Deepcell Expands AI-Powered Morphology Characterization for Biological Researchers, Announces UCSF and TGen as First Installations in Technology Access Program | Tech Rasta


Menlo Park, Calif.–(Business Wire)–DeepCell, a life science company pioneering AI-based single-cell morphology characterization technology for biology and translational research, today announced the release of the next phase of its Technology Access Program (TAP). Deepcell Platform. The University of California, San Francisco (UCSF) and the Translational Genomics Research Institute (TGen), part of City of Hope, are the initial locations to install the first-generation DeepCell platform through the TAP program, which is expanding to three. More sites across the US and Europe.

“We have taken a significant step forward in our technology access program to bring the power of our DeepCell platform into the hands of end users,” said Mark Montserrat, Chief Business Officer of DeepCell. “Having world-renowned researchers apply DeepCell technology to investigate morphological differences in a wide range of applications using cell filaments as well as primary body fluid and solid tissue samples will accelerate the commercial deployment of our AI-powered single-cell image analysis and isolation platform for cell biology. to generate novel insights.” The possibilities for how the Deepcell platform can be used are vast.

“We are excited to be one of the first institutions to access the DeepCell platform in our own lab,” said Dr. Hani Gudarji, associate professor in the Department of Biochemistry & Biophysics at UCSF. “Using DeepCell technology, we aim to study time-course morphological changes in drug-treated lymphoblast cells. This will allow us to understand drug response and efficacy in ways not possible before. I am pleased with the initial results and we already have many other research ideas that can be started with this technology.

“We are excited to be part of the Technology Access Program testing the DeepCell platform. Our goal is to characterize tumor cells found in malignant effusions from patients with metastatic breast cancer. Using this technology, we are able to label-freely enrich rare tumor cells from these fluids,” said Mark Magbanua, MD, Laboratory Medicine at UCSF. and can be isolated. Initial results from copy number profiling of enriched tumor cell fractions show genetic alterations consistent with those frequently seen in breast cancer. Next, we plan to test the feasibility of single-cell RNA sequencing of extracted tumor cells in malignant effusions using the DeepCell platform to further elucidate the pathobiology of the disease. Evaluating the unique tumor microenvironment provides an opportunity to look at tumor biology in a unique niche that behaves differently than solid tumors, which may ultimately lead to novel therapeutic targets. helps to achieve.”

DeepCell pioneered the innovative area of ​​single-cell biology analysis focused on multidimensional readouts of cell morphology at a scale without the use of cellular markers. The company has developed an AI-based technology that iteratively learns to identify and capture single cells based on morphological characteristics that are undetectable to the human eye. Groups of morphologically similar cells can be extracted without disturbing or affecting viability for downstream molecular analysis. By unlocking the power of morphology for cell biology, DeepCell is advancing the use of deep learning capabilities to understand cellular heterogeneity in greater detail.

With a multi-phase approach, Deepcell is driving its AI-based platform towards commercialization. The company is well positioned to set a new standard for the industry with AI-centric single cell morphology analysis for applications in complex samples, cell atlasing, cell and gene therapy, functional screening, cancer biology and stem cell characterization. Research.

“It is exciting to begin operating the instrument in-house at TGen as part of the Technology Access Program. “Our goal is to explore the use of this device for translational research in determining how melanoma tumor cells respond to different treatments,” said Candice Wike, Ph.D., TGen’s Scientific Technology Assessment Research Team Manager.

Expanding the adoption of quantitative single-cell morphology

Deepcell held its inaugural Scientific Summit last month in San Jose, California with a select group of experts and innovators in pathology, imaging cytometry, computational biology and molecular biology. At the event, scientific leaders from across the US, Europe and Asia heard about the latest data from Deepcell, provided their feedback on technology roadmaps, and worked together to create clear data generation studies that will help advance adoption. High-content morphology across life sciences and biotech.

“There is no doubt that cellular ‘form’ is linked to cellular function. “The team at DeepCell has developed technology that can select cells in flow based on morphometric characteristics that have both discovery science and clinical research applications,” says Dr. Andrew Philby, IMA Theme Lead and FCCF Director at Newcastle University. It means that.”

Deepcell has announced that it will support researchers’ efforts to include multidimensional morphology assessment in their grant applications. The company has developed a series of writing resources to illustrate the technology that researchers can tap into for writing assistance. Scientists interested in hearing more about DeepCell technology or including DeepCell technology in their grants can contact DeepCell directly at: info@deepcellbio.com.

About Deepcell

DeepCell is advancing the understanding of cell biology by combining AI and advances in high-throughput, quantitative cell classification and single cell capture to provide novel insights through an unprecedented view of cell biology. Founded in 2017, the company has created a unique, microfluidics-based technology that uses continuous learning AI to classify cells based on detailed visual characteristics without labeling and capture them based on their morphological profiles without inherent bias. The DeepCell platform manages cell viability for downstream molecular analysis. Deepcell is privately held and based in Menlo Park, CA. For more information, please visit www.deepcell.com.



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