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Drug safety. Engineered. 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.

13 people are employed at Cytocast.

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