We have entered into a collaboration with leading tech innovators to develop cutting-edge solutions that will transform our service offerings. This partnership is a step towards embracing the future of technology.
We have entered into a collaboration with leading tech innovators to develop cutting-edge solutions that will transform our service offerings. This partnership is a step towards embracing the future of technology.
Our company has launched several community engagement initiatives aimed at fostering relationships and supporting local development. These programs are designed to empower residents and promote sustainable growth.
Our company has launched several community engagement initiatives aimed at fostering relationships and supporting local development. These programs are designed to empower residents and promote sustainable growth.
We are thrilled to announce a breakthrough in our research and development efforts, leading to innovative solutions that enhance product efficiency and sustainability. This achievement underscores our commitment to innovation.
We are thrilled to announce a breakthrough in our research and development efforts, leading to innovative solutions that enhance product efficiency and sustainability. This achievement underscores our commitment to innovation.
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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