Clinical site selection problems with probabilistic constraints

Anh Ninh, Yunhong Bao, Daniel McGibney and Tuan Nguyen

European Journal of Operational Research, 2024, vol. 316, issue 2, 779-791

Abstract: Recruiting candidates globally and across multiple sites in different geographic regions is necessary to speed up the enrollment of clinical trials. While patient enrollment can benefit from this globalization, initiating clinical trials has become much more complicated. In the start-up stage, the sites must be selected out of a set of potential candidates around the globe based on the specifics of those clinical trials, such as protocols, operational costs, and recruitment deadlines. Sites in one region can be very distinct from sites in another area. Yet, a common mistake in selecting sites is to rely on too little knowledge or subjective data. Poor selection decisions can lead to study delays and prolong the time to market for life-saving treatments. Thus, this paper proposes a novel framework to aid the decision-making in the global site selection problem (GSSP). To ensure that our framework accurately captures the uncertainty in recruitment time, we adopt a risk-based constraint that accounts for random patient enrollment. The extensive computational studies help quantify significant time-cost trade-offs as a potential solution to control the costs of conducting a trial.

Keywords: OR in medicine; Clinical trial; Optimization; Geography; Log-concavity (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:316:y:2024:i:2:p:779-791

DOI: 10.1016/j.ejor.2024.03.013

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