Automated Processes and Artificial Intelligence in Generating Candidates for Oncology Drug Repurposing: Three-Year Scoping Review of Data

Oncology conditions are increasingly defined by their molecular profiles, and drug repurposing exploits this new evidence to identify new therapeutic uses of authorized/investigational medicinal products outside their original indication(s). This scoping review mapped original research published between January 2022 and December 2024 to determine the impact of automated processes and artificial intelligence in generating oncology candidates for drug repositioning, and 42 individual projects met the eligibility criteria and were analyzed. The included studies demonstrate extensive use of computational approaches for candidate prioritization, large-scale data integration, and hypothesis generation in oncology drug repurposing, creating opportunities for positive impact on efficiency. The included projects most commonly were target-oriented and disease-oriented and used multiple databases and computational validation procedures, while experimental and clinical validation were less frequently reported. The available open-access literature suggests substantial activity in China and India, which can support the notion that digitalization represents an important instrument in healthcare systems of low- and middle-income countries but should be interpreted cautiously. While the search was limited to PubMed and open-access English-language publications, we identified a relatively small number of drug-oriented projects, the importance of providing publicly accessible source code to reduce development costs, and the predominant role of academic institutions.