How can quantum computing be applied in clinical trial design and optimization?

Abstract

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challenges, lack of efficacy, absence of reliable biomarkers, etc. Each of these factors possesses a unique computational challenge, such as data management, trial simulations, statistical analyses, and trial optimization. Recent advancements in quantum computing offer a promising opportunity to overcome these hurdles. In this opinion we uniquely explore the application of quantum optimization and quantum machine learning (QML) to the design and execution of clinical trials. We examine the current capabilities and limitations of quantum computing and outline its potential to streamline clinical trials.