Company announces launch of collaboration program with researchers and medical
MOUNTAIN VIEW, Calif. — June 8, 2021 — Deepcell, a life science company pioneering AI-
powered cell classification and isolation for cell biology and translational research, today
announced a collaboration with Dr. Jianyu Rao, MD, a vice chair of the department of pathology
and chief of cytopathology at the University of California at Los Angeles (UCLA), to advance
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. This collaboration aims to enable
increased accuracy of cell classification and deliver intact cells for molecular analysis.
Deepcell’s platform for cell analysis includes a microfluidic-based imaging, real-time sorting
system, powered by deep learning. The collaboration allows Deepcell to continue to expand
their Cell Morphology Atlas and to demonstrate the performance of the platform.
“Cytologic analysis on a self-learning AI platform for cancer research could lead to a better
understanding of the biology of malignant cells and contribute to future diagnosis and improved
patient outcomes,” said Dr. Rao, who is an internationally renowned cytopathologist and the
director of Cytopathology, the director of gynecological pathology, and the medical director of
the cytotechnology school. “Before Deepcell, cell morphology was limited by human
interpretation and a lack of adequate tools for capturing and studying abnormal cells. Through
the combination of AI, microfluidics, and single-cell analysis, the Deepcell platform provides a
new way of understanding these cells.”
This collaboration is the first to be announced as part of Deepcell’s new collaboration program
with scientific researchers and medical experts. This initiative is designed to form a series of
partnerships that will unlock the potential of single-cell, morphology-based sorting and analysis.
The goals of the program are to demonstrate the performance of the Deepcell platform,
continue to expand a unique Cell Morphology Atlas for the benefit of the scientific and medical
communities, and co-develop AI models for specific applications.
“The launch of Deepcell’s collaboration program formalizes our engagement with leaders across
basic and translational research and opens up a new phase for Deepcell,” said Maddison
Masaeli, Co-founder and CEO of Deepcell. “It is by focusing on the science and making Dr. Rao
and future collaborators successful in their particular field that we will realize our vision to create
a new lexicon for single cell morphology, paving the path that connects the genome to the
Deepcell was spun out of Stanford in 2017 to re-invent single cell analysis by creating a new
quantitative dimension of cell morphology. Since then, the company has developed its AI-
powered technology to characterize, identify and sort cells relying solely on cell morphology.
Deepcell’s technology is able to differentiate among cell types with a novel approach compared
to traditional cell isolation techniques that rely on antibody staining or similar methods. Unlike
other approaches, Deepcell’s technology was developed to profile samples, and isolate and
collect label-free cells of any type, keeping the cell intact for downstream biological
characterization. The technology combines advances in AI, cell capture, and single-cell analysis
to identify and sort cells based on detailed visual features.
For more information about Deepcell or future collaborations with Deepcell, go to
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 Mountain
View, CA. For more information, please visit deepcellbio.com.