AI-Enabled Clinical Trials

This chapter discusses various inroads artificial intelligence (AI) and machine learning have made in clinical development ranging from target product profiles, through clinical trial design, patient enrichment and enrollment, site selection, patient monitoring, medication adherence and retention, comparative effectiveness assessments, drug supply, regulatory approval, and product launch to lifecycle management. It also discusses how AI-enabled applications can be used in advancing clinical development. Pharmaceutical companies have begun leveraging patient data from electronic health records to inform selection of high-enrolling sites, identify patients that meet the inclusion/exclusion criteria, and assess the impact of inclusion and exclusion criteria on trial feasibility. Enrichment design relies on the use of markers indicative of either the patient’s prognosis of disease and/or response to therapeutic intervention. Applications of reinforcement learning have the potential to lead to individualized treatment regimens and selection of individualized optimal combination therapy.