{"id":60327,"date":"2024-11-13T04:06:13","date_gmt":"2024-11-13T03:06:13","guid":{"rendered":"https:\/\/pharma-trend.com\/en\/tetrascience-collaborates-with-nvidia-to-industrialize-the-production-of-scientific-ai-use-cases\/"},"modified":"2024-11-13T04:06:13","modified_gmt":"2024-11-13T03:06:13","slug":"tetrascience-collaborates-with-nvidia-to-industrialize-the-production-of-scientific-ai-use-cases","status":"publish","type":"post","link":"https:\/\/pharma-trend.com\/en\/tetrascience-collaborates-with-nvidia-to-industrialize-the-production-of-scientific-ai-use-cases\/","title":{"rendered":"TetraScience Collaborates With NVIDIA to Industrialize the Production of Scientific AI Use Cases"},"content":{"rendered":"<div>\n<ul class=\"bwlistdisc\">\n<li>\nThe collaboration aims to accelerate the adoption of scientific AI in the life sciences by producing AI-enabled use cases at an industrial scale.<\/li>\n<li>\nThe work combines the foundational elements of scientific AI: compute, AI-native scientific data, domain-specific models, and scientific use case expertise.<\/li>\n<li>\nTetraScience aims to deliver scientific and economic impact across the life sciences value chain powered by the Tetra Scientific Data and AI Cloud and NVIDIA BioNeMo platform.<\/li>\n<\/ul>\n<p>BOSTON&#8211;(BUSINESS WIRE)&#8211;<a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Fwww.tetrascience.com%2F%3Futm_source%3Dprnewswire%26utm_medium%3Dpr%26utm_campaign%3D24-q4-nvidia&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=TetraScience&amp;index=1&amp;md5=f488d1d826409723b01b70412a8b0e99\" rel=\"nofollow\" shape=\"rect\">TetraScience<\/a> today announced it is collaborating with NVIDIA to accelerate innovation in the $1.5 trillion life sciences industry by bringing standardization and scalability to the development and implementation of scientific AI.<\/p>\n<p><a href=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302303\/5\/Press_releases_1.jpg\"><img decoding=\"async\" src=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302303\/22\/Press_releases_1.jpg\"><\/a><br \/><a href=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302303\/5\/Press_releases_1.jpg\"><img decoding=\"async\" src=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302303\/21\/Press_releases_1.jpg\"><\/a><br \/><a href=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302296\/5\/tetrascience_logo_logo_color.jpg\"><img decoding=\"async\" src=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302296\/22\/tetrascience_logo_logo_color.jpg\"><\/a><br \/><a href=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302296\/5\/tetrascience_logo_logo_color.jpg\"><img decoding=\"async\" src=\"https:\/\/mms.businesswire.com\/media\/20241112651874\/en\/2302296\/21\/tetrascience_logo_logo_color.jpg\"><\/a><\/p>\n<p>\nThe biopharma industry is racing to unlock AI\u2019s potential across thousands of scientific use cases. However, millions of silos of proprietary and unstructured data and a project-based DIY approach block any ability to produce AI-ready datasets. Achieving success in scientific AI depends on eliminating silos and assembling the four essential components of a scientific AI stack: massive computational power, advanced models, sophisticated scientific ontologies, and deep scientific use case expertise.<\/p>\n<p>\nTetraScience\u2019s collaboration with NVIDIA makes such a reference scientific AI stack tangible for global drug companies looking to accelerate and optimize scientific workflows across the pharmaceutical value chain. The <a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Fwww.tetrascience.com%2F%3Futm_source%3Dprnewswire%26utm_medium%3Dpr%26utm_campaign%3D24-q4-nvidia&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=Tetra+Scientific+Data+and+AI+Cloud&amp;index=2&amp;md5=025cb8f7b3c0df34c71d9f23f9715a29\" rel=\"nofollow\" shape=\"rect\">Tetra Scientific Data and AI Cloud<\/a> provides a robust pathway to industrial-strength scientific AI through collaboratively optimized solutions with NVIDIA CUDA-X libraries, AI frameworks, and AI models. The Tetra Cloud is purpose-built to transform proprietary and unstructured scientific data into AI-native data and AI-enabled use cases. This solid and open data foundation will now tap into the value of NVIDIA&#8217;s accelerated computing infrastructure, domain-specific large language models, and deep learning capabilities.<\/p>\n<p>\n\u201cScientific AI is the key to unlocking safer and more effective therapeutics as well as improving the economics of the life sciences industry,\u201d said Patrick Grady, CEO of TetraScience. \u201cBy integrating TetraScience\u2019s full-stack data, use case, and AI capabilities with the NVIDIA CUDA accelerated compute platform and domain-specific models, we intend to industrialize the production of AI-enabled use cases to help these vital organizations derive immediate scientific and business value.