(127) Drug Repurposing Using Real-World Data; A Scoping Review

Publication Number: 1172

Background: Drug repurposing, or using an existing approved drug for a novel indication, supplements de novo drug discovery with lower attrition rates, and financial and time savings. Pharmacoepidemiologic analyses of real-world data (RWD) is a growing computational approach to generate evidence for drug repurposing.

Objectives: This scoping review aims to 1) characterize how RWD is being used for hypotheses generation, validation or safety assessment in drug repurposing, and 2) discuss challenges and potential solutions from operational, technological and methodological aspects.

Methods: A systematic search of key databases (MEDLINE, Embase, Scopus, Web of Science) and grey literature from inception until 6 August 2021 was conducted. We included all records that described drug repurposing or synonyms using drugs approved for use by local regulators and RWD gathered in real-life clinical settings. Quantitative analysis was conducted using data extracted from original studies: RWD sources, target repurposing area, study objective and methodology.

Results: In total, we identified 250 relevant records, including 144 original studies from 2009 to 2021. Hypothesis validation (n=101, 70%) and hypothesis generation (n=36, 25%) studies were most common; 7 studies (4%) were safety assessments of potential COVID-19 therapies, published since 2020. Almost all hypothesis-validation studies used observational study designs such as cohort (86%) or case-control studies (13%). Diverse methodologies were explored in hypothesis-generation studies, including cohort studies (32%), pharmacovigilance signal detection (disproportionality or sequence symmetry analysis) (24%), machine learning (24%) and sematic analysis (14%). Key challenges identified were isolated RWD sources with poor clinical granularity, false-positive signals from data mining, and potential biases and confounding in observational studies.

Conclusions: Most drug repurposing studies using RWD over the past decade were to validate existing repurposing hypotheses. Analyses of RWD could also generate new hypothesis with the use of new data mining techniques or assess real-world safety of repurposed drugs. Key challenges such as isolated RWD sources and methodological pitfalls in data mining and observational study designs can be addressed with increasing record linkage, integration of preclinical knowledge into data mining and implementation of “target trial” framework.