Duminda S. Ranasinghe

Jan 20, 2024 | biorxiv.org | Duminda S. Ranasinghe |Nathan Sanders |Changchang Liu |Daniel Spitz

AbstractDrug combinations have been shown to be an effective strategy for cancer therapy, but identifying beneficial combinations through experiments is labor-intensive and expensive. Machine learning (ML) systems that can propose novel and effective drug combinations have the potential to dramatically improve the efficiency of combinatoric drug design.