Artificial Intelligence (AI) and machine learning are transforming the field of drug response prediction. These technologies can analyze vast amounts of data, identify patterns, and make predictions with high accuracy. AI models can integrate diverse data types, including genomic, proteomic, and clinical data, to provide a comprehensive prediction. This approach not only speeds up the prediction process but also enhances its precision.
