Marc Drudis, Christa Zoufal, et al.
QSim 2026
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.
Marc Drudis, Christa Zoufal, et al.
QSim 2026
Mathias Steiner, Marco Antonio Guimaraes Auad Barroca, et al.
APS Global Physics Summit 2025
Theodore Yoder, Eddie Schoute, et al.
Quantum Summer Cluster Workshop 2025
Luke Govia, David McKay, et al.
APS March Meeting 2024