\u201d<\/p>\n<p>\n\u201cOne of the most significant ways AI can benefit the pharma and life sciences industry is by enhancing complex scientific experiments and lab data, reducing time and costs for managing them,\u201d said Kimberly Powell, vice president of healthcare at NVIDIA. \u201cWe\u2019re working with TetraScience to innovate and integrate generative AI and agentic workflows for knowledge extraction, relationship discovery, and reasoning, helping the industry get the most out of its data.\u201d<\/p>\n<p>\nTetraScience will work together with NVIDIA to engage with leading biopharmaceutical companies to establish a scientific AI use-case roadmap across drug discovery, development, manufacturing, and QC, prioritizing those with the highest impact. Lead clone selection, for example, is a critical but complex and time-consuming step in developing the cell lines that produce biologic drugs such as vaccines and monoclonal antibodies. Traditionally, it takes more than eight months to identify high-producing, stable clones. Models trained on AI-native Tetra Data could shrink that time by 80% by better predicting which are the \u201csuper clones.\u201d TetraScience\u2019s new Lead Clone Assistant data app uses the NVIDIA <a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Fdeveloper.nvidia.com%2Fblog%2Fadvancing-cell-segmentation-and-morphology-analysis-with-nvidia-ai-foundation-model-vista-2d%2F&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=VISTA-2D+model&amp;index=3&amp;md5=765a6696faca2ff9a4ef552100192b5e\" rel=\"nofollow\" shape=\"rect\">VISTA-2D model<\/a> to analyze and classify hundreds of cellular images in minutes. It also applies the <a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Fdeveloper.nvidia.com%2Fblog%2Funlock-gene-networks-using-limited-data-with-ai-model-geneformer%2F&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=Geneformer&amp;index=4&amp;md5=32640888016cbccb0887c2ca1b6fa646\" rel=\"nofollow\" shape=\"rect\">Geneformer<\/a> model, accelerated and supported in the NVIDIA BioNeMo framework, to unearth gene expression differences between high-performing and problematic subpopulations, revealing details often missed in population-level studies.<\/p>\n<p>\n<b>About TetraScience<\/b><\/p>\n<p>\nTetraScience is the Scientific Data and AI Cloud with a mission to radically improve and extend human life. TetraScience is accelerating the Scientific AI revolution by designing and industrializing AI-native scientific datasets, which it brings to life in a growing suite of next-generation scientific data and lab data automation products and AI-enabled scientific use cases. For more information, visit <a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Ftetrascience.com%2F&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=tetrascience.com&amp;index=5&amp;md5=25f412f8264a3f0d06ad799ae663e562\" rel=\"nofollow\" shape=\"rect\">tetrascience.com<\/a> or follow us on <a target=\"_blank\" href=\"https:\/\/cts.businesswire.com\/ct\/CT?id=smartlink&amp;url=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ftetrascience%2Fmycompany%2F&amp;esheet=54151312&amp;newsitemid=20241112651874&amp;lan=en-US&amp;anchor=LinkedIn&amp;index=6&amp;md5=b71920b1dd93bec6706e4dbdd74982de\" rel=\"nofollow\" shape=\"rect\">LinkedIn<\/a>.<\/p>\n<p> <b>Contacts<\/b> <\/p>\n<p>\nMedia inquiries: Bruce Upbin, <a target=\"_blank\" href=\"&#x6d;a&#x69;&#108;&#x74;&#111;:&#x70;r&#x40;&#116;&#x65;&#116;r&#x61;&#115;&#x63;&#105;e&#x6e;c&#x65;&#46;&#x63;&#111;m\" rel=\"nofollow\" shape=\"rect\">&#x70;r&#x40;&#116;&#x65;&#116;&#x72;&#x61;s&#x63;&#105;&#x65;&#110;&#x63;&#101;&#46;&#x63;&#111;&#x6d;<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The collaboration aims to accelerate the adoption of scientific AI in the life sciences by producing AI-enabled use cases at an industrial scale. The work combines the foundational elements of scientific AI: compute, AI-native scientific data, domain-specific models, and scientific use case expertise. TetraScience aims to deliver scientific and economic impact across the life sciences &#8230; <span class=\"more\"><a class=\"more-link\" href=\"https:\/\/pharma-trend.com\/en\/tetrascience-collaborates-with-nvidia-to-industrialize-the-production-of-scientific-ai-use-cases\/\">[Read more&#8230;]<\/a><\/span><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-business","4":"post-60327","6":"format-standard","7":"category-industry"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>TetraScience Collaborates With NVIDIA to Industrialize the Production of Scientific AI Use Cases - Pharma Trend<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pharma-trend.com\/en\/tetrascience-collaborates-with-nvidia-to-industrialize-the-production-of-scientific-ai-use-cases\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"TetraScience Collaborates With NVIDIA to Industrialize the Production of Scientific AI Use Cases - Pharma Trend\" \/>\n<meta property=\"og:description\" content=\"The collaboration aims to accelerate the adoption of scientific AI in the life sciences by producing AI-enabled use cases at an industrial scale. 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