Atomwise
AI-powered virtual screening for small molecule drug discovery
Atomwise is a pioneer in applying deep learning to structure-based drug design. Its AtomNet platform uses convolutional neural networks trained on millions of experimental affinity measurements to predict the binding of small molecules to protein targets, enabling rapid virtual screening of billions of compounds. The company has established a broad network of academic and pharmaceutical collaborations.
Virtual Screening, Generative Chemistry
AtomNet
Funding
$123M
Total raised
Technology
AtomNet is a deep learning neural network for structure-based drug design that predicts binding affinity of small molecules to protein targets. It uses 3D convolutional neural networks to evaluate molecular interactions, enabling virtual screening of ultra-large compound libraries.
Leadership
Abraham Heifets
CEO & Co-Founder
PhD in Computer Science from University of Toronto
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