The Atomwise approach to drug discovery is based on the strong belief that virtual screening enabled by sophisticated AI-based computational models will accelerate the development of new drug candidates, and eventually achieve our mission of […]
Here at Atomwise, we are really proud of the AtomNet® tool we’ve built to perform virtual screening of targets against billions of compounds to find promising candidates. This approach has already provided new leads for academic labs and drug […]
You probably hear about AI on a regular basis, but if you’re not a programmer steeped in machine learning algorithms, AI can seem like a mysterious black box.
Drug discovery startup Atomwise, which joined the NVIDIA Inception virtual accelerator program in 2018, developed AtomNet, a convolutional neural network for small molecule drug discovery. The AtomNet AI technology can screen more than 16 billion […]
At the American Chemical Society Fall 2020 Virtual Meeting & Expo, several Atomwise members and partners were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Fall 2020 Virtual […]
- by Stefan Schroedl, Head of Machine Learning at Atomwise Originally posted on Medium This post is intended for my fellow machine learning engineers who are curious about applications in medicine, biology, or chemistry, but without a prior formal […]
What is AtomNet® technology? AtomNet® technology is the first drug discovery algorithm to use a deep convolutional neural network – the same AI technology that recognizes faces in a crowd enables self-driving cars, and allows you to talk to your […]
In November, Atomwise published the first scientific paper about our technologies – AtomNet® platform: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery. This blog post is an introduction to that work […]
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