Interactive Similarity-Based Search of Clinical Trials

The rapid growth of clinical trials launched in recent years poses significant challenges for accurate and efficient trial search. Keyword-based clinical trial search engines require users to construct effective queries, which can be a difficult task given complex information needs. In this study, we present an interactive clinical trial search interface that retrieves trials similar to a target clinical trial. It enables user configuration of 13 clinical trial features and 4 metrics (Jaccard similarity, semantic-based similarity, temporal overlap and geographical distance) to measure pairwise trial similarities. Among 1,007 coronavirus disease 2019 (COVID-19) trials conducted in the United States, 91.9% were found to have similar trials with the similarity threshold being 0.85 and 43.8% were highly similar with the threshold 0.95. A simulation study using 3 groups of similar trials curated by COVID-19 clinical trial reviews demonstrates the precision and recall of the search interface.