The collaboration is aimed at deepening comprehension of cell morphology, ultimately hastening the integration of AI-driven cellular analysis into diverse areas of cell biology and translational research
Deepcell partners with Nvidia to expedite use of generative AI in single-cell research. (Credit: Colin Behrens from Pixabay)
Deepcell, a life science company which brings artificial intelligence to cell biology, has partnered with Nvidia to expedite the advancement and widespread adoption of advanced computer vision solutions within the life sciences domain.
Already using the Nvidia A4000 and Nvidia AI technology, Deepcell plans to integrate Nvidia AI into its single-cell analysis technology. The integration involves a cooperative effort with Nvidia to jointly develop novel applications for generative AI and multimodal solutions in the field of cell biology.
The overarching objective of this collaborative venture is to deepen comprehension of cell morphology, ultimately hastening the integration of AI-driven cellular analysis into diverse areas of cell biology and translational research. This spans a wide spectrum of applications, encompassing cancer research, stem cell studies, and investigations into cell therapy.
While the potential applications of multimodal generative AI in life sciences are vast, their successful development and deployment necessitate domain-specific expertise and innovative adjustments to AI models tailored to the intricacies of life science applications.
Deepcell, in tandem with Nvidia, is uniquely positioned to leverage its technological prowess. The collaboration aims to provide AI models that optimally exploit innovative architectures and algorithms, coupled with multimodal and multiomic datasets. This synergistic approach enhances the generation of novel biological insights, reinforcing the integration of AI into the forefront of life sciences research.
Deepcell co-founder, president, and chief technology officer Mahyar Salek said: “Deepcell has catalysed the field of morpholomics and showcased the benefits of a revolutionary new method for single cell analysis using brightfield cell imaging and artificial intelligence.
“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 discoveries at unprecedented speed.”
As part of the collaboration, Deepcell intends to harness Nvidia’s computational proficiency and the Nvidia Clara suite to jointly create innovative algorithms tailored for the analysis of cell images.
The Nvidia Clara suite comprises computing platforms, software, and services designed to drive AI solutions in healthcare and life sciences, spanning applications from medical imaging and instrumentation to genomics and drug discovery.
The collaborative initiative seeks to propel the field of cell-based imaging forward, utilizing tools like the Deepcell REM-I platform.
Nvidia genomics alliances lead George Vacek said: “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.
“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.”
Last year, Deepcell introduced the REM-I platform and is set to fully launch the instrument, software, and AI model in 2024.
The REM-I platform stands out as a high-dimensional cell morphology analysis and sorting platform, seamlessly integrating single-cell imaging, sorting capabilities, and advanced high-dimensional analysis.
This convergence opens avenues for groundbreaking discoveries across various fields, such as cancer biology, developmental biology, stem cell biology, gene therapy, and functional screening, among others.
The comprehensive capabilities of the REM-I platform mark a significant stride in enabling novel methods of exploration and analysis in these diverse scientific domains.