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Leonardo Bernal

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Open access Aug 2026

A Combined Chemoinformatics- and Machine Learning-Based Approach Identifies Chlormidazole as a Drug Repurposing Candidate against Aggressive Prostate Cancer

An integrated chemoinformatics and machine learning workflow with ligand-based similarity filtering is developed and prospectively validated, identifying chlormidazole as a promising repurposing candidate for PCa and demonstrating the value of integrating chemoinformatics with ML for drug repurposing and virtual screening.

Leonardo Bernal, Luca Pinzi, T. Martinelli et al. · 0 citations

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