Integrates genomic, proteomic, and phenotypic data to uncover signatures conventional methods miss. Identifies biomarkers and targets grounded in translational relevance.
Maps computational insights to therapeutic strategies. Prioritizes based on druggability, patient stratification, and clinical feasibility, creating a direct route from data to patient benefit.
Combines living zebrafish models with AI-powered analysis. Captures behavioral, morphological, and physiological responses at scale, uncovering mechanisms and treatment effects that static models cannot.