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Drug safety. Engineered, not discovered. Cytocast is mapping the mechanistic chain from compound to clinical side effect, pathway by pathway, so drug teams see not just what will fail, but which off-target causes it. Every drug discovery team currently selects compounds to advance based on incomplete information. We add the missing piece: predicted clinical side effects to reduce cost, time, unnecessary animal studies, and patient harm. Our platform checks candidate compounds for potential (off-)targets using deep learning, simulates their effects on protein complexes and pathways across 15 tissue types, and connects these results to 1,200+ clinical side effects through machine learning trained on 1,000+ drugs. Every prediction is mechanistic and explainable, showing which (off-)targets are connected to a given adverse event. Unlike AI tools focused on a handful of toxicity endpoints, Cytocast predicts 1,200+ clinically relevant side effects across the body. Built by professors in systems biology and computational biology, Cytocast is grounded in world-class science and driven by a research-first team. Our vision is a world where no drug candidate advances without its full safety profile mechanistically mapped.

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Attila Csikasz-Nagy is the CEO of Cytocast.

12 people are employed at Cytocast.

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