Nvidia, Schrödinger Team Up To Advance Drug Discovery

April 21, 2021
The collaboration enables pharmaceutical industry giants and biotech startups to use Schrödinger’s computation drug discovery platform boosted by Nvidia DGX SuperPOD and Nvidia Clara Discovery Libraries.

Nvidia announces a strategic partnership with Schrödinger that harnesses Nvidia DGX A100 systems to further expand the speed and accuracy of Schrödinger’s computational drug discovery platform and enable rapid, accurate evaluation of billions of molecules for potential development of therapeutics. The companies will optimize Schrödinger’s software platform — designed to model and predict the properties of novel molecules — for the Nvidia DGX SuperPOD, which is built with Nvidia DGX A100 systems and Nvidia InfiniBand HDR networking.

The work includes the physics-based modeling in Schrödinger’s product suite, as well as support for Nvidia Clara Discovery, a collection of state-of-the-art A.I. frameworks, applications and pre-trained models for the most advanced computational drug discovery, according to the company. Additionally, the companies will partner on scientific and research breakthroughs to further advance physics-based computing and machine learning for drug discovery.

For each potential drug candidate, Schrödinger routinely evaluates tens of thousands of molecules with its most computationally intensive physics-based approaches. This requires hundreds of thousands of hours of GPU time on high-performance computers.

Through the collaboration, the entire pharmaceutical industry comprising over 3,000 companies — from startups to multinationals — reportedly will be able to further accelerate drug discovery at supercomputing scale. The joint offering will enable companies of all sizes to simulate molecular combinations with physics and A.I. to identify and optimize the most promising compounds for potential therapeutic use. Pharmaceutical companies can run this research on their own easy-to-deploy private clouds featuring the Schrödinger platform running on Nvidia DGX SuperPOD, which is available to install on premises or in a colocation facility.

For more information, visit: www.nvidia.com

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