AI-driven simulations typically utilize machine learning algorithms that are trained on extensive datasets, including genomic, proteomic, and clinical data. These algorithms can identify patterns and correlations that may not be evident through conventional analysis. By simulating different scenarios, AI can predict the outcomes of various treatment strategies, helping researchers to optimize therapy plans.
