bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: April 19, 2025
A bstract Predicting synergistic cancer drug combinations through computational methods offers a scalable approach to creating therapies that are more effective and less toxic. However, most algorithms focus solely on synergy without considering toxicity when selecting optimal combinations. In the absence of combinatorial assays, few models use penalties balance high with lower toxicity. these have not been explicitly validated against known drug-drug interactions. this study, we examine whether scores metrics correlate adverse While some show trends levels, our results reveal significant limitations in using them as penalties. These findings highlight challenges incorporating into prediction frameworks suggest advancing field requires comprehensive combination data.
Language: Английский