Deepcell Launches AI-Powered Single Cell Analysis Platform
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Deepcell has announced the launch of the REM-I Platform,
“Deepcell’s approach to bringing artificial intelligence into cellular analysis will revolutionize biological research, ushering in a new era of discovery,” Maddison Masaeli, PhD,
Cell morphology was one of the first ways cells were studied since the advent of the microscope. Despite recent advancements in microscopy and flow cytometry, existing tools for cellular quantification and characterization have left the field of cell biology hypothesis bounded and reliant on human interpretation, until now. With the new generation of AI and machine learning models like Deepcell’s Human Foundation Model, cell morphology can finally join other high-dimensional, single cell analysis methods and enable researchers to realize the full potential of the morpholome.
“In the launch of the REM-I Platform we are witnessing the realization of years of first principle thinking about the future of cell biology— a future liberated from the constraints of prior knowledge,” said Euan Ashley, MD, PhD, scientific cofounder of Deepcell, associate dean in the Stanford University School of Medicine and professor at Stanford University. “With the help of sophisticated artificial intelligence models, we can surpass the limits of what our eyes can see and peer ever more deeply into the biology of individual cells. I can’t wait to see what the scientific community does with this powerful new tool.”
REM-I Platform Enables Unbounded Single Cell Discovery and Analysis
Deepcell technology has been used to capture and characterize more than two billion images of single cells across a large variety of cell types. The Human Foundation Model, a self-supervised deep learning model trained on a subset of these unlabeled cellular images from a range of carefully selected biological samples, characterizes brightfield single cell images captured on the REM-I instrument and generates high-dimensional embedding data. Researchers can use the Axon data suite to access, visualize, and analyze these data in real-time and perform sorting of their cell groups of interest into up to six outlets on the REM-I instrument.
“Until now, the field of morphology has been limited to human interpretation of cellular features. Advancing morphology-powered discovery requires a new way of thinking to scale up and democratize single cell data generation and to enable unprecedented insights,” said Mahyar Salek, PhD, cofounder, president, and chief technology officer at Deepcell. “Advances in machine learning will transform our understanding of cell phenotype akin to the way next-generation sequencing transformed our understanding of the genome.”
Deepcell launched its Technology Access Program with the Translational Genomics Research Institute as well as University of California San Francisco, which leveraged the technology to study human cell lines, bodily fluids, and solid tissues as part of cancer research and drug screening projects.
The company recently completed its first European installation of the Deepcell technology through its Technology Access Program at the Erasmus Medical Center in Rotterdam, which will use the instrument to study immune therapies from cancer patient samples.
“The Deepcell platform gives us the ability to discriminate between activated and naive T cells and provides next-level detection of therapy response in peripheral blood mononuclear cells derived from patients treated with immune therapies for cancer,” said Peter van der Spek, professor, Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center. “Pathologists can increase the throughput of samples and assess many more cells than by conventional light microscopy.”
The REM-I Platform is available for orders and expected to begin shipping to customers in early 2024.
CYTO Presentations Validate Deepcell’s AI-Driven Approach to High-Dimensional Biology
Three scientific abstracts sharing data developed by Deepcell scientists were selected for scientific talks at CYTO 2023 from among hundreds of submissions. In addition to these presentations, the company will also reveal the REM-I instrument and demonstrate its capabilities at the conference.
Presentation Title: Deep learning models capture multi-dimensional features for cell morphology analysis from brightfield images
Time and Location: May 22 at 10:30 a.m. in room 512B
Presenter: Mahyar Salek, PhD, president, chief technology officer, and cofounder, Deepcell
Presentation Title: A novel platform using deep learning to perform label-free multi-dimensional morphology analysis for biological discoveries
Time and Location: May 24 at 10:30 a.m. in room 511E
Presenter: Maddison Masaeli, PhD, cofounder and chief executive officer, Deepcell
Presentation Title: Multi-omics analysis integrating deep learning morphology profiling and single cell RNA-seq reveals lung tumor heterogeneity and enriches tumor sub-populations
Time and Location: May 24 at 10:30 a.m. in room 512B
Presenter: Nicholas Banovich, PhD, chief scientist, Deepcell
For more information about the Deepcell’s activities at CYTO 2023, visit booth #238.
