Published in GEN (Genetic Engineering & Biotechnology News)
Published in LAist/AirTalk by NPR
Published in Technology Networks
Published in American Journal of Managed Care
Published in The Medicine Maker
Published in Pharmaphorum
Published in Drug Discovery News
Published in Marksmen Daily
Published in BioTuesdays
Published in Marksmen Daily
Published in Informa TechTarget
Published in Newsweek
Published in BioXConomy
Published in Pharmaceutical Manufacturing
Published in Pharma's Almanac
AtlasGEN Novel Drug Designer efficiently identifies new molecules based on favorable chemical properties and simultaneously evaluates them for clinical safety and effectiveness based on biology using VeriSIM Life’s groundbreaking Translational Index™ technology.
Iterative ranking of target engaging hits by their Translational Index values reduces the time and cost associated with other computational hit discovery approaches, while compressing the hit-to-lead refinement and optimization process by pre-validating hits for translatability. This unique integration dramatically reduces the number of compounds to evaluate in subsequent experimental research.
The ability to generate target engaging compound hits depends largely on the size of the molecular search library. The AtlasGEN search space is supported by more than 1 trillion compounds. Generative AI and deep learning techniques deliver unprecedented discovery capability.
AtlasGEN accurately predicts protein-lygand binding affinity by combining geometric conformer analysis with machine learning based on experimental data 72% more efficiently than molecular docking-based approaches.
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