MENLO PARK, Calif.–(BUSINESS WIRE)–#AI—Deepcell, a pioneer in artificial intelligence (AI)-powered single cell analysis to fuel deep biological discoveries, today announced a research collaboration with NVIDIA to accelerate the development and adoption of advanced computer vision solutions in life sciences. Deepcell, which already uses the NVIDIA A4000 and NVIDIA AI technology, will incorporate NVIDIA AI into its single cell analysis technology, working collaboratively with NVIDIA to codevelop new uses for generative AI and multimodal applications in cell biology. The joint collaboration aims to advance understanding of cell morphology, and ultimately accelerate the use of AI-powered cellular analysis in cell biology and translational research across a broad swath of applications including cancer, stem cell, and cell therapy.
There are many potential applications of multimodal generative AI in life sciences. However, the development and successful deployment of such tools requires domain-specific expertise, and innovation to the underlying AI models to account for the particulars of the life science application. Deepcell, in collaboration with NVIDIA, is uniquely positioned to leverage its technological strengths, to provide AI models that optimally leverage state-of-the-art architectures and algorithms along with multimodal and multiomic datasets, thereby enhancing the generation of novel biological insights.
“Deepcell has catalyzed the field of morpholomics and showcased the benefits of a revolutionary new method for single cell analysis using brightfield cell imaging and artificial intelligence,” said Mahyar Salek, Ph.D., Cofounder, President, and Chief Technology Officer at Deepcell. “As we look to the future, we see many possibilities for incorporating multimodal and generative AI into our platform, and leveraging our proprietary database of billions of cell images to train additional AI models. Our relationship with NVIDIA will help us accelerate such enhancements, and bring these advancements to our customers, enabling new discoveries at unprecedented speed.”
Through this collaboration, Deepcell plans to apply NVIDIA’s computing expertise and the NVIDIA Clara suite to codevelop novel algorithms for cell image analysis. NVIDIA Clara includes computing platforms, software, and services that power AI solutions for healthcare and life sciences, from medical imaging and instruments to genomics and drug discovery.
This work will advance the use of cell-based imaging, with tools such as the DeepcellⓇ REM-I platform, to boost morpholomics discovery and its application across the life sciences.
“Generative AI is revolutionizing many health-related disciplines, from basic life sciences research informing drug discovery to the diagnosis of medical conditions at the patient’s bedside,” said George Vacek, Genomics Alliances Lead at NVIDIA. “This collaboration will accelerate the development and adoption of generative AI tools in cell analysis, helping power future discoveries and their application in translational research.”
Deepcell announced the REM-I platform last year and will fully commercialize the instrument, software, and AI model in 2024. The REM-I platform is a high-dimensional cell morphology analysis and sorting platform that brings together single cell imaging, sorting, and high-dimensional analysis, enabling new methods of discovery in a wide range of fields including cancer biology, developmental biology, stem cell biology, gene therapy, and functional screening, among others.
For more information, visit www.deepcell.com.
About Deepcell
Deepcell is a life science company which brings artificial intelligence to cell biology, unlocking a new field of high-dimensional biological discovery known as morpholomics. Through Deepcell’s AI-powered imaging and microfluidics solution, the REM-I Platform, the company is enabling a new scale of cell biology research and single cell analysis leveraging cellular morphology for unbounded discovery. Deepcell’s platform leverages its artificial intelligence model, the Human Foundation Model, to identify and sort cells based on morphological distinctions helping power basic and translational research and offering future applications in diagnostic testing and therapeutics targeting. The company was spun out of Stanford University in 2017 and has raised nearly $100 million in venture capital. It is based in Menlo Park, California. Learn more at www.deepcell.com or follow us on LinkedIn, Twitter, and YouTube.
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