiple areas of medicine. We consider in this review the potential applications of AI to enhance MASH trials. Methods We conduct a narrative review of AI uses in MASH, with a focus on current and potential applications in MASH trials. Results We describe current digital pathology and AI technologies for MASH grading, a mature application where specific models have been qualified by the FDA and EMA for endpoint determination in MASH trials. We also cover the use of contemporary AI risk models to facilitate patient enrollment, and large language models to facilitate patient interactions including recruitment and retention. Finally, we consider lessons from innovative uses of AI in other medical domains, and how current guidelines shape our thinking about the use of AI in MASH trials. Conclusion AI has made inroads into the world of MASH trials and shows high potential to further enhance their safety, efficacy, and scientific validity.