Network medicine and artificial intelligence in cancer precision therapy: Path to prevent drug-induced toxic side effect

Abstract

The discovery of cancer-specific therapeutics and determining their sensitivity is a critical step in preventing drug-induced toxicity. Drug sensitivity varies among cancer patients due to intra-tumor heterogeneity. It demands rational drug design, target identification, and novel treatment modalities. This review discusses the use of network medicine in targeted therapy and AI-based drug response prediction for personalized cancer therapy. The network medicine is successfully implemented to integrate multiple omics data to identify the disease modules in cancer. The cancer-specific disease modules are utilized for drug screening and targeted therapy. Additionally, the model developed using AI, and genomic data shows superior performance and also reveals relationships between the genomic variability of cancer and their response to drugs. There is significant promise for network medicine and AI to handle large-scale omics data, leading to the identification of a novel cancer-specific treatment strategy and improved patient care.