Clinical researcher who uses the Deepcell platform for label-free isolation and enrichment of cancer cells is recognized for contributions to improve the understanding of cell biology
MENLO PARK, Calif. — November 30, 2021 — Deepcell, a life science company pioneering AI-powered cell classification and isolation for basic and translational research, today announced that a UCLA team has won the 2021 Geno Saccomanno, MD New Frontiers in Cytology Award for their work, using the Deepcell platform as their core capabilities for the analysis of cancer cells.
Dr. Yipeng Geng, MD, PhD, a clinical research fellow within the Rao Lab in the Department of Pathology and Laboratory Medicine at the David Geffen School of Medicine at UCLA, presented data at the 69th annual scientific meeting of the American Society of Cytopathology (ASC) and was recognized with this prestigious cytology award for the team’s work on isolating and enriching cancer cells in body fluids using the Deepcell technology. Her research demonstrated the potential of the technology and highlighted significant implications in the personalized management of cancer patients.
Established in 1993, the Geno Saccamanno, MD New Frontiers in Cytology Award recognizes research that contributes to a better understanding of cell biology or enhances diagnosis by showing significant innovation, good study design and potential diagnostic utility.
“We are very appreciative of the support of Dr Rao and want to congratulate Dr. Geng for her winning the New Frontiers in Cytology Award for her presentation at ASC. The work that she and her colleagues are doing is important because it sets the stage for the label-free enrichment to go beyond the cytology slide by augmenting the ability of researchers to understand cell biology and ultimately improve patient care. We are looking forward to strengthening our collaboration program with UCLA and other centers,” said Maddison Masaeli, Co-founder and CEO of Deepcell.
The data in Dr. Geng’s presentation showed that the Deepcell platform can identify and enrich malignant cells at high performance. Deepcell’s novel technology enabled Dr. Geng and her colleagues at the Rao Lab at UCLA to rapidly and reliably enrich cancer cells for downstream molecular analysis.
The Deepcell platform combines high-resolution imaging of cells in flow with real-time cell classification and sorting, using cell morphology as the only analyte. This label-free, target-agnostic approach overcomes some of the limitations of cell surface marker-based classification and enrichment. Deepcell’s unique AI-powered technology transforms cell morphology into a precise, reproducible and unbiased analyte that enables highly accurate cell classification while maintaining cell viability.
For more information about Deepcell, go to www.deepcell.com.
About Deepcell
Deepcell is helping to advance precision medicine by combining advances in AI, cell classification and capture, and single-cell analysis to deliver novel insights through an unprecedented view of cell biology. Spun out of Stanford University in 2017, the company has created unique, microfluidics-based technology that uses continuously learning AI to classify cells based on detailed visual features and sort them without inherent bias. The Deepcell platform maintains cell viability for downstream single-cell analysis and can be used to isolate virtually any type of cell, even those occurring at frequencies as low as one in a billion. The technology will initially be available as a service for use in translational research as well as diagnostics and therapeutic development. Deepcell is privately held and based in Menlo Park, CA. For more information, please visit deepcellbio.com.
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