Drug Synergy

Drug synergy research focuses on predicting the enhanced therapeutic effect of drug combinations compared to their individual effects, aiming to optimize treatment efficacy and reduce side effects. Current research heavily utilizes machine learning, particularly deep learning models like graph convolutional networks and transformer-based architectures, to analyze high-throughput screening data and predict synergistic interactions, often incorporating drug chemical structures and cell line gene expression profiles. These advancements hold significant promise for accelerating drug discovery and development, enabling more personalized and effective therapies, especially in cancer treatment, by identifying optimal drug combinations and reducing the need for extensive and costly clinical trials.