  Clinical trials are pivotal in the drug discovery process to determine the
safety and efficacy of a drug candidate. The high failure rates of these trials
are attributed to deficiencies in clinical model development and protocol
design. Improvements in the clinical drug design process could therefore yield
significant benefits for all stakeholders involved. This paper examines the
current challenges faced in clinical trial design and optimization, reviews
established classical computational approaches, and introduces quantum
algorithms aimed at enhancing these processes. Specifically, the focus is on
three critical aspects: clinical trial simulations, site selection, and cohort
identification. This study aims to provide a comprehensive framework that
leverages quantum computing to innovate and refine the efficiency and
effectiveness of clinical trials.
