Researchers demonstrate the utility of Deepcell platform for label-free isolation and
enrichment of cancer cells using deep learning.
MENLO PARK, Calif. — November 10, 2021 — Deepcell, a life science company pioneering
AI-powered cell classification and isolation for basic and translational research, today
announced that Dr. Yipeng Geng, MD, PhD, a collaborator and research fellow within the Rao
Lab in the Department of Pathology and Laboratory Medicine at the David Geffen School of
Medicine at UCLA, will present new data generated on the Deepcell platform. The data will be
unveiled at the 69 th annual scientific meeting of the American Society of Cytopathology (ASC).
“We are delighted that our collaborators are presenting the new data. Isolation and enrichment
of cancer cells in body fluids for cytological and molecular analysis have significant implications
in personalized management of cancer patients, but current methods are inadequate,” said
Maddison Masaeli, Co-founder and CEO of Deepcell. “The data shows that the Deepcell
platform can identify and enrich malignant cells at high performance, setting the stage to enable
label-free enrichment of cells of interest for the diagnosis and study of cancer cells in body
Advancements in deep learning have significantly improved the accuracy to resolve a wide
range of image classification issues. This breakthrough has unlocked the opportunity to develop
a rapid, more scalable approach to isolate and enrich cancer cells for downstream cytological
and molecular analysis. Using the novel Deepcell technology, Dr. Jianyu Rao, MD, and Dr Geng
at UCLA generated a classifier model to discriminate carcinoma cells from non-carcinoma cells
in 20 body fluid samples, including four with metastatic carcinomas.
Dr. Jianyu Rao, MD is a vice chair of the department of pathology and chief of cytopathology at
UCLA. The Rao Lab is advancing cancer research through an innovative approach to studying
cytology samples. The collaboration with Dr. Rao and his team of researchers is focused on
using Deepcell’s AI-powered platform to identify and sort cancer cells from clinical cytology
samples of body fluids (e.g. ascitic or pleural fluid) based entirely on morphological distinctions
‒ or the visual features of cells ‒ rather than on labeling or using biomarkers.
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.
Details of the presentation of the data:
ASC’s 69 th Annual Scientific Meeting, Platform Session
Date & Time: Friday, November 12, 2021 at 5pm
Presenter: Yipeng Geng, MD, PhD, fellow at UCLA’s David Geffen School of Medicine
Title of the Presentation: “Developing A Deep Learning Approach for Label-free Isolation &
Enrichment of Cancer Cells in Body Fluids for Cytological and Molecular Analysis”
For more information about Deepcell, go to www.deepcell.com.
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.