Cognizant to apply generative AI to enhance drug discovery for pharmaceutical clients with NVIDIA BioNeMo

Cognizant’s AI and industry expertise, combined with the NVIDIA BioNeMo generative AI platform, create a strong foundation to improve outcomes in the healthcare and life sciences sectors.

Cognizant (NASDAQ: CTSH) is advancing the application of generative AI (gen AI) technology with the NVIDIA BioNeMo platform to solve complex challenges of drug discovery in the life sciences industry, such as improving productivity in the development process and increasing the speed at which new, life-saving treatments can be brought to market.

Traditional drug discovery methodologies are process intensive and require the analysis of vast repositories of scientific literature and clinical data in order to reveal relevant insights. Moreover, traditional methods are burdened with high costs and long development lifecycles with a high rate of failure. By leveraging gen AI technologies, clinical researchers can rapidly sift through extensive datasets, more accurately predict interactions between drug compounds and create new, viable drug development pathways.

“More than any other technological breakthrough in recent decades, generative AI has the potential to revolutionize the way new drugs are researched, developed and brought to market, making the creation of lifesaving discoveries faster, smarter and more accessible to all,” said Anna Elango, EVP, Cognizant’s Core Technologies & Insights. “By collaborating with NVIDIA, Cognizant can open the path to realizing this vision safely, responsibly and cost-effectively for our life sciences clients.”

By leveraging its deep life sciences and AI domain expertise and NVIDIA’s pretrained, industry-specific generative AI models offered as part of BioNeMo, Cognizant aims to give clients access to a suite of model-making services, including pretrained models, cutting-edge frameworks, and APIs, that offers clients the quickest path to train and customize enterprise models using their proprietary data. The offering is intended to enable this with reduced manual intervention for data analysis, and without the need to write elaborate code and build or maintain infrastructure.

“Generative AI will drive the next wave of enterprise productivity gains across industries, enabled by the NVIDIA AI Enterprise software platform,” said Alvin DaCosta, VP, Global Consulting Partner Organization, NVIDIA. “Using NVIDIA BioNeMo, Cognizant will help provide its life sciences clients with advanced, secure and reliable AI services to drive improved outcomes with custom drug discovery applications.”

Cognizant collaborates with leading global firms in pharmaceuticals, biotech and medical devices, covering the entire life sciences value chain from R&D to digital health. This work contributes to the industry’s ability to enhance science, improve patient outcomes, and increase business value, by enabling a patient-centric approach and better interactions with healthcare professionals. Cognizant’s life sciences offerings support more than 120 global manufacturing lines and more than 18 million patients with medical device company products.

Cognizant intends to pursue additional applications by collaborating with NVIDIA in areas such as manufacturing and automotive engineering, where gen AI has the potential to enhance productivity, optimize costs and bring innovation to market more quickly. Cognizant intends to establish an NVIDIA AI Center of Excellence this year to further innovate with NVIDIA technologies, including the NVIDIA MetropolisNVIDIA Omniverse and NVIDIA AI Enterprise platforms, for the benefit of clients across industries around the world.

About Cognizant
Cognizant (Nasdaq: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world. Together, we’re improving everyday life. See how at or @cognizant.

Disclaimer: The Press Release has been provided by Cognizant. CXO Digital Pulse holds no responsibility of its content.

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