Written by : Jayati Dubey
November 24, 2023
Genentech and NVIDIA collaborate to optimise Genentech's ML algorithms on the NVIDIA DGX Cloud, a dedicated AI supercomputing platform with BioNemo for generative AI applications in drug discovery.
Genentech, a member of the Roche Group, has entered a multi-year strategic research collaboration with NVIDIA, a global leader in accelerated computing and artificial intelligence (AI) towards accelerated drug discovery and development.
This collaboration aims to leverage Genentech's extensive biological and molecular datasets, AI capabilities, and research expertise alongside NVIDIA's cutting-edge accelerated computing capabilities to expedite the discovery and development of novel therapies.
The collaboration is structured to enhance Genentech's advanced AI research programs by transforming its generative AI models and algorithms into a next-generation AI platform. The goal is to significantly speed up the delivery of innovative therapies and medicines to address unmet medical needs.
Genentech and NVIDIA will work in tandem to accelerate and optimise Genentech's proprietary machine learning (ML) algorithms and models on the NVIDIA DGX Cloud. This platform provides a training-as-a-service solution built on dedicated NVIDIA AI supercomputing and software, including NVIDIA BioNemo, for generative AI applications in drug discovery.
NVIDIA's expertise in computing will be shared with Genentech's computational scientists to optimise and scale Genentech's models. The collaboration also allows for potential improvements or enhancements to NVIDIA's platforms during this joint optimisation process.
Aviv Regev, EVP and head of Genentech Research and Early Development, said, "By harnessing the power of AI models and algorithms, with our unique data and experiments, we're unlocking scientific discoveries with incredible speed and generating insights at an unprecedented scale."
Genentech's AI/ML teams are already developing and leveraging foundational models across various research areas, including diverse therapeutic modalities. The collaboration with NVIDIA aims to complement these efforts and further enhance Genentech's capabilities in AI-driven drug discovery.
Jensen Huang, founder and CEO of NVIDIA, said, "Our collaboration to create Genentech's next-generation AI platform will dramatically accelerate the pace of drug discovery and development."
The collaboration will be crucial in accelerating Genentech's "lab in a loop" concept, where experimental data feeds computational models to uncover patterns and make new predictions.
These predictions are rapidly tested in the lab, and the results are fed back into the models for continuous improvement, enabling the iterative development of better therapies.
Activities within the collaboration will utilise publicly available and Genentech-proprietary data. Genentech will maintain control over sharing its proprietary data, and NVIDIA will not have direct access to such data unless Genentech grants it for specific projects during the project's term.
Drug discovery and development are complex and time-consuming processes. Genentech believes that AI, in combination with scientific expertise and technology, plays a pivotal role in making these processes more predictable and cost-effective.
The collaboration with NVIDIA aligns with Genentech's vision of utilising AI to boost the success rate of research and development, ultimately leading to the discovery and design of therapeutics that can enhance people's lives.
Roche, founded in 1896 in Basel, Switzerland, is one of the world's largest biotechnology companies and a global leader in in-vitro diagnostics. Genentech, based in the United States, is a wholly-owned member of the Roche Group. Roche is also the majority shareholder in Chugai Pharmaceutical, Japan.
In another development, NVIDIA, just days back, collaborated with L&T Technology Services Limited (LTTS) to pioneer software-defined architectures for medical devices, specifically focusing on endoscopy applications. This partnership aims to elevate image quality and scalability in medical products, promising significant advancements in the field.