Mapping the intellectual landscape of malaria drug repurposing: a systematic analysis of the 51 most cited studies

BACKGROUND: The escalating threat of Plasmodium falciparum resistance to artemisinin-based therapies necessitates accelerated drug development. Drug repurposing offers a promising pathway to bypass the extensive time and cost of de novo discovery. METHODS: This study conducted a systematic analysis of the top 51 most cited original research articles in malaria drug repurposing identified from the Scopus database. Data on methodologies, drug candidates, targets, and outcomes were extracted and synthesized. RESULTS: The analysis reveals a field dominated by computational approaches, with molecular docking (AutoDock Vina) and virtual screening serving as primary filters for identifying candidates from FDA-approved libraries. These methods are increasingly integrated with advanced techniques like machine learning for synergy prediction and transcriptomics-guided discovery. The repurposing landscape has identified promising antimalarial activity in diverse drug classes, including anticancer agents (methotrexate, lapatinib), antivirals (lopinavir, ritonavir), and immunosuppressants (everolimus). Key validated targets include the proteasome, PfHT1 glucose transporter, and various parasite enzymes. Candidates such as alisporivir, bazedoxifene, and nitrofurantoin have demonstrated efficacy in in vitro and in vivo models, often showing synergistic potential when combined with standard antimalarials. CONCLUSION: The convergence of computational power and biological insight has generated a rich pipeline of repurposable candidates. A quantitative analysis revealed molecular docking as the most frequent (31.4% of studies) and successful strategy, though in vivo preclinical evaluation yielded the highest validation score. Future success hinges on rigorous experimental validation, lead optimization, and advancing the most promising agents into clinical trials to address the urgent need for novel antimalarial therapies.